Note : Les descriptions sont présentées dans la langue officielle dans laquelle elles ont été soumises.
TEXT INFORMATION EXTRACTING METHOD, DEVICE, COMPUTER
EQUIPMENT AND STORAGE MEDIUM
BACKGROUND OF THE INVENTION
Technical Field
[0001] The present invention relates to the field of data processing
technology, and more
particularly to a text information extracting method, and corresponding
device, computer
equipment and storage medium.
Description of Related Art
[0002] Announcement text information in the field of finance is usually
extremely complicated
and lengthy, for example, such common texts of types relevant to public
prospectuses,
contract announcements, etc. They are usually merged and summarized from
information
in the order of magnitude reaching several hundred pages. As for the fund
information
extracting task, it is modus operandi in the art to copy and extract the
information through
manual operation and maintenance, or through the simple regular expression
extraction.
[0003] However, the aforementioned traditional processing modes are defective
more or less
apparently. For instance, the purely manual information extraction mode
necessitates
extremely large workload that includes many repetitive works, so the mode is
low in
efficiency and high in manpower cost. As for the simple regular expression
extraction,
the problem of missing extraction of information might occur, in particular
when the
volume of text published by an announcement is extremely large, information
extraction
errors usually occur due to information similarity between different chapters
and
paragraphs, and a great deal of manpower is required for proofreading and
checking. In
addition, since different fund issuers do not have a unified structural
requirement on
1
Date Recue/Date Received 2022-02-08
characters, the descriptive texts of find status changes are usually merged
and elliptically
described to differing extents, and all these practices also cause failures to
the regular
expression extraction mode.
[0004] In short, there is an urgent need to propose a novel long text
information extracting
method to address the aforementioned problems.
SUMMARY OF THE INVENTION
[0005] In order to solve problems pending in the state of the art, embodiments
of the present
invention provide a long text information extracting method, and corresponding
device,
computer equipment and storage medium, so as to overcome the problems existing
in the
prior-art technology in which workload for information extraction is large,
efficiency is
low and manpower cost is high, and missing and errors tend to occur.
[0006] To solve one or more of the aforementioned technical problem(s), the
present invention
employs the following technical solutions.
[0007] According to the first aspect, there is provided a long text
information extracting method
that comprises the following steps:
[0008] obtaining a text to be extracted and an extracting rule corresponding
to the text to be
extracted, wherein the extracting rule includes an extracting field;
[0009] determining, based on a file directory of the text to be extracted, a
chapter location of
each piece of directory information of the file directory in the text to be
extracted, and
generating chapter information;
[0010] partitioning the chapter information according to a preset rule, and
generating a
corresponding partition list; and
[0011] generating key-value pair information corresponding to the text to be
extracted according
to the partition list and the extracting rule and storing the information into
a database,
2
Date Recue/Date Received 2022-02-08
wherein the key includes an extracting field, and the value includes the
partition list and
target information corresponding to the extracting field.
[0012] Further, the partition list includes paragraph lists and sentence
lists, and the step of
partitioning the chapter information according to a preset rule, and
generating a
corresponding partition list includes:
[0013] partitioning each piece of the chapter information into paragraphs
according to preset
paragraph features, and generating corresponding paragraph lists respectively;
and
[0014] partitioning each paragraph in each paragraph list into sentences
according to preset
sentence features, and generating corresponding sentence lists respectively.
[0015] Further, when the target information corresponding to the extracting
field is long text
information, the step of generating key-value pair information corresponding
to the text
to be extracted according to the partition list and the extracting rule and
storing the
information into a database includes:
[0016] determining a first paragraph or a first sentence in the partition list
in which the extracting
field locates, and determining a second paragraph adjacent to the first
paragraph or a
second sentence adjacent to the first sentence;
[0017] searching for the first paragraph and the second paragraph or the first
sentence and the
second sentence by use of a preset searching rule, and determining the target
information
corresponding to the extracting field; and
[0018] generating key-value pair information corresponding to the text to be
extracted according
to the extracting field and the target information and storing the information
into a
database.
[0019] Further, when the target information corresponding to the extracting
field is short text
information, the step of generating key-value pair information corresponding
to the text
to be extracted according to the partition list and the extracting rule and
storing the
information into a database includes:
3
Date Recue/Date Received 2022-02-08
[0020] performing a target detection process on the sentences in the partition
list, and obtaining
the target information corresponding to the extracting field; and
[0021] generating key-value pair information corresponding to the text to be
extracted according
to the extracting field and the target information and storing the information
into a
database.
[0022] Further, when the extracting field is status change, the step of
generating key-value pair
information corresponding to the text to be extracted according to the
partition list and
the extracting rule and storing the information into a database includes:
[0023] obtaining business status change information in the sentence lists
according to the
extracting rule, and generating key-value pair information corresponding to
the text to be
extracted according to the business status change information and the
extracting field and
storing the information into a database.
[0024] Further, prior to storing the key-value pair information into a
database, the method further
comprises:
[0025] denoising the key-value pair information, and storing the denoised key-
value pair
information into the database.
[0026] Further, the extracting rule includes a regular expression.
[0027] According to the second aspect, there is provided a text information
extracting device that
comprises:
[0028] a data obtaining module, for obtaining a text to be extracted and an
extracting rule
corresponding to the text to be extracted, wherein the extracting rule
includes an
extracting field;
[0029] a chapter obtaining module, for determining, based on a file directory
of the text to be
extracted, a chapter location of each piece of directory information of the
file directory in
the text to be extracted, and generating chapter information;
4
Date Recue/Date Received 2022-02-08
[0030] a data partitioning module, for partitioning the chapter information
according to a preset
rule, and generating a corresponding partition list; and
[0031] an information generating module, for generating key-value pair
information
corresponding to the text to be extracted according to the partition list and
the extracting
rule and storing the information into a database, wherein the key includes an
extracting
field, and the value includes the partition list and information corresponding
to the
extracting field.
[0032] According to the third aspect, there is provided a computer equipment
that comprises a
memory, a processor and a computer program stored on the memory and operable
on the
processor, and the following steps are realized when the processor executes
the computer
program:
[0033] obtaining a text to be extracted and an extracting rule corresponding
to the text to be
extracted, wherein the extracting rule includes an extracting field;
[0034] determining, based on a file directory of the text to be extracted, a
chapter location of
each piece of directory information of the file directory in the text to be
extracted, and
generating chapter information;
[0035] partitioning the chapter information according to a preset rule, and
generating a
corresponding partition list; and
[0036] generating key-value pair information corresponding to the text to be
extracted according
to the partition list and the extracting rule and storing the information into
a database,
wherein the key includes an extracting field, and the value includes the
partition list and
target information corresponding to the extracting field.
[0037] According to the fourth aspect, there is provided a computer-readable
storage medium
storing a computer program thereon, and the following steps are realized when
the
computer program is executed by a processor:
[0038] obtaining a text to be extracted and an extracting rule corresponding
to the text to be
extracted, wherein the extracting rule includes an extracting field;
Date Recue/Date Received 2022-02-08
[0039] determining, based on a file directory of the text to be extracted, a
chapter location of
each piece of directory information of the file directory in the text to be
extracted, and
generating chapter information;
[0040] partitioning the chapter information according to a preset rule, and
generating a
corresponding partition list; and
[0041] generating key-value pair information corresponding to the text to be
extracted according
to the partition list and the extracting rule and storing the information into
a database,
wherein the key includes an extracting field, and the value includes the
partition list and
target information corresponding to the extracting field.
[0042] The technical solutions provided by the embodiments of the present
invention bring about
the following advantageous effects.
[0043] In the text information extracting method, and corresponding device,
computer
equipment and storage medium provided by the embodiments of the present
invention,
by obtaining a text to be extracted and an extracting rule corresponding to
the text to be
extracted, wherein the extracting rule includes an extracting field,
determining, based on
a file directory of the text to be extracted, a chapter location of each piece
of directory
information of the file directory in the text to be extracted, and generating
chapter
information, partitioning the chapter information according to a preset rule,
and
generating a corresponding partition list, and generating key-value pair
information
corresponding to the text to be extracted according to the partition list and
the extracting
rule and storing the information into a database, wherein the key includes an
extracting
field, and the value includes the partition list and target information
corresponding to the
extracting field, on the one hand, the present invention enhances the
efficiency of text
extraction, avoids such problems as missing from and error in information
extraction, and
enhances the precision of text extraction, on the other hand, by dividing the
long text, the
present invention avoids the circumstance of infinite backtracking that might
be
encountered in regular matching, enhances fault tolerance rate of codes, and
reduces time
6
Date Recue/Date Received 2022-02-08
consumption in the overall operation.
[0044] In the text information extracting method, and corresponding device,
computer
equipment and storage medium provided by the embodiments of the present
invention,
by partitioning each piece of the chapter information into paragraphs
according to preset
paragraph features, and generating corresponding paragraph lists respectively,
and
partitioning each paragraph in each paragraph list into sentences according to
preset
sentence features, and generating corresponding sentence lists respectively,
the text is
precisely positioned to the levels of chapter, paragraph and sentence through
the directory
hierarchy positioning mode, so that to effect precise positioning and to
extract relevant
information from the text to be extracted.
[0045] In the text information extracting method, and corresponding device,
computer
equipment and storage medium provided by the embodiments of the present
invention,
by denoising the key-value pair information and storing the denoised key-value
pair
information into the database, the key-value pair information extracted from
the text is
further screened and filtered, whereby the precision in long text information
extraction is
effectively enhanced.
BRIEF DESCRIPTION OF THE DRAWINGS
[0046] To more clearly describe the technical solutions in the embodiments of
the present
invention, drawings required to illustrate the embodiments will be briefly
introduced
below. Apparently, the drawings introduced below are merely directed to some
embodiments of the present invention, while persons ordinarily skilled in the
art may
further acquire other drawings on the basis of these drawings without spending
creative
effort in the process.
[0047] Fig. 1 is a flowchart illustrating a fund announcement long text
information extracting
7
Date Recue/Date Received 2022-02-08
method according to an exemplary embodiment;
[0048] Fig. 2 is a flowchart illustrating a fund status change information
extracting method
according to an exemplary embodiment;
[0049] Fig. 3 is a flowchart illustrating a text information extracting method
according to an
exemplary embodiment;
[0050] Fig. 4 is a view schematically illustrating the structure of a text
information extracting
device according to an exemplary embodiment; and
[0051] Fig. 5 is a view schematically illustrating the internal structure of a
computer equipment
according to an exemplary embodiment.
DETAILED DESCRIPTION OF THE INVENTION
[0052] To make more lucid and clear the objectives, technical solutions and
advantages of the
present invention, the technical solutions in the embodiments of the present
invention will
be clearly and comprehensively described below with reference to the
accompanying
drawings in the embodiments of the present invention. Apparently, the
embodiments as
described are merely partial, rather than the entire, embodiments of the
present invention.
Any other embodiments makeable by persons ordinarily skilled in the art on the
basis of
the embodiments in the present invention without creative effort shall all
fall within the
protection scope of the present invention.
[0053] As noted in the Description of Related Art, as regards such common
information
disclosure texts of types relevant to fund information public prospectuses and
fund
contracts, etc., they are usually merged and summarized from information in
the order of
magnitude reaching several hundred pages. Accordingly, the workload in
information
8
Date Recue/Date Received 2022-02-08
extraction of these types of texts is extremely large, and such problems as
missing and
errors tend to occur.
[0054] To solve the above problems, a text information extracting method is
creatively proposed
in the embodiments of the present invention, starting from the document
structure of the
text to be extracted, the method precisely positions the text to the levels of
chapter,
paragraph and sentence through the directory hierarchy positioning mode; with
respect to
the extraction of generalization information in the text to be extracted,
sentences and
paragraphs are taken as input data, data information required to be extracted
is
automatically detected through a scheme of multiple rules, and denoising and
calibration
are performed thereon, so as to obtain key-value pair information to which the
generalization information corresponds; likewise, with respect to the
extraction of status
change information of the business involved in the text to be extracted, a
parts of speech
hierarchy is established for the descriptive words of statuses, and a status
change list is
extracted through the combination form of [action-business]. The precision of
information extraction is not only ensured, but the problems of missing for
and errors in
information extraction are also avoided; moreover, by dividing the long text,
the present
invention avoids the circumstance of infinite backtracking that might be
encountered in
regular matching, enhances fault tolerance rate of codes, and reduces time
consumption
in the overall operation.
[0055] Embodiment 1
[0056] Specifically, as shown in Fig. 1, taking for example a fund-related
disclosure text, the
process of employing the aforementioned method to extract information from a
fund
announcement long text includes the following steps.
[0057] Step 1 ¨ obtaining an original long text sequence of information to be
extracted, wherein
the original long text sequence includes a fund announcement long text.
9
Date Recue/Date Received 2022-02-08
[0058] Specifically, the text to be extracted here mainly includes such
disclosure texts of the
types relevant to fund information disclosure prospectuses and fund contracts
obtained
from official websites that make public disclosure information. As should be
noted here,
the disclosure texts of the types relevant to fund information disclosure
prospectuses and
fund contracts in the embodiments of the present invention are merely by way
of example,
and do not constitute any restriction in the embodiments of the present
invention, besides
the aforementioned long texts, the method provided by the embodiments of the
present
invention is also applicable to information extraction of other long texts
having fixed
directory structures.
[0059] Step 2 ¨ configuring an extracting rule for information extraction of
the announcement
long text.
[0060] Specifically, this process is mainly directed to infusing an extracting
rule to subsequent
steps. The extracting rule includes, but is not limited to, regular statements
of
configuration files and external artificial rule citations, in which regular
expressions of
identical extracting fields can be used in superimposition, and the external
artificial rule
citations are mainly used to configure such information as fields required to
be extracted
by the user; during specific implementation, an external artificial rule
citation can be
imported in a form file format, and can also be configured via a backstage
operation and
maintenance platform. As should be noted here, in the embodiments of the
present
invention, the extracting rule is embodied in the mode of a combination of
multiple rules,
thus making it possible to effectively enhance the efficiency and precision of
long text
information extraction.
[0061] Step 3 ¨ positioning a chapter in which directory information locates
according to a file
directory of the announcement long text, and generating chapter information.
Date Recue/Date Received 2022-02-08
[0062] Specifically, what the method provided by the embodiments of the
present invention
processes are mainly long texts having fixed directory structures, and the
directory
information is usually the title information of each chapter. As a preferred
example, while
a chapter in which the directory information locates is being positioned, the
directory
information can be used as an extracting field to automatically position and
extract the
chapter in which the field locates through a preset screening function of
chapter
positioning, and to generate corresponding chapter information, which includes
the title
and the entire content of the chapter. During specific implementation, chapter
blocks in
Chinese documents can usually be positioned through regular expressions.
[0063] Step 4 ¨ partitioning the chapter information, and generating
corresponding paragraph
lists and sentence lists.
[0064] Specifically, the chapter information generated in the aforementioned
step is further
finely processed into paragraph text blocks and sentence text blocks, and
paragraph lists
and sentence lists are respectively generated. During specific implementation,
while
paragraphs are being partitioned, it is possible to segment the text inside
the chapter into
paragraphs according to paragraph features. Features of Chinese paragraphs
include, but
are not limited to, a blank at the end of a paragraph line and an indent at
the start of a
paragraph line, etc. While sentence partition is being performed, a previously
generated
paragraph is further extracted according to sentence features, and the
paragraph is re-
partitioned into sentences. Sentence features include, but are not limited to,
a full stop, an
exclamatory mark, etc.
[0065] Step 5 ¨ performing information extraction on the paragraph lists and
the sentence lists
according to the extracting rule configured in step 2, and obtaining key-value
pair
information to which the announcement long text corresponds.
[0066] Specifically, here the key in the key-value pair information is an
extracting field defined
11
Date Recue/Date Received 2022-02-08
in the extracting rule, and the value is relevant information extracted from
the paragraph
lists and the sentence lists in accordance with the extracting field and
according to the
extracting rule. During specific extraction, different pieces of information
can employ
different extracting modes. For instance, partial values in fund
generalization information
are text descriptive information, so such information may be one paragraph,
several
sentences, or one sentence, and the concept of adjacent sentence (or
paragraph) is
introduced here for searching. For instance, when a certain paragraph or
sentence to
which the extracting field corresponds ends with a colon, usually the content
following
the colon is the information required to be extracted, at this time the
paragraph or sentence
following the colon is taken as the extracted target information. When the
value required
to be extracted is also short information of a specific type, for instance,
the information
required to be extracted is a date, while such information is usually
intermingled in a
sentence, it is possible at this time to employ the mode of target detection
to extract the
relevant information contained in the sentence.
[0067] Step 6 ¨ denoising the key-value pair information, and obtaining the
key-value pair
information thus processed.
[0068] Specifically, a series of output values (namely the key-value pair
information) can be
obtained through the foregoing steps. Although the paragraph to which the
information
corresponds has been precisely positioned, some noises might be present in
these output
values, even some cases of disorderly extraction might appear. In order to
solve this
problem, a numerical value denoising filter is introduced in the embodiments
of the
present invention to further purify redundant or unreasonable results. The
denoising
process includes, but is not limited to, numerical value type verification
(for in-sentence
numerical value cleaning), numerical value cutoff extraction (for use in inter-
sentence
information), etc., to which no explanation is redundantly made in this
context.
[0069] Step 7 ¨ subjecting the denoised key-value pair information to manual
check and
12
Date Recue/Date Received 2022-02-08
verification, and storing the manually checked and verified key-value pair
information
into a database.
[0070] Specifically, the manually checked and verified information can serve
as fund foundation
information supplying a series of fund diagnostic and screening bases and
providing data
support for internal and external platforms.
[0071] Specifically, during specific implementation of the aforementioned
steps, a PySpark big
data task can be deployed on a pre-constructed big data cloud platform for
routinely
incrementally processing fund information extracting tasks, and output results
are stored
in a Hive table, whereby is made possible to analyze and probe the long text
in real time
within the order of several minutes.
[0072] Specifically, as shown in Fig. 2, taking a fund status change
announcement text for
example, a fund status change information extracting method is further
provided in the
embodiments of the present invention, and the process thereof includes the
following
steps.
[0073] Step RO ¨ extracting a corresponding sentence list from a fund status
change
announcement text, analyzing the extracted sentence list and an announcement
title of the
status change announcement text, and obtaining an analyzing result.
[0074] Specifically, the specific process of extracting a sentence list from a
fund status change
announcement text can be inferred from the specific contents of the foregoing
steps 1 to
4, and no repetition is made in this context. As should also be noted here,
the fund status
announcement text in the embodiments of the present invention is merely by way
of
example, and does not constitute any restriction in the embodiments of the
present
invention, besides the fund status change announcement text, the status change
information extracting method provided by the embodiments of the present
invention is
13
Date Recue/Date Received 2022-02-08
also applicable to information extraction of other long texts having fixed
directory
structures.
[0075] Specifically, since the titles of some announcement texts also contain
information
required to be extracted, the title of the announcement should be taken
together into
consideration while status change is being analyzed. For instance, the title
of a certain
announcement text reads "Announcement Relating to Temporary Stop of Large-sum
Subscription, Fixed Investment and Conversion & Transfer Businesses of xx
Money
Market Fund", the "Temporary Stop of Large-sum Subscription, Fixed Investment
and
Conversion & Transfer Businesses" in the title is also information required to
be extracted.
[0076] Step R1 ¨ performing action extraction on the analyzing result, and
obtaining action
information.
[0077] Specifically, in the embodiments of the present invention, action
information includes
action type words appearing in the announcement text and the title. The action
type words
here are mainly differentiated according to the part of speech, and action
type words
relevant to business status change frequently seen in the field of finance
include open,
temporarily stop, restore and restrict, etc.
[0078] Step R2 ¨ performing business extraction on the analyzing result, and
obtaining business
information.
[0079] Specifically, in the embodiments of the present invention, business
information includes
such nouns of business properties appearing in the announcement text and the
title as
subscription, redemption, fixed investment, conversion and transfer, etc.
Since business
change involves status and sum of money, business nouns are further combined
with some
modifiers in the embodiments of the present invention to come up with new
business
terms, as such status change similar to "large-sum redemption". In addition,
business
14
Date Recue/Date Received 2022-02-08
further involves some common phrases, bynames and abbreviations, and these
will also
be uniformly replaced at this step in the embodiments of the present
invention.
[0080] Step R3 ¨ generating status change information according to the action
information and
the business information.
[0081] Specifically, the action and business phrases extracted and obtained in
the foregoing steps
are arranged and combined, and matched with enumerated values of the status
change to
obtain a completed change list (namely status change information).
[0082] Step R4 ¨ verifying the status change information, and storing the
verified information
into a database.
[0083] Specifically, when the status change information is stored in the
database, storage can
likewise be effected by the mode of key-value pair, during specific
implementation, the
"status change" field is taken as the key, and the specific status change
information as
extracted is taken as the value.
[0084] Specifically, in the embodiments of the present invention, the reason
why to divide into
action and business in the change status is because actions or businesses in
the statuses
are described considerably elliptically in such long texts as fund disclosure
texts (for
instance, "temporary stop of subscription, redemption" actually expresses two
status
changes of temporary stop of subscription and temporary stop of redemption).
The
division can effectively alleviate the above circumstance, and even avoid the
circumstance of incomplete extraction due to information dislocation and
information
ellipsis.
[0085] Embodiment 2
Date Recue/Date Received 2022-02-08
[0086] Fig. 3 is a flowchart illustrating a text information extracting method
according to an
exemplary embodiment. With reference to Fig. 3, the method comprises the
following
steps.
[0087] Si ¨ obtaining a text to be extracted and an extracting rule
corresponding to the text to be
extracted, wherein the extracting rule includes an extracting field.
[0088] Specifically, the text to be extracted includes, but is not limited to,
such long texts having
fixed directory structures as fund information disclosure prospectuses and
fund contracts.
As should be noted here, the information extracting method provided by the
embodiments
of the present invention is further applicable to information extraction of
other long texts
with relatively standard structures and styles. The extracting rule includes
regular
statements of configuration files and self-defined rules, the self-defined
rules are mainly
used to configure such information as fields required to be extracted by the
user, and the
self-defined rules can be adjusted according to practical requirements of the
user, so as to
adapt to different information extracting requirements. The extracting rule is
embodied
in the mode of a combination of multiple rules, thus making it possible to
effectively
enhance the efficiency and precision of long text information extraction.
[0089] S2 ¨determining, based on a file directory of the text to be extracted,
a chapter location
of each piece of directory information of the file directory in the text to be
extracted, and
generating chapter information.
[0090] Specifically, some documents usually have relatively fixed template
structures, such as
the directory structure, etc. In the embodiments of the present invention, the
file directory
inherent in the text to be extracted is utilized to precisely position the
text to the levels of
chapter, paragraph and sentence through the directory hierarchy positioning
mode, and to
prepare for subsequent information extraction. While chapter positioning is
being
performed, the directory information can be used as an extracting field (the
directory
16
Date Recue/Date Received 2022-02-08
information is usually the title of each chapter) to automatically position
and extract the
chapter in which the field locates through the mode of regular expression, and
to generate
corresponding chapter information. The chapter information includes the title
and the
corresponding entire content of the chapter in the embodiments of the present
invention.
[0091] S3 ¨ partitioning the chapter information according to a preset rule,
and generating a
corresponding partition list.
[0092] Specifically, in order to enhance precision of information extraction,
after the chapter of
the text to be extracted has been positioned, it is further required to
further finely partition
the chapter information, by firstly partitioning the chapter information to
which each
chapter corresponds into paragraphs, thereafter sequentially partitioning the
paragraphs
each into sentences, and generating paragraph lists and sentence lists
respectively
according to the partitioning result for use by subsequent steps. The specific
partitioning
process can be inferred from the descriptions to the related steps in
Embodiment 1, while
no repetition is made in this context.
[0093] S4 ¨ generating key-value pair information corresponding to the text to
be extracted
according to the partition list and the extracting rule and storing the
information into a
database, wherein the key includes an extracting field, and the value includes
the partition
list and target information corresponding to the extracting field.
[0094] Specifically, information extraction is performed on the partition list
obtained in the
foregoing step in accordance with the extracting field and according to the
extracting rule
to obtain information required to be extracted, key-value pair information is
then
generated from the extracting field and the extracted information, and the key-
value pair
information is stored into a database.
[0095] As a preferred mode of execution in the embodiments of the present
invention, the
17
Date Recue/Date Received 2022-02-08
partition list includes paragraph lists and sentence lists, and the step of
partitioning the
chapter information according to a preset rule, and generating a corresponding
partition
list includes:
[0096] partitioning each piece of the chapter information into paragraphs
according to preset
paragraph features, and generating corresponding paragraph lists respectively;
and
[0097] partitioning each paragraph in each paragraph list into sentences
according to preset
sentence features, and generating corresponding sentence lists respectively.
[0098] Specifically, the processes of partitioning into paragraphs and
partitioning into sentences
can be inferred from the descriptions to the related steps in Embodiment 1,
while no
repetition is made in this context.
[0099] As a preferred mode of execution in the embodiments of the present
invention, when the
target information corresponding to the extracting field is long text
information, the step
of generating key-value pair information corresponding to the text to be
extracted
according to the partition list and the extracting rule and storing the
information into a
database includes:
[0100] determining a first paragraph or a first sentence in the partition list
in which the extracting
field locates, and determining a second paragraph adjacent to the first
paragraph or a
second sentence adjacent to the first sentence;
[0101] searching for the first paragraph and the second paragraph or the first
sentence and the
second sentence by use of a preset searching rule, and determining the target
information
corresponding to the extracting field; and
[0102] generating key-value pair information corresponding to the text to be
extracted according
to the extracting field and the target information and storing the information
into a
database.
[0103] Specifically, when the target information corresponding to the
extracting field is long text
information, such as in fund generalization information, partial values are
text descriptive
18
Date Recue/Date Received 2022-02-08
information, so such information may be one paragraph, several sentences, or
one
sentence, and the concept of adjacent sentence (or paragraph) can be
introduced here for
searching, namely to take the adjacent sentence or paragraph also in the range
of
consideration. For instance, when a certain paragraph or sentence to which the
extracting
field corresponds ends with a colon, usually the content following the colon
is the
information required to be extracted, at this time the paragraph or sentence
following the
colon is taken as the extracted target information.
[0104] As a preferred mode of execution in the embodiments of the present
invention, when the
target information corresponding to the extracting field is short text
information, the step
of generating key-value pair information corresponding to the text to be
extracted
according to the partition list and the extracting rule and storing the
information into a
database includes:
[0105] performing a target detection process on the sentences in the partition
list, and obtaining
the target information corresponding to the extracting field; and
[0106] generating key-value pair information corresponding to the text to be
extracted according
to the extracting field and the target information and storing the information
into a
database.
[0107] Specifically, when the target information corresponding to the
extracting field is short
text information, for instance, the information required to be extracted is a
date, while
such information is usually intermingled in a sentence, it is possible at this
time to employ
the mode of target detection to extract the relevant information contained in
the sentence.
[0108] As a preferred mode of execution in the embodiments of the present
invention, when the
extracting field is status change, the step of generating key-value pair
information
corresponding to the text to be extracted according to the partition list and
the extracting
rule and storing the information into a database includes:
[0109] obtaining business status change information in the sentence lists
according to the
19
Date Recue/Date Received 2022-02-08
extracting rule, and generating key-value pair information corresponding to
the text to be
extracted according to the business status change information and the
extracting field and
storing the information into a database.
[0110] Specifically, the status change information extracting process can be
inferred from the
fund status change information extracting process in Embodiment 1, while no
repetition
is made in this context.
[0111] As a preferred mode of execution in the embodiments of the present
invention, prior to
storing the key-value pair information into a database, the method further
comprises:
[0112] denoising the key-value pair information, and storing the denoised key-
value pair
information in the database.
[0113] Specifically, in order to enhance precision of information extraction,
the key-value pair
information generated in the foregoing step is further processed by being
filtered in the
embodiments of the present invention, during specific implementation, it is
possible to
denoise the key-value pair information to remove redundant or unreasonable
results.
[0114] As a preferred mode of execution in the embodiments of the present
invention, the
extracting rule includes a regular expression.
[0115] Fig. 4 is a view schematically illustrating the structure of a text
information extracting
device according to an exemplary embodiment. With reference to Fig. 4, the
device
comprises:
[0116] a data obtaining module, for obtaining a text to be extracted and an
extracting rule
corresponding to the text to be extracted, wherein the extracting rule
includes an
extracting field;
[0117] a chapter obtaining module, for determining, based on a file directory
of the text to be
extracted, a chapter location of each piece of directory information of the
file directory in
Date Recue/Date Received 2022-02-08
the text to be extracted, and generating chapter information;
[0118] a data partitioning module, for partitioning the chapter information
according to a preset
rule, and generating a corresponding partition list; and
[0119] an information generating module, for generating key-value pair
information
corresponding to the text to be extracted according to the partition list and
the extracting
rule and storing the information into a database, wherein the key includes an
extracting
field, and the value includes the partition list and information corresponding
to the
extracting field.
[0120] As a preferred mode of execution in the embodiments of the present
invention, the data
partitioning module includes:
[0121] a paragraph partitioning unit, for partitioning each piece of the
chapter information into
paragraphs according to preset paragraph features, and generating
corresponding
paragraph lists respectively; and
[0122] a sentence partitioning unit, for partitioning each paragraph in each
paragraph list into
sentences according to preset sentence features, and generating corresponding
sentence
lists respectively.
[0123] As a preferred mode of execution in the embodiments of the present
invention, the
information generating module is specifically employed for:
[0124] determining a first paragraph or a first sentence in the partition list
in which the extracting
field locates, and determining a second paragraph adjacent to the first
paragraph or a
second sentence adjacent to the first sentence;
[0125] searching for the first paragraph and the second paragraph or the first
sentence and the
second sentence by use of a preset searching rule, and determining the target
information
corresponding to the extracting field; and
[0126] generating key-value pair information corresponding to the text to be
extracted according
to the extracting field and the target information and storing the information
into a
database.
21
Date Recue/Date Received 2022-02-08
[0127] As a preferred mode of execution in the embodiments of the present
invention, the
information generating module is further employed for:
[0128] performing a target detection process on the sentences in the partition
list, and obtaining
the target information corresponding to the extracting field; and
[0129] generating key-value pair information corresponding to the text to be
extracted according
to the extracting field and the target information and storing the information
into a
database.
[0130] As a preferred mode of execution in the embodiments of the present
invention, the
information generating module is further employed for:
[0131] obtaining business status change information in the sentence lists
according to the
extracting rule, and generating key-value pair information corresponding to
the text to be
extracted according to the business status change information and the
extracting field and
storing the information into a database.
[0132] As a preferred mode of execution in the embodiments of the present
invention, the device
further comprises:
[0133] a denoising module, for denoising the key-value pair information, and
storing the
denoised key-value pair information in the database.
[0134] As a preferred mode of execution in the embodiments of the present
invention, the
extracting rule includes a regular expression.
[0135] Fig. 5 is a view schematically illustrating the internal structure of a
computer equipment
according to an exemplary embodiment. With reference to Fig. 5, the computer
equipment
comprises a processor, a memory and a network interface connected to each
other via a
system bus. The processor of the computer equipment is employed to provide
computing
and controlling capabilities. The memory of the computer equipment includes a
22
Date Recue/Date Received 2022-02-08
nonvolatile storage medium, and an internal memory. The nonvolatile storage
medium
stores therein an operating system, a computer program and a database. The
internal
memory provides environment for the running of the operating system and the
computer
program in the nonvolatile storage medium. The network interface of the
computer
equipment is employed to connect to an external terminal via network for
communication.
The computer program realizes a method of optimizing an execution plan when it
is
executed by a processor.
[0136] As understandable to persons skilled in the art, the structure
illustrated in Fig. 5 is merely
a block diagram of partial structure relevant to the solution of the present
invention, and
does not constitute any restriction to the computer equipment on which the
solution of
the present invention is applied, as the specific computer equipment may
comprise
component parts that are more than or less than those illustrated in Fig. 5,
or may combine
certain component parts, or may have different layout of component parts.
[0137] As a preferred mode of execution in the embodiments of the present
invention, the
computer equipment comprises a memory, a processor and a computer program
stored
on the memory and operable on the processor, and the following steps are
realized when
the processor executes the computer program:
[0138] obtaining a text to be extracted and an extracting rule corresponding
to the text to be
extracted, wherein the extracting rule includes an extracting field;
[0139] determining, based on a file directory of the text to be extracted, a
chapter location of
each piece of directory information of the file directory in the text to be
extracted, and
generating chapter information;
[0140] partitioning the chapter information according to a preset rule, and
generating a
corresponding partition list; and
[0141] generating key-value pair information corresponding to the text to be
extracted according
to the partition list and the extracting rule and storing the information into
a database,
wherein the key includes an extracting field, and the value includes the
partition list and
23
Date Recue/Date Received 2022-02-08
target information corresponding to the extracting field.
[0142] As a preferred mode of execution in the embodiments of the present
invention, when the
processor executes the computer program, the following steps are further
realized:
[0143] partitioning each piece of the chapter information into paragraphs
according to preset
paragraph features, and generating corresponding paragraph lists respectively;
and
[0144] partitioning each paragraph in each paragraph list into sentences
according to preset
sentence features, and generating corresponding sentence lists respectively.
[0145] As a preferred mode of execution in the embodiments of the present
invention, when the
processor executes the computer program, the following steps are further
realized:
[0146] determining a first paragraph or a first sentence in the partition list
in which the extracting
field locates, and determining a second paragraph adjacent to the first
paragraph or a
second sentence adjacent to the first sentence;
[0147] searching for the first paragraph and the second paragraph or the first
sentence and the
second sentence by use of a preset searching rule, and determining the target
information
corresponding to the extracting field; and
[0148] generating key-value pair information corresponding to the text to be
extracted according
to the extracting field and the target information and storing the information
into a
database.
[0149] As a preferred mode of execution in the embodiments of the present
invention, when the
processor executes the computer program, the following steps are further
realized:
[0150] performing a target detection process on the sentences in the partition
list, and obtaining
the target information corresponding to the extracting field; and
[0151] generating key-value pair information corresponding to the text to be
extracted according
to the extracting field and the target information and storing the information
into a
database.
24
Date Recue/Date Received 2022-02-08
[0152] As a preferred mode of execution in the embodiments of the present
invention, when the
processor executes the computer program, the following steps are further
realized:
[0153] obtaining business status change information in the sentence lists
according to the
extracting rule, and generating key-value pair information corresponding to
the text to be
extracted according to the business status change information and the
extracting field and
storing the information into a database.
[0154] As a preferred mode of execution in the embodiments of the present
invention, when the
processor executes the computer program, the following steps are further
realized:
[0155] denoising the key-value pair information, and storing the denoised key-
value pair
information in the database.
[0156] As a preferred mode of execution in the embodiments of the present
invention, the
extracting rule includes a regular expression.
[0157] In the embodiments of the present invention, there is further provided
a computer-
readable storage medium storing a computer program thereon, and the following
steps
are realized when the computer program is executed by a processor:
[0158] obtaining a text to be extracted and an extracting rule corresponding
to the text to be
extracted, wherein the extracting rule includes an extracting field;
[0159] determining, based on a file directory of the text to be extracted, a
chapter location of
each piece of directory information of the file directory in the text to be
extracted, and
generating chapter information;
[0160] partitioning the chapter information according to a preset rule, and
generating a
corresponding partition list; and
[0161] generating key-value pair information corresponding to the text to be
extracted according
to the partition list and the extracting rule and storing the information into
a database,
wherein the key includes an extracting field, and the value includes the
partition list and
target information corresponding to the extracting field.
Date Recue/Date Received 2022-02-08
[0162] As a preferred mode of execution in the embodiments of the present
invention, when the
computer program is executed by a processor, the following steps are further
realized:
[0163] obtaining a text to be extracted and an extracting rule corresponding
to the text to be
extracted, wherein the extracting rule includes an extracting field;
[0164] determining, based on a file directory of the text to be extracted, a
chapter location of
each piece of directory information of the file directory in the text to be
extracted, and
generating chapter information;
[0165] partitioning the chapter information according to a preset rule, and
generating a
corresponding partition list; and
[0166] generating key-value pair information corresponding to the text to be
extracted according
to the partition list and the extracting rule and storing the information into
a database,
wherein the key includes an extracting field, and the value includes the
partition list and
target information corresponding to the extracting field.
[0167] As a preferred mode of execution in the embodiments of the present
invention, when the
computer program is executed by a processor, the following steps are further
realized:
[0168] determining a first paragraph or a first sentence in the partition list
in which the extracting
field locates, and determining a second paragraph adjacent to the first
paragraph or a
second sentence adjacent to the first sentence;
[0169] searching for the first paragraph and the second paragraph or the first
sentence and the
second sentence by use of a preset searching rule, and determining the target
information
corresponding to the extracting field; and
[0170] generating key-value pair information corresponding to the text to be
extracted according
to the extracting field and the target information and storing the information
into a
database.
[0171] As a preferred mode of execution in the embodiments of the present
invention, when the
computer program is executed by a processor, the following steps are further
realized:
26
Date Recue/Date Received 2022-02-08
[0172] performing a target detection process on the sentences in the partition
list, and obtaining
the target information corresponding to the extracting field; and
[0173] generating key-value pair information corresponding to the text to be
extracted according
to the extracting field and the target information and storing the information
into a
database.
[0174] As a preferred mode of execution in the embodiments of the present
invention, when the
computer program is executed by a processor, the following steps are further
realized:
[0175] obtaining business status change information in the sentence lists
according to the
extracting rule, and generating key-value pair information corresponding to
the text to be
extracted according to the business status change information and the
extracting field and
storing the information into a database.
[0176] As a preferred mode of execution in the embodiments of the present
invention, when the
computer program is executed by a processor, the following steps are further
realized:
[0177] denoising the key-value pair information, and storing the denoised key-
value pair
information in the database.
[0178] As a preferred mode of execution in the embodiments of the present
invention, the
extracting rule includes a regular expression.
[0179] In short, the technical solutions provided by the embodiments of the
present invention
bring about the following advantageous effects.
[0180] In the text information extracting method, and corresponding device,
computer
equipment and storage medium provided by the embodiments of the present
invention,
by obtaining a text to be extracted and an extracting rule corresponding to
the text to be
extracted, wherein the extracting rule includes an extracting field,
determining, based on
a file directory of the text to be extracted, a chapter location of each piece
of directory
27
Date Recue/Date Received 2022-02-08
information of the file directory in the text to be extracted, and generating
chapter
information, partitioning the chapter information according to a preset rule,
and
generating a corresponding partition list, and generating key-value pair
information
corresponding to the text to be extracted according to the partition list and
the extracting
rule and storing the information into a database, wherein the key includes an
extracting
field, and the value includes the partition list and target information
corresponding to the
extracting field, on the one hand, the present invention enhances the
efficiency of text
extraction, avoids such problems as missing from and error in information
extraction, and
enhances the precision of text extraction, on the other hand, by dividing the
long text, the
present invention avoids the circumstance of infinite backtracking that might
be
encountered in regular matching, enhances fault tolerance rate of codes, and
reduces time
consumption in the overall operation.
[0181] In the text information extracting method, and corresponding device,
computer
equipment and storage medium provided by the embodiments of the present
invention,
by partitioning each piece of the chapter information into paragraphs
according to preset
paragraph features, and generating corresponding paragraph lists respectively,
and
partitioning each paragraph in each paragraph list into sentences according to
preset
sentence features, and generating corresponding sentence lists respectively,
the text is
precisely positioned to the levels of chapter, paragraph and sentence through
the directory
hierarchy positioning mode, so that to effect precise positioning and to
extract relevant
information from the text to be extracted.
[0182] In the text information extracting method, and corresponding device,
computer
equipment and storage medium provided by the embodiments of the present
invention,
by denoising the key-value pair information and storing the denoised key-value
pair
information in the database, the key-value pair information extracted from the
text is
further screened and filtered, whereby the precision in long text information
extraction is
effectively enhanced.
28
Date Recue/Date Received 2022-02-08
[0183] As should be noted, when the text information extracting device
provided by the
aforementioned embodiment triggers an extracting business, it is merely
exemplarily
described with its division into the aforementioned various functional
modules, whereas
in actual application it is possible to base on requirements to assign the
aforementioned
functions to different functional modules for completion, that is to say, the
internal
structure of the device is divided into different functional modules to
complete the entire
or partial functions as described above. In addition, the text information
extracting device
provided by the aforementioned embodiment pertains to the same inventive
conception
as the text information extracting method, in other words, the device is based
on the text
information extracting method ¨ see the method embodiment for its specific
implementation process, while no repetition will be made in this context.
[0184] As comprehensible to persons ordinarily skilled in the art, the entire
or partial steps in the
aforementioned embodiments can be completed via hardware, or via a program
instructing relevant hardware, the program can be stored in a computer-
readable storage
medium, and the storage medium can be a read-only memory, a magnetic disk or
an
optical disk, etc.
[0185] The foregoing embodiments are merely preferred embodiments of the
present invention,
and they are not to be construed as restrictive to the present invention. Any
amendment,
equivalent substitution, and improvement makeable within the spirit and
principle of the
present invention shall all fall within the protection scope of the present
invention.
29
Date Recue/Date Received 2022-02-08
