CN114579712B - Text attribute extraction and matching method based on dynamic model - Google Patents

Text attribute extraction and matching method based on dynamic model Download PDF

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CN114579712B
CN114579712B CN202210478783.9A CN202210478783A CN114579712B CN 114579712 B CN114579712 B CN 114579712B CN 202210478783 A CN202210478783 A CN 202210478783A CN 114579712 B CN114579712 B CN 114579712B
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attribute name
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extraction
attribute
text
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CN114579712A (en
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杨波
王小莉
秦克良
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Zhongke Yuchen Technology Co Ltd
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    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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    • G06F16/3331—Query processing
    • G06F16/334—Query execution
    • G06F16/3344—Query execution using natural language analysis
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
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Abstract

The invention provides a text attribute extraction and matching system based on a dynamic model, which can automatically extract and match attribute names in text data and improve the extraction and matching speed and accuracy.

Description

Text attribute extraction and matching method based on dynamic model
Technical Field
The application relates to the field of text recognition, in particular to a text attribute extraction and matching method based on a dynamic model.
Background
Generally, corresponding specifications are provided for materials in life so as to know the characteristics and functions of the materials. At present, the attributes of the materials are manually obtained from the specification, so as to obtain the attribute information of the corresponding materials, for example, the material name, the material components and other attribute information. However, for a large number of specifications, the manual acquisition mode has the defects of low efficiency, high labor intensity and the like.
Disclosure of Invention
In view of the above technical problems, an embodiment of the present invention provides a text attribute extraction and matching system based on a dynamic model, which is used to solve at least one of the above technical problems.
The embodiment of the invention adopts the technical scheme that:
the embodiment of the invention provides a text attribute extraction matching system based on a dynamic model, which comprises: a processor, a memory and a database connected in communication, the memory having stored therein text data of N types of target objects, the ith row of the database comprising (C)i，A0 i，Di，R0 i），CiIs ID of the i-th class target object, A0 iIs CiCorresponding text data TiCurrent property name set of A0 iIs Null; di=（Di1，Di2，…，Dimi），DijIs TiCorresponding set of data elements DiThe jth data element in (1); r0 iIs a and A0 iCorresponding set of matching results, R0 i∈Di，R0 iIs Null;
text data T for any one target object iiSaid processor being adapted to execute a computer program to perform the steps of:
s10, based on TiObtaining the corresponding current attribute name set A from the database0 i(ii) a If A is0 iNot Null, perform S20, otherwise, perform S30;
s20, based on A0 iExtraction of TiAttribute name in (1) to obtain TiProperty name set A ofi；
S30, extracting T based on the set extraction ruleiTo obtain TiProperty name set A ofi；
S40, based on TiTo A, aiCorrecting to obtain a corrected attribute name set Ac i=（Ac i1，Ac i2，…，Ac ini），Ac irIs Ac iR is 1 to ni, and ni is Ac iThe number of attribute names in (1); using ac iUpdate A0 i；
S50, if Ac ir∈A0 iThen A is added0 iNeutralizing with Ac irThe data elements corresponding to the same attribute name are used as Ac irThe matching result of (2); otherwise, go to S60;
s60, obtaining Dc ir=max（Dc ir1，Dc ir2，…，Dc irmi），Dc irsIs Ac irAnd text data TiCorresponding set of data elements DiData element D in (1)isS is 1 to mi;
s70, if Dc irIf > D, then Dc irCorresponding data element as Ac irThe matching result of (1); d is a set threshold;
s80, obtaining A based on S60-S70c iMatching result set R ofi(ii) a To R isiCorrecting to obtain a corrected matching result set Rc iAnd use of Rc iUpdating R0 i。
The embodiment of the invention provides a text attribute extraction matching system based on a dynamic model, which optimizes an attribute name set extracted last time by using a currently extracted attribute name set to serve as a basis for extracting an attribute name next time. Because the attribute name sets stored in the database are all the attribute name sets manually corrected last time, the subsequent automatic extraction of the attribute names can be more accurate, and all the attribute names in the text data can be automatically extracted as accurately as possible. In addition, the matching result of each time is corrected, and the corrected matching result is used as the matching basis of the attribute name of the next time, so that the automatic matching result can be continuously optimized, the automatic matching result is more accurate, and the matching result of the extracted attribute name can be automatically found from the set attribute name set as accurate as possible.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a flowchart of a method implemented when a computer program is executed by the system for extracting and matching text attributes based on dynamic models according to the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The embodiment of the invention provides a text attribute extraction matching system based on a dynamic model, which comprises: a processor, a memory, and a database communicatively coupled.
Wherein the memory stores text data of N types of target objects, and the ith row of the database comprises (C)i，A0 i，Di，R0 i），CiIs ID of the i-th class target object, A0 iIs CiCorresponding text data TiCurrent property name set of Ai=（Ai1，Ai2，…，Aini），A0 ipIs AiP-th attribute name in (1), p is 1 to ni, and ni is AiNumber of attribute names in (1); a. the0 iIs Null. Di=（Di1，Di2，…，Dimi），DijIs TiCorresponding set of data elements DiThe jth data element in (1); r0 iIs a and A0 iCorresponding set of matching results, R0 i∈Di，R0 iInitial value of (2)Is Null.
In the embodiment of the present invention, the target object may be a material, for example, a product such as a medicine, a food, a device, and the like. The text data may be text recognized from a description file, such as a specification, corresponding to the target object. Those skilled in the art will appreciate that the text recognized from the description file corresponding to the target object may be recognized in any conventional manner, such as ocr text recognition software.
Further, in the embodiment of the present invention, the description file of the target object for recognition may be obtained by photographing with the image pickup device.
In the embodiment of the present invention, the attribute name may be a name describing characteristics of the material, such as specification, content, composition, and the like.
In the embodiment of the present invention, the data element may be a primary attribute name for the target object, that is, primary information of the target object can be known through the data element.
Further, in the embodiment of the present invention, the text data T for any one target object iiThe processor is configured to execute a computer program to implement the following steps (as shown in fig. 1):
s10, based on TiObtaining the corresponding current attribute name set A from the database0 i(ii) a If A is0 iNot Null, S20 is performed, otherwise, S30 is performed.
Otherwise, the description is that the text data T is processed for the first timeiAnd T is not stored in the databaseiHistory data of (i.e. A)0 iIs Null.
S20, based on A0 iExtraction of TiAttribute name in (1) to obtain TiProperty name set A ofi。
If A is0 iNot Null, meaning that the text data T is not processed for the first timeiT is stored in the databaseiHistory data of (A)0 iIs the last extracted attribute name set, therefore, utilizes A0 iExtraction of TiAttribute name in (1) to obtain TiProperty name set A ofiCan improveAnd (4) attribute extraction accuracy.
S30, extracting T based on the set extraction ruleiGet TiProperty name set A ofi。
In an embodiment of the present invention, the ith row of the database further comprises TiCorresponding first identifier set M1iAnd a second set of identifiers M2i. First set of identifiers M1iIs TiThe identifier set inherent in the method can comprise at least one identifier, and the identifier can be, for example, ")"< >"," [ sic ], and the like. Second set of identifiers M2iCan be a custom set of identifiers and can include at least one identifier.
Further, in S30, if M1iNot Null, based on M1iExtraction of TiThe attribute name in (2). Specifically, if M1iIncluding ui identifiers, i.e. M1i=（M1i1，M1i2，…，M1iui) Then T can be extracted as followsiProperty name in (2):
s301, go through M1iUsing either M1ivFrom TiExtracting corresponding attribute names; v is from 1 to ui;
s302, based on S301, generating basis M1iExtracted TiThe attribute name of (2).
The information extracted based on each identifier may be a key-value pair, i.e., including a key and a corresponding value, in the present invention, the key is an attribute name. It is known to those skilled in the art that extracting attribute names in text data based on identifiers may be an existing method.
Further, in S30, if M1iIs Null and M2iNot Null, then M2iExtraction of TiProperty name in (2). Based on M2iExtraction of TiThe attribute name in (2) can be compared with the attribute name based on M1iExtraction of TiIn a similar manner.
Further, in one embodiment of the present invention, in S30, if M1 is satisfiediIs Null and M2iIs Null, then T can be extracted based on NulliInThe attribute name, the resulting attribute name is also Null.
Further, in one embodiment of the present invention, in S30, if M1 is satisfiediIs Null and M2iFor Null, T may be extracted based on a randomly generated identifieriThe obtained corresponding attribute name.
S40, based on TiTo A, aiCorrecting to obtain a corrected attribute name set Ac i=（Ac i1，Ac i2，…，Ac ini），Ac irIs Ac iR is 1 to ni, and ni is Ac iThe number of attribute names in (1); using ac iUpdate A0 i。
In the embodiment of the invention, A can be manually alignediAnd (6) correcting. Specifically, the operator may manually search from TiFinding out all attribute names to form a contrast attribute name set, and then adding AiComparing with the formed comparison attribute name set to find out the missing, error or redundant attribute names to AiCorrecting to obtain a corrected attribute name set Ac i。
In the present embodiment, use is made of Ac iUpdate A0 iCan be a0 iIs replaced by Ac iThat is, the attribute name set extracted last time is optimized by using the attribute name set extracted currently, so as to be used as the basis for extracting the attribute name next time. Because the attribute name sets stored in the database are all the attribute name sets manually corrected last time, the subsequent automatic extraction of the attribute names can be more accurate, and all the attribute names in the text data can be automatically extracted as accurately as possible.
S50, if Ac ir∈A0 iThen A is added0 iNeutralizing with Ac irThe data elements corresponding to the same attribute name are used as Ac irThe matching result of (1); otherwise, S60 is executed.
In an embodiment of the invention, the data element corresponding to each text data is fixed, i.e. DiIs stationary.
In another embodiment of the present invention, the data element corresponding to each text data may be dynamically changed, for example, updated with each type of material, in this case, due to DiReason for update, there will be Ac ir∈A0 i，A0 iNeutral with Ac irThe data elements corresponding to the same attribute name are not in DiIn S50, therefore, if A is in S500 iNeutral with Ac irData elements corresponding to the same attribute name do not belong to DiThen S60 is executed.
The technical effect of S50 is that if Ac ir∈A0 iAnd A is0 iNeutralizing with Ac irData elements corresponding to the same attribute name are in DiIn (1), then A is0 iNeutralizing with Ac irThe data elements corresponding to the same attribute name are used as Ac irThe matching result of the time can be directly obtained based on the last matching result, and the matching speed and the matching accuracy can be improved.
S60, obtaining Dc ir=max（Dc ir1，Dc ir2，…，Dc irmi），Dc irsIs Ac irAnd text data TiCorresponding set of data elements DiData element D in (1)isS is 1 to mi.
In particular, in this step, for Ac iAny attribute name A in (1)c irFirst, and D can be acquired separatelyiThe similarity between each data element in (1), i.e. D is obtained separatelyc ir1，Dc ir2，…，Dc irmi(ii) a Then from Dc ir1，Dc ir2，…，Dc irmiSelecting the largest one as Dc ir. Those skilled in the art will appreciate that existing similarity calculation methods, such as hanlp, may be used to obtain the similarity, e.g., euclidean distance, cosine distance, mahalanobis distance, etc.
S70, if Dc irIf > D, then Dc irCorresponding data element as Ac irThe matching result of (2); d is a set threshold.
In embodiments of the present invention, D can be an empirical value, such as 90% to 99%, preferably, can be 95% to 99%, and more preferably, can be 99%.
S80, obtaining A based on S60-S70c iIs matched with the result set Ri(ii) a To RiCorrecting to obtain a corrected matching result set Rc iAnd use of Rc iUpdating R0 i。
In embodiments of the present invention, R may be empirically pairediAnd (6) correcting.
In the present embodiment, R is usedc iUpdating R0 iCan be prepared by reacting R0 iIs replaced by Rc i。
In the embodiment of the invention, because the matching result of each time is corrected and the corrected matching result is used as the matching basis of the attribute name of the next time, the automatic matching result can be continuously optimized, so that the automatic matching result is more accurate, and the matching result of the extracted attribute name can be automatically found from the set attribute name set as accurate as possible.
Further, in the embodiment of the present invention, before S40, the data element further includes:
s32, for Ac iAnd performing visual presentation.
In visual presentation, A may be presented sequentially, e.g., from top to bottomc iFor example, the content displayed in each line may be: a name; XX, and the like.
Further, in the embodiment of the present invention, the method further includes:
s90, to Rc iAnd performing visual presentation.
In the pair Rc iWhen performing visual presentation, R can be presented sequentially in order, for example, from top to bottomc iAnd the corresponding attribute name.
Although some specific embodiments of the present application have been described in detail by way of illustration, it should be understood by those skilled in the art that the above illustration is only for purposes of illustration and is not intended to limit the scope of the present application. It will also be appreciated by those skilled in the art that various modifications may be made to the embodiments without departing from the scope and spirit of the present application. The scope of the disclosure of the present application is defined by the appended claims.

Claims (9)

1. A text attribute extraction matching system based on a dynamic model is characterized by comprising: a processor, a memory and a database connected in communication, wherein the memory stores text data of N types of target objects, and the ith line of the database comprises (C)i，A0 i，Di，R0 i），CiIs ID of the i-th class target object, A0 iIs CiCorresponding text data TiCurrent attribute name set of A0 iIs Null; di=（Di1，Di2，…，Dimi），DijIs TiCorresponding set of data elements DiThe jth data element in (1); r0 iIs a and A0 iCorresponding set of matching results, R0 i∈Di，R0 iIs Null;
text data T for any target object iiSaid processor being adapted to execute a computer program to perform the steps of:
s10, based on TiObtaining the corresponding current attribute name set A from the database0 i(ii) a If A is0 iNot Null, S20 is executed, otherwise, execution is performedS30；
S20, based on A0 iExtraction of TiAttribute name in (1) to obtain TiProperty name set A ofi；
S30, extracting T based on the set extraction ruleiTo obtain TiProperty name set A ofi；
S40, based on TiTo A, aiCorrecting to obtain a corrected attribute name set Ac i=（Ac i1，Ac i2，…，Ac ini），Ac irIs Ac iR is 1 to ni, and ni is Ac iNumber of attribute names in (1); using Ac iUpdate A0 i；
S50, if Ac ir∈A0 iThen A is added0 iNeutralizing with Ac irThe data elements corresponding to the same attribute name are used as Ac irThe matching result of (1); otherwise, go to S60;
s60, obtaining Dc ir=max（Dc ir1，Dc ir2，…，Dc irmi），Dc irsIs Ac irAnd text data TiCorresponding set of data elements DiData element D in (1)isS is 1 to mi;
s70, if Dc irIf > D, then D isc irCorresponding data element as Ac irThe matching result of (1); d is a set threshold;
s80, obtaining A based on S60-S70c iIs matched with the result set Ri(ii) a To RiCorrecting to obtain a corrected matching result set Rc iAnd use of Rc iUpdating R0 i。
2. The system of claim 1, wherein the text data is text identified from a description file corresponding to the target object.
3. The system of claim 1, wherein row i of the database further comprises TiCorresponding first identifier set M1iAnd a second set of identifiers M2i。
4. The system of claim 3, wherein in S30, if M1iNot Null, then M1iExtraction of TiThe attribute name in (2).
5. The system of claim 3, wherein in S30, if M1iIs Null and M2iNot Null, based on M2iExtraction of TiProperty name in (2).
6. The system according to claim 1, wherein in S50, if A0 iNeutral with Ac irData elements corresponding to the same attribute name do not belong to DiThen S60 is executed.
7. The system of claim 1, further comprising, prior to S40:
s32, for Ac iAnd performing visual presentation.
8. The system of claim 1, further comprising:
s90, to Rc iAnd performing visual presentation.
9. The system of any one of claims 1 to 8, wherein the target object is a material.
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