JP4838743B2 - Similar text search program - Google Patents

Description

  The present invention relates to a computer program for searching a sentence similar to a sentence input by a user from sentence data stored in a database.

With the spread of computers and the progress of computerization of data, the need to efficiently retrieve documents from a huge database is increasing. As a document search technique, a technique for performing a text search of a document in a database based on a user input keyword is known, but there is a problem that the number of documents to be searched is too many or not searched at all.
For this reason, a technique has been disclosed that allows a user to specify and input a part of speech of a keyword together with a keyword, perform a database search under a search condition that combines the keyword and the part of speech, and improve search accuracy and efficiency. (See Patent Document 1).

  On the other hand, in keyword search, there is an essential problem that a user needs to set a keyword and that the keyword is not searched unless it corresponds to the keyword. Therefore, when the user inputs a natural sentence or a word string, morphological analysis of the sentence is performed, and the semantic category of the word in the input sentence is extracted based on the semantic category set for each word, and the word and the semantic category are extracted. A technique for searching for search sentences (similar sentences) stored in a database as a key is disclosed (see Patent Document 2).

JP-A-9-73460 Japanese Patent No. 2732661

However, in the case of the technique described in Patent Document 1 described above, it is necessary for the user to set the part of speech together with the keyword. If these settings are inappropriate, the number of documents to be searched is too many or no search is performed. The problem of not being done is not resolved.
In the case of the technique described in Patent Document 2, a semantic category is set for each word in advance, but the meaning may change depending on the position of the word in the sentence and the relationship with the preceding and following words. The accuracy and usability are not sufficient in terms of analysis. For example, it is more convenient for a user to determine the context of words in an input sentence on the system side and to search a sentence appropriately similar to that sentence (hereinafter referred to as an ambiguous search). .

  The present invention has been made in view of the above-described problems. Even if a user inputs a sentence without being aware of the keyword, the present invention can accurately and based on the position and context of words (parts of speech) in the sentence. The purpose is to provide a similar text search program that can search for similar text flexibly.

  In order to achieve the above-described object, the similar sentence search program of the present invention executes a process of searching for a sentence similar to the input sentence, determines a phrase by performing morphological analysis on the input sentence, and sets each phrase. Analyzing the dependency for each dependency, and arranging the clauses in the order of appearance, and when a verb or a clause with no dependency appears, a compound word that includes all the clauses including and including the verb or clause A compound word creation process to be created; a sentence database recording process in which the compound word is associated with the input sentence and recorded in a sentence database; and when an arbitrary original sentence is newly input, the analysis process and the compound word A similar sentence search process for searching a sentence including the compound word as the key from the sentence database using the compound word obtained for the original sentence as a key. When, and having an output step of outputting the retrieved text.

  In this similar sentence search program, even if a user inputs a sentence without being aware of the keyword, one or more clauses reflecting the meaning contents based on the position and context of the word in the sentence are grouped, and the group Since a compound word having a word included in is created, similar sentences can be searched with high accuracy and flexibility using this compound word as a key.

Moreover, it is preferable that the similar sentence search program of this invention deletes a predetermined part of speech and / or unifies the utilization form of a verb among the parts of speech contained in the said compound word in the said compound word preparation process.
In this similar sentence search program, since an extra part of speech in a compound word is deleted, an ambiguous search is easily performed.

Further, the similar sentence search program of the present invention provides a first sentence having all of the compound words of the original sentence and the compound words of the original sentence in the similar sentence search process when there are a plurality of compound words of the original sentence. It is preferable that a second sentence having at least one of them is searched from the sentence database, and a predetermined weight is given to the first sentence and the second sentence.
In this similar sentence search program, various search results can be obtained according to the number of key compound words, and the results are weighted and output to perform an ambiguous search that balances the accuracy and flexibility of the search. be able to. In particular, even if there are individual differences in the text input by the user, the search can be executed flexibly, and the problem that the result cannot be obtained by a strict search is solved.

Further, the similar sentence search program of the present invention includes an integrated sentence creation process for classifying the inputted sentences into a predetermined category and creating an integrated sentence in which the similar sentences belonging to the same category are upgraded. An integrated sentence management process that records the compound word obtained by executing the analysis process and the compound word creation process on the integrated sentence, and records it in the sentence database in association with the integrated sentence, In the similar text search process, it is preferable to search the integrated text recorded in the text database using a compound word obtained from the original text as a key.
In this similar sentence search program, since an integrated sentence obtained by collecting original sentences in a sentence database is also a search target, various search results can be obtained and an ambiguous search can be easily performed.

The similar sentence search program of the present invention preferably ranks the search results in accordance with the weight assigned to the part of speech included in the compound word in the similar sentence search process.
In this similar sentence search program, for example, when the searched compound word includes many parts of speech, or the search order of compound words including the part of speech designated as an important phrase is increased, the search accuracy can be improved.

Furthermore, the similar text search program of the present invention preferably ranks the search results according to the weight assigned to the category in the similar text search process.
In this similar text search program, since the category in the text database is also a search target, various search results can be obtained and an ambiguous search can be easily performed.

The present invention has the following effects.
That is, according to the similar sentence search program of the present invention, even if a user inputs a sentence without being aware of the keyword, it is accurate and flexible based on the position and context of the word (part of speech) in the sentence. Search for similar sentences.

Hereinafter, an embodiment of a similar text search program according to the present invention will be described with reference to the accompanying drawings.
FIG. 1 is a block diagram showing a search system for executing a similar text search program of the present invention on a computer.

  The search system 100 may be a Web server or the like, and includes a processor 101 such as a CPU, a program storage unit 103 that stores a similar text search program of the present invention, a synonym dictionary 104, and a text DB (database) unit 105. The program stored in the program storage unit 103 is stored in a memory (ROM, RAM, etc.) (not shown) and executed by the processor 101.

The search system 100 is connected to the user terminal 200 and the sample sentence DB unit 300 via a network 400 such as the Internet. The user accesses the search system 100 from the user terminal 200 and inputs the original text (for example, Japanese free text) desired to be searched, and the search result is transmitted from the search system 100 to the user terminal 200. .
The sample sentence DB unit 300 may be a database server or the like, and various Japanese sentence data to be accumulated in the sentence DB 105 are accumulated and transferred to the sentence DB 105 as necessary.

  In the search system 100, a program storage unit 103 made up of a recording medium such as a hard disk drive includes a classification program 1031, an integration program 1032, a morpheme analysis program 1033, a dependency analysis program 1034, a compound word creation program 1035, and a score (weight). A designation program 1036, a similar sentence search program 1037, and an output program 1038 are provided. In addition to the above-described programs, the program unit 103 appropriately includes other programs for executing the Japanese free text search method of the present invention.

The classification program 1031 classifies the sentences stored in the sample sentence DB unit 300 into predetermined categories (major classification, middle classification, small classification, and fine classification).
The integrated program 1032 creates a simple integrated sentence by superimposing (integrating) similar sentences belonging to the same category among sentences classified by the classification program 1031.

The morpheme analysis program 1033 executes morphological analysis of sentences. Here, the morpheme refers to the minimum character string (part of speech) that does not make sense if the character string is made finer than this, and the morpheme analysis is a well-known analysis method in the Japanese search technology. In the present invention, for example, a part of speech is set in the synonym dictionary 104 in advance, and the morphological analysis can be performed by decomposing the sentence into parts of speech while referring to the synonym dictionary 104.
The sentences to be analyzed by the morphological analysis program 1033 include 1) the original sentence (original sentence) accumulated in the sample sentence DB unit 300, 2) the integrated sentence integrated by the integrated program 1032, and 3) the user terminal. The original text of the text entered from.
In the present invention, the “original text” refers to the original text before being integrated.

  The dependency analysis program 1034 determines a phrase based on morphological analysis and analyzes the dependency for each phrase. A phrase is a unit defined in Japanese and consists of an independent word or an independent word followed by an attached word. A dependency defines a relationship between phrases. Determination of clauses and dependency is a well-known method in Japanese search technology and language processing (kana-kanji conversion, etc.).

  In the present invention, for example, an independent word or an attached word is set in advance in the synonym dictionary 104 for each type of part of speech obtained by morphological analysis, and a phrase can be analyzed with reference to this. Further, in the present invention, whether or not the latter clause is related to each type of part of speech is set in advance in the synonym dictionary 104, and the dependency between phrases can be analyzed with reference to this.

  The compound word creation program 1035 arranges the clauses in the order of appearance based on the analysis result by the dependency analysis program 1034, and when a verb or an unrelated clause appears, all the clauses including the verb or the clause before it are included. Create a compound word that groups The compound word creation program 1035 executes compound word simplification described later.

  The score (weighting) designation program 1036 designates a score (weighting) in advance in the sentence data recorded in the sentence DB unit 105 when the user searches for similar sentences from the sentence DB unit 105, whereby the search result It is possible to improve the suitability (fitness) of search by giving superiority to inferiority.

The similar text search program 1037 executes a search process based on the text DB unit 105 when the user accesses the search system 100 to perform a search.
The output program 1038 transmits the search result to the user terminal 200.

The sentence DB unit 105 records the compound word created by the compound word creation program 1035 in association with the sentence to be analyzed. If necessary, the sentence DB unit 105 further records the integrated sentence integrated by the integrated program 1032 and the category in association with the compound word.
The timing of recording the data in the sentence DB unit 105 is not limited to the point in time when the sentence data is transferred from the sample sentence DB unit 300, but immediately when a sentence to be searched is input from the user terminal 200. It can also be recorded dynamically (in real time) by creating compound words of sentences.

<Record to text DB>
Next, the recording process to the sentence DB performed by executing the program of the present invention will be described with reference to FIGS. FIG. 2 is a flowchart showing a procedure for recording in the sentence DB.
In FIG. 2, first, the classification program 1031 executes classification of sentences accumulated in the sample sentence DB unit 102 (step 210). Categorization means classifying sentences into predetermined categories.

  Examples of categories include those composed of a plurality of upper and lower concepts such as “major category, middle category, minor category and fine category” as shown in FIG. For example, the major classification and middle classification are a collection of keywords “foreign”, and the minor classification and fine classification are classified as words, phrases, short sentences, or sentences relating to “foreign”.

  It should be noted that at least one of keywords, short sentences, or sentences associated with each of these classifications is set in the synonym dictionary 104 in advance, and by referring to the synonym dictionary 104, the inputted sentences are classified into categories. The result of classification is recorded in the sentence DB unit 105. Also, for example, keywords corresponding to the major classification and middle classification are set in the synonym dictionary 104, and the sentence input based on the synonym dictionary 104 is classified to the middle classification, and then the clauses in the sentence are subclassified. By assigning to or sub-category, words or phrases belonging to the sub-category or sub-category may be recorded dynamically.

After executing Step 210, the integration program 1032 creates a simple integrated sentence by upgrading (integrating) similar sentences belonging to the same category (Step 220). This process is performed as shown in FIG. 4, for example.
In FIG. 4, it is assumed that there are sentences (original texts) A and B belonging to the same category (major classification: outpatient, middle classification: selection of hospital / doctor). The integrated program 1032 determines that the original texts A and B whose major classification and middle classification match are similar texts, and then, from the result of the morphological analysis of each original text A and B, “consultation”, “worried”, “stray” Part of speech. The model sentence corresponding to the appearance of these parts of speech “I was worried about choosing which hospital or doctor to receive treatment from now on” is set in the synonym dictionary 104 in advance, and these parts of speech are acquired. Then, the integrated program 1032 extracts a model sentence with reference to the synonym dictionary 104, and outputs it as an integrated sentence.

  Next, the morpheme analysis program 1033 performs morpheme analysis on each category, integrated sentence, and original sentence, and determines a phrase (step 230). Next, the dependency analysis program 1034 determines a phrase based on morphological analysis and analyzes the dependency for each phrase (step 240). Morphological analysis and phrase determination are as described above, and known morphological analysis and phrase determination methods can be employed.

For example, taking the case where the original text is “A bone metastasis was recognized in the lumbar spine and spine and the doctor told me that surgery was not possible.”, These methods will be explained specifically.
First, when the original text is classified into parts of speech by morphological analysis, it is as shown in FIG.
Next, the classified parts of speech are further classified into independent words and adjunct words. Here, independent words are words that can constitute a phrase even in a sentence alone, and are “lumbar spine”, “spinal cord”, and “bone metastasis” in the example sentences. An adjunct is not a word that can form a phrase by itself, but is always used as part of a phrase under an independent word, such as “to”, “ni”, “ga”, etc. .
In this way, the clauses can be determined by classifying into independent words and attached words. In the example sentence, it is divided into clauses at the position (/) of “Lumbar vertebrae / vertebrae / bone metastasis / recognized / physician / inoperable / notified”.

  Next, in dependency analysis, it is determined with reference to the synonym dictionary 104 whether the part of speech is related to the latter section or not. For example, the particle “to” in the phrase “lumbar vertebra” is set to relate to the subsequent phrase, so the phrase “lumbar vertebra” (phrase number 0) is the posterior section “to the spine” (phrase number 1). ). Moreover, since the phrase “telled” includes punctuation marks, it is determined that there is no dependency. The result of the dependency analysis of the above example sentence is as shown in FIG.

  Next, the compound word creation program 1035 creates a compound word according to the result of the dependency analysis program 1034 (step 250). That is, the compound word creation program 1035 arranges clauses in the order of appearance, and when a verb or an unrelated clause appears, creates a compound word including all the clauses including and including the verb or clause as a group.

In the case of the above example sentence, the phrase “recognized” is a verb, and the phrase “spoken” has no relation, so a group including these previous phrases should be created as compound words 1 and 2, respectively. It becomes. For example, compound word 1 is composed of four clauses including the clause “recognized” and including previous clauses.
Compound Word 1: Bone metastasis was found in the lumbar spine and spine. Compound Word 2: The doctor told me that surgery was impossible.

  The above-mentioned compound word groups one or more clauses by using a verb or unrelated clause in the sentence as a break position, so that a group reflecting the semantic content based on the position and context of the word can be obtained. And since a compound word is comprised from the word contained in the said group, by using this compound word as a key, the precision and flexibility (fuzzy search) of search can be made compatible, and a similar sentence can be searched easily.

  In other words, the present invention is a grouping of keywords for each semantic content in a sentence. As will be described later, all compound words in a compound word input by a user are used as search keys. In addition, when a search using at least one of them as a search key is performed at the same time, search results are diversified, and search flexibility (ambiguity) is further improved.

  The compound word created in this way includes elements that complicate the search, such as particles, adverbs and conjunctions. For this reason, it is preferable that the compound word creation program 1035 simplifies the compound word by deleting a predetermined part of speech and / or unifying the utilization form of the verb among the parts of speech included in the compound word (step 260).

The part of speech to be deleted is a moving verb, symbol, adjective-suffix, adjective-non-independent, particle, auxiliary verb, conjunction, verb-suffix, adverb, noun-independent, noun-number, noun-suffix, noun-pronoun, noun -Part-of-speech classification or part-of-speech classification such as adverbial possible, conjunction, verb-non-independent, verb (some are, is, is, is, thinks). In the case of the above example sentence, “re” in “acknowledgment + reed” is a verb but is deleted because it is a suffix.
In addition, in order to unify the utilization form of the verb, for example, it is applicable to unify “acknowledgement” to the basic form “acknowledgement”.

In the case of the above example sentence, the simplified compound word is as follows.
Compound word 1: Lumbar spine Bone metastasis Acknowledgment Compound word 2: Doctor Surgery Impossible Tell As described above, compound words created for each category, integrated sentence, and original sentence respectively are classified into each category, integrated sentence, and original sentence. They are associated with each other and recorded in the sentence DB unit 105.

  Next, the score (weighting) designation program 1036 automatically determines the score (weighting) of words included in the sentence data recorded in the sentence DB unit 105 (step 270). As the score, there are weighting according to the frequency of use of the word in the sentence and weighting according to the importance of the word.

As a weighting determination method according to the frequency of use, for example, the number of times of use of each word included in the compound word simplified in step 260 is counted, and according to the frequency of use of each word, as shown in FIG. There is a method of automatically assigning points.
As a method for determining the weight according to the importance of the word, for example, there is a method of counting a specific word having a high importance and overwriting the count of the importance on the score automatically assigned according to the use frequency. According to the method according to the importance of the word, the score score of the keyword in the specific field can be raised, and the matching of the search result in the field desired by the user can be improved.

<Use and search of DB by users>
Next, the execution processing of the program of the present invention when a user accesses the search system 100 and uses the text DB unit 105 to perform a search will be described with reference to FIGS. FIG. 8 is a flowchart showing a search processing procedure.
In FIG. 8, first, when a Japanese free sentence (original sentence) is input from the user terminal 200, the similar sentence search program 1037 executes a morphological analysis program 1033, a dependency analysis program 1034, and a compound word creation program 1035. A compound word of the input Japanese free sentence is created by the processing procedure described with reference to FIG. 2 (step 510).

Next, the similar sentence search program 1037 searches the sentence DB unit 105 for the presence of this compound word using the compound word created in step 510 as a key. If there are a plurality of compound words created in step 510, this search can be performed by the following two procedures.
First, the similar sentence search program 1037 searches the sentence DB unit 105 for a sentence (original sentence, integrated sentence) or a category including all of the plurality of compound words created in step 510 (all compound word search). Step 520). For example, when the user inputs an original sentence having compound words 1 and 2, only sentences having compound words 1 and 2 are retrieved from sentences recorded in the sentence DB unit 105.

  Next, the similar sentence search program 1037 searches the sentence DB unit 105 for a sentence (original sentence, integrated sentence) or category including at least one of the plurality of compound words created in step 510. (Individual compound word search; step 530). For example, when the user inputs an original sentence having compound words 1 and 2, sentences having only compound word 1 and those having only compound word 2 are retrieved from sentences recorded in sentence DB unit 105. .

  The concept of the processing of step 520 is shown in FIG. 9, and this processing ensures the whole search degree of fuzzy search. Further, the concept of the processing in step 530 is shown in FIG. 10, and this processing secures the specificity of the fuzzy search.

Next, the similar sentence search program 1037 performs a score (weighting) on the results obtained in Steps 520 and 530, respectively, and calculates a total score combining them (Step 540).
The processing procedure of step 540 is not particularly limited. For example, it is calculated by the following formulas 1 to 3 based on the number of word matches of each compound word for the search key and the score (weighting) assigned to each matched word. The

First, in Expression 1, a matching score is calculated separately for each of the original sentence, the integrated sentence, and the category (each classification) recorded in the sentence DB unit.
Match score = (score of match word 1 + score of match word 2 + score of match word n) × number of match words (1)

Next, the matching score calculated for each of the original sentence, the integrated sentence, and the category is scored again by weighting for each of the original sentence, the integrated sentence, and the category. However, for the step 530, the search result by the category (each classification) recorded in the sentence DB part is not reflected.
Score of all compound word search results (step 520) =
(Each classification match score x Weight of each classification) + (Integrated sentence match score x Integrated sentence weight) + (Original sentence match score x Original sentence weight) (2)
Score of individual compound word search result (step 530) =
(Integrated sentence matching score × Integrated sentence weight) + (Original sentence matching score × Original sentence weight) (3)

Then, the similar sentence search program 1037 calculates a total score as a final search result based on the score of all the compound word search results and the score of the individual compound word search result by the following Expression 4 (step 540).
Total score = (total compound word search score × total compound word search weight) + (individual compound word search score × individual compound word search weight) (4)

  As described above, it is possible to ensure the accuracy and flexibility of fuzzy search by performing two types of searches, the total compound word search and the individual compound word search, and combining the results and determining the similarity ranking. it can. In other words, there is no leakage of search and there are no too many search results.

In addition, in order to automatically adjust the performance of the fuzzy search, the score distribution of each classification, integrated sentence, and original sentence may be dynamically changed from the user terminal side. By changing the score distribution, the search performance can be automatically adjusted to a level desired by the user.
For example, when the category (each classification) is emphasized, the user can expect a search result for each classification by keyword search. In addition, when emphasizing an integrated sentence, the user can expect an integrated search result by a standard search. Further, when the original text is important, the user can expect a detailed search result by the detailed search.

  Finally, the output program 1038 outputs the sentences calculated in step 540 in descending order of the total score (step 550).

<Duplicate word processing when scoring search results>
Next, the processing when a plurality of identical words (parts of speech) are included in the searched compound word in the search processing in steps 520 and 530 will be described.

  In general, when a plurality of identical words are included in a compound word, the score increases according to the number of times the word is used. For example, when the original sentence recorded in the sentence DB section is “received medical examination / diagnosed as a cold from a doctor / received a doctor's prescription”, there are three compound words. If all the scores are scored, the word “doctor” is used three times. If the word “doctor” has a score of 30 points, only the word “doctor” is included in the Japanese free text entered by the user, and the score of the corresponding original sentence is 30 points × 3 times ( Number of matches) = 90 points. However, in such a case, the weighting relationship between other words and “doctor” may be lost, and the search may not be performed successfully.

  Therefore, no matter how many times the same word appears in one sentence, the score can be corrected by processing so that the score is counted only once. In the original text, the original score of 30 points for “doctor” may be divided by the number of appearances (3 times), and the score of 10 points may be counted three times.

<Example>
Hereinafter, an example of the search according to the present invention will be shown.

(1) Text classification and text integration in text database (sentence example 1)
Major classification: Outpatient Medium classification: Outpatient consultation Small classification: Outpatient treatment Subcategory: Difficult to treat anticancer drugs in the outpatient department.
Original 1: When it recurs, I am worried that I have selected a conservative operation, and weekly anticancer drug treatment is performed in an outpatient setting, which puts a burden on the body.
Integrated sentence 1: Weekly anti-cancer drug treatment is performed in an outpatient department, which puts a burden on the body.

(Sentence example 2)
Major classification: Outpatient Medium classification: Outpatient consultation Small classification: Outpatient treatment Subcategory: Difficult to treat anticancer drugs in the outpatient department.
Original 2: Anti-cancer drug side effects and hospital visits were difficult.
Integrated sentence 2: Side effects and visits to anticancer drugs were difficult.

(Sentence example 3)
Major Category: Symptoms / Side Effects / Sequences Middle Category: Side Effects / Sequences Caused by Treatment Subcategory: Symptoms of Side Effects Caused by Anticancer Agents Subcategory: Hair Loss Caused by Anticancer Agents It was hard. I could talk to people with the disease if I was in the hospital, but I was shocked when I lost my whole body hair, and I was worried if it would grow. I wondered who could understand this anxiety.
Integrated sentence 3: Anticancer drug treatment by hospital was difficult. If you are hospitalized, you can talk to people with the same illness, but I wondered if anyone could understand the shock when the whole body lost hair and the anxiety about whether it will grow later.

(2) Morphological analysis of sentence databases eg) Difficult to treat anticancer drugs in outpatient clinics.
FIG. 11 shows the result of morphological analysis of the above example sentence.

(3) Dependency analysis of sentence databases eg) Difficult to treat anticancer drugs in outpatients.
FIG. 12 shows the result of dependency analysis of the above example sentence.

(4) Simplified compound word creation of sentence database Example sentence 1) Difficult to treat anticancer drugs in the outpatient department.
(Simplified compound word creation)
Compound 1 Outpatient anticancer drug treatment painful

Example 2) When recurrence occurs, I am worried that I have selected conservative surgery, and weekly anticancer drug treatment is performed in an outpatient department, which puts a burden on the body.
(Simplified compound word creation)
Compound Word 1 Recurrence Preserving Surgery Selection Worried Compound Word 2 Anticancer Treatment Outpatient Compound Word 3 Body Burden

Example sentence 3) Since weekly anticancer drug treatment is performed in an outpatient setting, it is burdensome to the body.
(Simplified compound word creation)
Compound word 1 Anticancer drug Treatment Outpatient Compound word 2 Body Burden

Example sentence 4) The side effects and treatment of anticancer drug treatment were difficult.
(Simplified compound word creation)
Compound 1 Anticancer treatment Treatment Side effects Visit to hospital

Example 5) It was harder than anti-cancer drug treatment by the hospital. I could talk to people with the disease if I was in the hospital, but I was shocked when I lost my whole body hair, and I was worried if it would grow. I wondered who could understand this anxiety.
(Simplified compound word creation)
Compound Word 1 Visiting Anticancer Drug Treatment Annoying Compound Word 2 Annoying Compound Word 3 Hospital Syndrome People Speak Compound Word 4 Can Compound Word 5 Whole Body Hair Loss Compound Word 6 Shock Growing Compound Word 7 Anxiety Knowing

Example 6) I was having difficulty with anticancer drug treatment at the hospital. If you are hospitalized, you can talk to people with the same illness, but I wondered if anyone could understand the shock when the whole body lost hair and the anxiety about whether it will grow later.
(Simplified compound word creation)
Compound Word 1 Visiting Anticancer Drug Treatment Hard Compound Word 2 Hospitalized Same Person Speak Compound Word 3 Can Compound Word 4 Whole Body Hair Drop Compound Word 5 Shock Grows Compound Word 6 Anxiety Understand

(5) Example of automatic word score determination Outpatient frequency of use 81 times Score 40
Anticancer drug usage frequency 2575 times score 40 (specific term)
Treatment Frequency of use 109 times Score 30
Hard use frequency 410 times Score 30

(6) Creation of compound words in Japanese free sentences entered by the user Example) Since the treatment for anti-cancer drugs is performed at the hospital, it is difficult and painful for the body due to hospital visits, waiting time, and side effects of treatment.
(Simplified compound word creation)
Compound Word 1 Anticancer Agent Treatment Visit Compound Word 2 Visit Waiting Treatment Side Effect Body Burden Compound Word 3 Hard

(7) Search with all compound words of Japanese free text entered by the user All compound words shown in (6) (anticancer drugs, treatment, visit, visit, visit, waiting time, treatment, side effects, body, Search by burden, cost, pain.

(8) Retrieval by individual compound words of Japanese free sentences input by the user A separate search is performed for each compound word shown in (6).
Compound Word 1 Anticancer Agent Treatment Visit Compound Word 2 Visit Waiting Treatment Side Effect Body Burden Compound Word 3 Hard

(9) Example of calculating and ranking total score from scores of all compound word search and individual compound word search However, in order to adjust each weight and word score, the score score is fluid.
(Free Japanese text entered by the user)
Since anticancer drug treatment is performed in the hospital, it is difficult and painful for the body due to hospital visits, waiting time, and side effects of treatment.

(Search first place total score: 6655)
Total compound word search score + individual compound word search score (Classification score: 2430 Original sentence score: 1475 Integrated sentence score: 2750)
Major classification: Outpatient Medium classification: Outpatient consultation Small classification: Outpatient treatment Subcategory: Difficult to treat anticancer drugs in the outpatient department.
Original: When relapsed, I was worried that I had selected conservative surgery, and weekly anticancer drug treatment was performed outpatiently, which puts a burden on the body.
Integrated sentence: Weekly anticancer drug treatment is performed outpatiently, so it is burdensome to the body.

(Search 2nd place total score: 6200)
Total compound word search score + individual compound word search score (Classification score: 410 Original sentence score: 950 Integrated sentence score: 4840)
Major classification: Symptoms, side effects, and sequelae Middle classification: Side effects and sequelae caused by treatment Subclassification: Symptoms of side effects caused by anticancer drugs Subclassification: Hair loss caused by anticancer drugs Original: More painful than worrying about anticancer drug treatment by hospital visits It was. I could talk to people with the disease if I was in the hospital, but I was shocked when I lost my whole body hair, and I was worried if it would grow. I wondered who could understand this anxiety.
Integrated text: Anticancer drug treatment by hospital was difficult. If you are hospitalized, you can talk to people with the same illness, but I wondered if anyone could understand the shock when the whole body lost hair and the anxiety about whether it will grow later.

(Search 3rd place total score: 4970)
Total compound word search score + individual compound word search score (Classification score: 2430 Original sentence score: 900 Integrated sentence score: 1640)
Major classification: Outpatient Medium classification: Outpatient consultation Small classification: Outpatient treatment Subcategory: Difficult to treat anticancer drugs in the outpatient department.
Original 2: Anti-cancer drug side effects and hospital visits were difficult.
Integrated sentence 2: Side effects and visits to anticancer drugs were difficult.

It is a block diagram which shows the search system for performing the similar text search program of this invention on a computer. It is a flowchart which shows the recording procedure to text DB. It is the figure which illustrated the category (each classification). It is the figure which showed an example of the process which produces an integrated sentence. It is the figure which showed an example which classify | categorizes an original sentence into a part of speech by morphological analysis. It is the figure which showed an example which carries out dependency analysis of an example sentence. It is the figure which showed an example which weights the word in the searched sentence according to use frequency. It is a flowchart which shows a search processing procedure. FIG. 10 is a diagram showing a concept of all compound word search by the process of step 520. FIG. 11 is a diagram showing a concept of individual compound word search by the processing of step 530. It is the figure which showed another example which classifies an original sentence into a part of speech by morphological analysis. It is the figure which showed another example which carries out dependency analysis of an example sentence.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 ... Search system 101 ... Processor 103 ... Program storage part 104 ... Synonym dictionary 105 ... Text DB part 200 ... User terminal 300 ... Sample text DB part 400 ... Network 1031 ... Classification program 1032 ... Integrated program 1033 ... Morphological analysis Program 1034 ... Dependency analysis program 1035 ... Compound word creation program 1036 ... Score (weighting) designation program 1037 ... Similar sentence search program 1038 ... Output program

Claims (6)

A computer program that executes a process of searching for a sentence similar to an inputted sentence,
Analyzing process of analyzing the dependency for each phrase and determining the phrase by morphological analysis of the input sentence,
Arranging the clauses in the order of appearance, and when a verb or an unrelated clause appears, a compound word creating process for creating a compound word including all the clauses including and including the verb or clause; and
A sentence database recording process of associating the compound word with the input sentence and recording it in a sentence database;
When an arbitrary original sentence is newly input, the analysis process and the compound word creation process are executed, and the compound word that becomes the key from the sentence database with the compound word obtained for the original sentence as a key A similar sentence search process for searching sentences including
An output process for outputting the searched sentence. A similar sentence search program characterized by comprising: The similar sentence search program according to claim 1,
A similar sentence search program characterized in that, in the compound word creation process, a predetermined part of speech is deleted from parts of speech included in the compound word and / or a verb utilization form is unified. The similar sentence search program according to claim 1 or 2, wherein when there are a plurality of compound words of the original sentence, the first sentence having all of the compound words of the original sentence in the similar sentence search process, A similar sentence search program, wherein a second sentence having at least one of compound words is searched from the sentence database, and a predetermined weight is given to the first and second sentences. In the similar sentence search program as described in any one of Claim 1 to 3,
An integrated sentence creating process for classifying the inputted sentences into predetermined categories and creating an integrated sentence in which similar sentences belonging to the same category are upgraded;
An integrated sentence management process characterized in that a compound word obtained by executing the analysis process and the compound word creating process on the obtained integrated sentence is recorded in a sentence database in association with the integrated sentence; Further comprising
In the similar sentence search step, the integrated sentence recorded in the sentence database is searched using a compound word obtained from the original sentence as a key. The similar sentence search program according to any one of claims 1 to 4,
In the similar sentence search process, the similar sentence search program ranks the search results according to the weight assigned to the part of speech included in the compound word. In the similar text search program according to claim 4 or 5,
In the similar sentence search process, the similar sentence search program ranks the search results according to the weight assigned to the category.