KR20210039908A - Method for calculating for weight score of word based reference information of patent document - Google Patents

Abstract

Provided is a method of calculating an importance degree score of a word. The method of calculating an importance degree score of a word includes: a step wherein a server obtains a word which is a calculation target of an importance degree score from a target patent document; a step wherein the server calculates at least one of a first detailed importance degree of the word for all patent documents, a second detailed importance degree of the word for patent classification information corresponding to technological field information of the target patent document, and a third detailed importance degree of a search patent document including the word among all the patent documents; and a step wherein the server calculates the importance degree score of the word based on at least one of the first, second and third detailed importance degrees. Therefore, the present invention is capable of accurately calculating an importance degree score by subdividing the same.

Description

[Method for calculating for weight score of word based reference information of patent document}

The present invention relates to a method, an apparatus, and a computer program for calculating the importance score of a word.

Recently, a vast amount of information has been introduced mainly through the Internet, and as the number of holders of portable devices such as smart phones increases, a technology for acquiring only necessary information among a large amount of information has been attracting attention. To this end, a technology for extracting only key words from words of various electronic documents is being studied.

Conventional word extraction techniques include a method of extracting a word including a core content and a method of reconstructing a document by changing the structure or vocabulary of the document. This conventional word extraction technique has several disadvantages in extracting words.

For example, the conventional word extraction technology simply extracts words that are commonly handled from among several searched documents, or extracts only words that are frequently used in the corresponding document. Accordingly, the conventional word extraction technology has a problem in that even words that are frequently used in a specific field according to the content of a document but do not have a large meaning are extracted.

Accordingly, there is a need for a word extraction technology capable of extracting words including major core contents from a document without extracting words of low importance in terms of meaning even though they are frequently repeated in a document.

Unexamined Patent Publication No. 10-2017-0142526, 2017.12.28

An object to be solved by the present invention is to provide a method, apparatus, and computer program for calculating the importance score of words capable of calculating the importance score of words included in a target patent document.

The problems to be solved by the present invention are not limited to the problems mentioned above, and other problems that are not mentioned will be clearly understood by those skilled in the art from the following description.

A method for calculating an importance score of a word according to an aspect of the present invention for solving the above-described problem includes the steps of: obtaining, by a server, a word for which the importance score is calculated from a target patent document; The server includes the first detailed importance of the word in the entire patent document, the second detailed importance of the word in the patent classification information corresponding to the technical field information of the target patent document, and the word in the entire patent document. Calculating one or more detailed importance degrees of the third detailed importance of the searched patent document; And calculating, by the server, the importance score of the word based on at least one of the first detailed importance, the second detailed importance, and the third detailed importance.

Preferably, the calculating of the detailed importance of the word includes a first occurrence ratio of the number of occurrences of the word in the entire patent document to the total number of words in the entire patent document and the total number of sentences in the entire patent document. And calculating the first detailed importance based on a second occurrence ratio of the number of sentences in which the word appears among the sentences of the patent document.

Preferably, calculating the first detailed importance may include calculating the first detailed importance using the following equation.

<Equation>

Here, W ₁ is the first detailed importance, wpw is the number of occurrences of the word in the entire patent document, WPW is the total number of words in the entire patent document, and wps is the number of sentences in the entire patent document. Is the number of sentences in which the word appears, the WPS is the total number of sentences in the entire patent document, and a1 is an adjustment constant of the second appearance rate.

Preferably, the step of calculating the detailed importance of the word includes a third occurrence ratio of the number of occurrences of the word in the patent classification information to the total number of words in the patent classification information and the total number of sentences in the entire patent document. And calculating the second detailed importance based on a fourth occurrence ratio of the number of sentences in which the word appears in the sentences of the patent document.

Preferably, calculating the second detailed importance may include calculating the second detailed importance using the following equation.

<Equation>

Here, W ₂ is the second detailed importance, ipcw is the number of occurrences of the word in the patent classification information, IPCW is the total number of words in the patent classification information, and ipcs is the number of sentences in the entire patent document. Is the number of sentences in which the word appears, the IPCS is the total number of sentences in the entire patent document, and a2 is an adjustment constant of the fourth appearance rate.

Preferably, the step of calculating the detailed importance of the word includes calculating an influence value of each search patent document based on reference information of each search patent document, and using the influence value to determine the third detail of the search patent document. It may include the step of calculating the importance.

Preferably, calculating the importance score of the word may include calculating the importance score by summing a plurality of the first detailed importance, the second detailed importance, and the third detailed importance.

Preferably, the step of acquiring a word to be calculated for the importance score may include excluding a word set as a stop word among words included in the target patent document from a word to be calculated for the importance score.

According to an aspect of the present invention for solving the above-described problem, an apparatus for calculating the importance score of a word includes: a memory for storing at least one instruction; And a processor that executes the one or more instructions stored in the memory.

Preferably, the processor may perform a method of calculating the importance score of the word by executing the one or more instructions.

The computer program for calculating the importance score of a word according to an aspect of the present invention for solving the above-described problem is combined with a computer that is hardware, and can be stored in a computer-readable recording medium to perform a method of calculating the importance score of the word. have

In the present invention, the importance score of the word is calculated by calculating the detailed importance of a specific word in each of the entire patent document, patent classification information, and search patent document, thereby subdividing the importance score and accurately calculating the importance score.

The effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the following description.

1 is an exemplary diagram for describing a system according to an embodiment of the present invention.
2 is a flowchart illustrating a method of acquiring a word to be calculated for an importance score from a target patent document according to an embodiment of the present invention.
3 is a flowchart illustrating a method of calculating a first detailed importance of a word according to an embodiment of the present invention.
4 is a flowchart illustrating a method of calculating a second detailed importance of a word according to an embodiment of the present invention.
5 is a flowchart illustrating a method of calculating a third detailed importance of a word according to an embodiment of the present invention.
6 is a flowchart illustrating a method of calculating an importance score of a word according to an embodiment of the present invention.
7 is a block diagram of an apparatus for calculating a word importance score according to an embodiment of the present invention.

Advantages and features of the present invention, and a method of achieving them will become apparent with reference to the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in a variety of different forms. It is provided to fully inform the skilled person of the scope of the present invention, and the present invention is only defined by the scope of the claims.

The terms used in the present specification are for describing exemplary embodiments and are not intended to limit the present invention. In this specification, the singular form also includes the plural form unless specifically stated in the phrase. As used herein, “comprises” and/or “comprising” do not exclude the presence or addition of one or more other elements other than the mentioned elements. Throughout the specification, the same reference numerals refer to the same elements, and "and/or" includes each and all combinations of one or more of the mentioned elements. Although "first", "second", and the like are used to describe various elements, it goes without saying that these elements are not limited by these terms. These terms are only used to distinguish one component from another component. Therefore, it goes without saying that the first component mentioned below may be the second component within the technical idea of the present invention.

Unless otherwise defined, all terms (including technical and scientific terms) used in the present specification may be used with meanings that can be commonly understood by those of ordinary skill in the art to which the present invention belongs. In addition, terms defined in a commonly used dictionary are not interpreted ideally or excessively unless explicitly defined specifically.

The term "unit" or "module" used in the specification refers to a hardware component such as software, FPGA or ASIC, and the "unit" or "module" performs certain roles. However, "unit" or "module" is not meant to be limited to software or hardware. The “unit” or “module” may be configured to be in an addressable storage medium, or may be configured to reproduce one or more processors. Thus, as an example, "sub" or "module" refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, Includes procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays and variables. Components and functions provided within "sub" or "modules" may be combined into a smaller number of components and "sub" or "modules" or into additional components and "sub" or "modules". Can be further separated.

Spatially relative terms "below", "beneath", "lower", "above", "upper", etc. It can be used to easily describe the correlation between a component and other components. Spatially relative terms should be understood as terms including different directions of components during use or operation in addition to the directions shown in the drawings. For example, if a component shown in a drawing is turned over, a component described as "below" or "beneath" of another component will be placed "above" the other component. I can. Accordingly, the exemplary term “below” may include both directions below and above. Components may be oriented in other directions, and thus spatially relative terms may be interpreted according to the orientation.

In the present specification, a computer means all kinds of hardware devices including at least one processor, and may be understood as encompassing a software configuration operating in the corresponding hardware device according to embodiments. For example, the computer may be understood as including all of a smartphone, a tablet PC, a desktop, a laptop, and a user client and application running on each device, and is not limited thereto.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Each of the steps described herein is described as being performed by a computer, but the subject of each step is not limited thereto, and at least some of the steps may be performed by different devices according to embodiments.

1 is an exemplary diagram for describing a system according to an embodiment of the present invention.

The system for calculating the importance score of a word according to the present invention includes a server 10 and an electronic device 20.

The server 10 is a configuration for acquiring a target patent document, acquiring a word to be used for calculating the importance score from the acquired target patent document, and calculating the importance score of the word.

Specifically, the server 10 may receive a target patent document from the electronic device 20 or may obtain a target patent document from an external server.

In this specification, a patent document is a concept including a target patent document and a search patent document, and may be a document on the technical content submitted by an applicant to obtain a patent registration at a national patent office. However, the present disclosure is not limited thereto, and a patent document may be understood as a concept including various documents including technical contents such as a job invention for a patent application, a thesis, and the like. According to an embodiment, the target patent document may be at least one of a job invention and a thesis for a patent application, and the similar patent document may be at least one of a job invention, a thesis, and a patent application for a patent application. According to an embodiment, the search patent document may be a patent document searched from the server 10 including words among all patent documents.

The electronic device 20 is a configuration for providing a patent document to the server 10. The electronic device 200 according to the present invention may be implemented as a smart phone, but this is only an example, and a smart phone, a tablet personal computer, a mobile phone, a video phone, E-book reader, desktop PC, laptop PC, netbook computer, workstation, server, personal digital assistant (PDA), portable multimedia (PMP) player) or a wearable device.

2 is a flowchart illustrating a method of acquiring a word to be calculated for an importance score from a target patent document according to an embodiment of the present invention.

Referring to FIG. 2, in step S110, the server 10 may extract only the noun by performing a morpheme analysis on the target patent document. At this time, it should be noted that the type of morpheme analysis method is not limited as long as the server 10 extracts nouns from the target patent document.

Subsequently, in step S120, the server 10 may determine technical field information of the target patent document based on the extracted noun. In this case, the server 10 may compare the word data for each technical field information stored in advance with the extracted nouns, and as a result of the comparison, determine the technical field information including the most extracted nouns as the technical field information of the target patent document.

Thereafter, in step S130, the server 10 may exclude a word set as a stop word among words included in the target patent document from a word to be calculated for the importance score. Specifically, the server 10 reads the stop word data for each technology field information corresponding to the technology field information of the target patent document, and the words included in the read stop word data for each technology field information among the extracted words included in the target patent document Can be excluded from the words for which the importance score is to be calculated.

Here, the stop word is a word that is frequently used in the relevant technical field, but may mean a word that does not have a technical meaning. For example, in the field of IT technology, computers are frequently used, but because they do not have a technical meaning related to IT technology, they may be defined as stop words.

Accordingly, in step S140, the server 10 may obtain a word that is not a stopword among words extracted from the target patent document as a word to be calculated for the importance score.

3 is a flowchart illustrating a method of calculating a first detailed importance of a word according to an embodiment of the present invention.

Referring to FIG. 3, in step S210, the server 10 may count the total number of words in all patent documents and count the number of occurrences of words in all patent documents.

Thereafter, in step S220, the server 10 may calculate the number of appearances of words in the entire patent document compared to the total number of words in the entire patent document as the first appearance ratio.

Subsequently, in step S230, the server 10 may count the total number of sentences of the entire patent document, and count the number of sentences in which the word appears among the sentences of the entire patent document.

In step S240, the server 10 may calculate the total number of sentences of the entire patent document compared to the number of sentences in which words appear among the sentences of the entire patent document as the second appearance ratio.

To this end, the server 10 may search for a word from the entire patent document and search for a sentence including the word. In addition, the server 10 may analyze the sentence components of the entire patent document and count the total number of words and the total number of sentences.

Finally, in step S250, the server 10 may calculate the first detailed importance based on the first appearance rate and the second appearance rate.

In this case, the server 10 may calculate the first detailed importance by using Equation 1 below.

<Equation 1>

Here, W1 is the first detailed importance, wpw is the number of occurrences of words in the entire patent document, WPW is the total number of words in all patent documents, and wps is the number of sentences in which words appear in the entire patent document. , WPS is the total number of sentences in the entire patent document, and a1 is the adjustment constant of the second appearance rate.

Referring to Equation 1, the server 10 may calculate the first detailed importance as the number of occurrences of words in the entire patent document is larger and the number of sentences in which the word appears among sentences of the entire patent document is smaller.

That is, the server 10 may calculate the first detailed importance higher as words are used repeatedly in one sentence in the entire patent document.

On the other hand, the server 10 increases the second occurrence rate even if the number of sentences in which the word appears among the sentences of the entire patent document is small by increasing the adjustment constant of the second occurrence rate, and decreases the adjustment constant of the second appearance rate. Thus, even if the number of sentences in which the word appears among the sentences of the entire patent document is large, the second appearance rate can be reduced.

Note that in one embodiment, as long as the server 10 calculates the first detailed importance of words in the patent document, the type of detailed importance calculation method is not limited.

For example, the server 10 may calculate the first detailed importance by using a TF-IDF (Term Frequency-Inverse Document Frequency) analysis method that calculates the importance based on the appearance frequency as one of the text analysis methods.

4 is a flowchart illustrating a method of calculating a second detailed importance of a word according to an embodiment of the present invention.

Referring to FIG. 4, in step S310, the server 10 may count the total number of words in the patent classification information and count the number of occurrences of words in the patent classification information.

Here, the patent classification information is a code capable of classifying a patent according to a technical field, and may be any one of IPC (International Patent Classfication), CPC (Cooperative Patent Classification), and F-Term.

Thereafter, in step S320, the server 10 may calculate the number of appearances of words in the patent classification information relative to the total number of words in the patent classification information as a third appearance ratio.

Subsequently, in step S330, the server 10 may count the total number of sentences of the patent classification information, and count the number of sentences in which the word appears among the sentences of the entire patent document.

In step S340, the server 10 may calculate the total number of sentences of the entire patent document compared to the number of sentences in which words appear among the sentences of the entire patent document as a fourth appearance ratio.

To this end, the server 10 may search for a word from the patent classification information and search for a sentence including the word. In addition, the server 10 may count the total number of words and the total number of sentences by analyzing the sentence component of the patent classification information.

Finally, in step S350, the server 10 may calculate the second detailed importance based on the third appearance rate and the fourth appearance rate.

In this case, the server 10 may calculate the second detailed importance by using Equation 2 below.

<Equation 2>

Here, W ₂ is the second detailed importance, ipcw is the number of occurrences of words in the patent classification information, IPCW is the total number of words in the patent classification information, and ipcs is the number of sentences in which words appear in the entire patent document. And IPCS is the total number of sentences in the entire patent document, and a2 is the adjustment constant of the fourth appearance rate.

Referring to Equation 2, the server 10 can calculate the second detailed importance as the number of occurrences of words in the patent classification information is large and the number of sentences in which the word appears among sentences of the entire patent document is small.

That is, the server 10 may calculate the second detailed importance higher as a word is used repeatedly in one sentence in the patent classification information.

On the other hand, the server 10 increases the fourth appearance rate even if the number of sentences in which words appear among the sentences of the entire patent document by increasing the adjustment constant of the fourth appearance rate are small, and decreases the adjustment constant of the fourth appearance rate. Thus, even if the number of sentences in which words appear among the sentences of the entire patent document is large, the fourth appearance rate can be reduced.

Note that in one embodiment, as long as the server 10 calculates the second detailed importance of words in the patent document, the type of detailed importance calculation method is not limited.

For example, the server 10 may calculate the second detailed importance by using a TF-IDF (Term Frequency-Inverse Document Frequency) analysis method that calculates the importance based on the appearance frequency as one of the text analysis methods.

5 is a flowchart illustrating a method of calculating a third detailed importance of a word according to an embodiment of the present invention.

Referring to FIG. 5, in step S410, the server 10 may search for a search patent document including a word for which an importance score is to be calculated from among all patent documents.

In step S420, the server 10 may calculate an influence value of each search patent document based on reference information of each search patent document.

Specifically, the server 10 can calculate the influence value based on the number of items that are the same as the other patent documents by one or more of the applicant, inventor, and right holder as reference information of the search patent document, the number of citations and the number of citations as reference information have.

That is, the server 10 may calculate the degree to which the searched patent document is related to other patent documents as the influence value. For example, when the search patent document is cited from several patent documents, the server 10 may determine that the search patent document has an influence on the corresponding patent document and calculate the value of the search patent document as the influence value of the search patent document.

In step S430, the server 10 may calculate the third detailed importance of the search patent document by using the calculated influence value for each search patent document.

Specifically, the server 10 may calculate an average of the calculated influence values for each search patent document, and calculate the calculated average as a third detailed importance.

6 is a flowchart illustrating a method of calculating an importance score of a word according to an embodiment of the present invention.

Referring to FIG. 6, in step S510, the server 10 may read the above-described first detailed importance, second detailed importance, and third detailed importance.

At this time, the server 10 compares the minimum detailed importance values set in correspondence with each of the first detailed importance, the second detailed importance, and the third detailed importance, and each of the first detailed importance, the second detailed importance, and the third detailed importance. If the value is less than the minimum detailed importance value, the recalculation process can be performed for the detailed importance.

Thereafter, in step S520, if the first detailed importance, the second detailed importance, and the third detailed importance are greater than or equal to the minimum detailed importance value, the server 10 sums up a plurality of the first detailed importance, the second detailed importance, and the third detailed importance. Thus, it can be calculated as an importance score.

In step S540, the server 10 may output the calculated importance score to an internal memory or processor, or may transmit the calculated importance score to an external server.

7 is a block diagram of an apparatus for calculating a word importance score according to an exemplary embodiment.

The processor 102 may include one or more cores (not shown) and a graphic processing unit (not shown) and/or a connection path (eg, a bus) for transmitting and receiving signals with other components. .

The processor 102 according to an embodiment executes one or more instructions stored in the memory 104 to perform the method of calculating the importance score of a word described with reference to FIGS. 1 to 6.

For example, the processor 102 acquires a word to be calculated from the target patent document by executing one or more instructions stored in the memory, and obtains the first detailed importance of the word in the entire patent document and the target patent document The second detailed importance of words in the patent classification information corresponding to the technical field information and the third detailed importance of the search patent document containing the word among all patent documents are calculated. The importance score of the word may be calculated based on one or more of the importance and the third detailed importance.

Meanwhile, the processor 102 temporarily and/or permanently stores a signal (or data) processed inside the processor 102, and a RAM (Random Access Memory, not shown) and a ROM (Read-Only Memory). , Not shown) may further include. In addition, the processor 102 may be implemented in the form of a system on chip (SoC) including at least one of a graphic processing unit, RAM, and ROM.

The memory 104 may store programs (one or more instructions) for processing and controlling the processor 102. Programs stored in the memory 104 may be divided into a plurality of modules according to functions.

The steps of a method or algorithm described in connection with an embodiment of the present invention may be implemented directly in hardware, implemented as a software module executed by hardware, or a combination thereof. Software modules include Random Access Memory (RAM), Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), Flash Memory, hard disk, removable disk, CD-ROM, or It may reside on any type of computer-readable recording medium well known in the art to which the present invention pertains.

Components of the present invention may be implemented as a program (or application) and stored in a medium in order to be combined with a computer as hardware to be executed. Components of the present invention may be implemented as software programming or software elements, and similarly, embodiments include various algorithms implemented with a combination of data structures, processes, routines or other programming components, including C, C++ , Java, assembler, or the like may be implemented in a programming or scripting language. Functional aspects can be implemented with an algorithm running on one or more processors.

In the above, embodiments of the present invention have been described with reference to the accompanying drawings, but those skilled in the art to which the present invention pertains can be implemented in other specific forms without changing the technical spirit or essential features. You will be able to understand. Therefore, the embodiments described above are illustrative in all respects, and should be understood as non-limiting.

10: server
102: processor
104: memory

Claims (1)

In the word importance score calculation method,
Obtaining, by the server, a word for which an importance score is to be calculated from the target patent document;
The server includes the first detailed importance of the word in the entire patent document, the second detailed importance of the word in the patent classification information corresponding to the technical field information of the target patent document, and the word in the entire patent document. Calculating one or more of the third detailed importance of the searched patent document; And
And calculating, by the server, the importance score of the word based on at least one of the first detailed importance, the second detailed importance, and the third detailed importance,
The step of calculating the detailed importance of the word
Calculating an importance score of a word comprising calculating an influence value of each search patent document based on reference information of each search patent document, and calculating a third detailed importance of the search patent document using the influence value Way.

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