JP2003330958A - Information retrieval device, method, program, and recording medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an information retrieval device highly precisely and efficiently providing a retrieval result according to a user's intention. <P>SOLUTION: This information retrieval device, at first, obtains a query inputted via an input device 3 in a step S51, and performs a language analysis to the query obtained in the step S51 in a following step S52. In a step S53, it determines that either retrieval mode is applied thereto based on the language analysis result of the query in the step S52. When the query word number is one, it is determined to apply whole sentence retrieval, when the query word number is not less than one and not more than a prescribed number, it is determined to apply a phrase retrieval, and when the query word number exceeds the prescribed number, it is determined to apply a concept retrieval. <P>COPYRIGHT: (C)2004,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an information retrieval device, an information retrieval method, a program and a storage medium having a plurality of retrieval means of different systems.

[0002]

2. Description of the Related Art In recent years, there have been increasing opportunities to handle a large amount of document data, and various methods are used as a method for searching for desired document data. This is because a simple keyword search (a keyword is designated and a search is performed based on whether or not the keyword appears) cannot sufficiently satisfy the user's request. Therefore, a method based on the relationship between keywords and the degree of similarity of syntax information, and a method of searching using a document vector that characterizes the content of a document have appeared. Also, a method has been devised in which a meaning, a field, or a word itself that characterizes contents is used as a dimension, and a vector is expressed by using the feature amount as a value, and the similarity between documents is obtained using a value such as an inner product between document vectors. ing. Although there are various search methods as described above, it is necessary for the user to determine which search method to use for the search, depending on the search purpose and the search status.

Next, a procedure for deciding which of the plurality of search methods to use for the search according to the user's search purpose and the search situation and performing the search by the determined search method will be described with reference to FIG. 18 and FIG. This will be described with reference to FIG.
FIG. 18 is a flowchart showing the procedure of a conventional search method,
FIG. 19 is a diagram showing an example of an operation screen in the conventional search method.

Here, there are three types of search modes: full-text search, phrase search, and concept search. A search mode to be used is determined from these search modes, and a case of performing a search in the determined search mode will be described. .

When performing a search, as shown in FIG. 18, first, in step S41, the query input by the user is acquired, and in the subsequent step S42, the search mode specified by the user is acquired. And step S
At 43, the query acquired at step S41 is analyzed.

Then, in step S44, the obtained user-specified search mode is full-text search, phrase search,
It is determined whether it is a concept search. Here, when the user-specified search mode is full-text search, in step S45, full-text search is performed on the information stored in the storage device based on the analysis result of the query, and in subsequent step S48, the search result by full-text search is obtained. Is displayed. Then, this process ends. When the user-specified search mode is phrase search, in step S46 a phrase search is performed on the information stored in the storage device based on the analysis result of the query, and in the subsequent step S48, the search result by the phrase search is displayed. . Then, this process ends. If the user-specified search mode is concept search, a concept search is performed on the information stored in the storage device based on the analysis result of the query in step S47, and the search result by the concept search is displayed in step S48. To do. Then, this process ends.

When performing a search, for example, an operation screen as shown in FIG. 19 is displayed, and a query is input on this operation screen. Here, it is assumed that "Kawasaki" is entered as a query. Then, the user selects the search mode on the operation screen. Here, at the user's discretion, it is assumed that the full-text search is selected as the optimum search mode when the search is performed with the intention of searching for a document or an image containing the word "Kawasaki" input after being created. . By this full-text search, documents or images containing the word "Kawasaki" are extracted from the documents stored in the storage device, and a list of the extracted documents or images is displayed as the search result. . When displaying the search results, the extracted documents and the like are displayed in a list in the order of search or those having the highest degree of coincidence.

[0008]

In the above-described conventional search method, the user himself needs to select and determine the optimum search mode according to his intention. Therefore, in order to obtain an intended search result in a short time. , The user is required to have knowledge or experience to determine which search mode is suitable for the search intention. However, when the knowledge about the features of each search mode is insufficient, the user may select a search mode different from the search mode according to the intention. In such cases,
The search may take extra time because it is not possible to obtain a search result according to the intention and it is necessary to select another search method and perform the search again.

An object of the present invention is to provide an information search device, an information search method, a program, and a storage medium that can obtain a search result according to a user's intention with high accuracy and efficiency.

[0010]

In order to achieve the above object, the present invention provides a plurality of search means each having a different method,
Input means for inputting a query, query analysis means for analyzing the input query, and at least one or more search means to be applied to a search are determined from the plurality of search means according to search application conditions. Determining means, search executing means for executing a search using the analysis result for the input query by the at least one or more determined searching means, and search results by the executed at least one or more searching means And display means for displaying.

Further, in the above information search apparatus, the search applicable condition is an analysis result for the input query.

Further, in the above information retrieval apparatus, the query analysis means includes a plurality of analysis means for respectively performing different analyzes on the input query.

Further, in the above information retrieval apparatus, the plurality of analyzing means include a morpheme analyzing means, a syntactic analyzing means and a semantic analyzing means for the inputted query.

Further, in the above information retrieval apparatus, the plurality of retrieval means include at least one of a full-text retrieval means, a phrase retrieval means, and a concept retrieval means.

Further, in the above information retrieval apparatus, it is characterized in that it is incorporated in a client in a server / client system.

Further, in the above information search apparatus, the search applicable condition is the number of clients in a connected state with the server.

Further, in the above information retrieval apparatus, the retrieval applicable condition is the number of clients connected to the server and an analysis result for the inputted query.

Further, in the above information retrieving apparatus, the information retrieving apparatus is incorporated in a terminal connectable to a communication network.

Further, in order to achieve the above-mentioned object, the present invention comprises a step of inputting a query, a step of analyzing a query, a step of analyzing a query, and a plurality of different methods according to search application conditions. A determination step of determining at least one or more search means to be applied to the search from the search means, and a search using the analysis result for the input query by the at least one or more determined search means. And a display step of displaying a search result by the at least one or more executed search means on a display means.

Further, the present invention is a computer-executable program for performing information retrieval, comprising an input step of inputting a query, a query analysis step of analyzing the input query, and a search application condition. Accordingly, a determining step of determining at least one search module to be applied to the search from a plurality of search modules having different methods, and the input query by the determined at least one search module. And a display step of displaying a search result by the at least one search module executed on the display means.

Further, the present invention is characterized in that the above program is stored in a computer-readable manner.

[0022]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings.

(First Embodiment) FIG. 1 is a block diagram showing the arrangement of an information retrieval apparatus according to the first embodiment of the present invention.
2 is a diagram showing an example in which the information search device of FIG. 1 is incorporated in a server / client system, and FIG. 3 is a diagram showing an example in which the information search device of FIG. 1 is incorporated in an Internet connection terminal.

As shown in FIG. 1, the information retrieval device includes a central processing unit 1 for executing a process according to a program stored in a storage device 2, an input device 3 such as a keyboard and a mouse for operating the process, and information. Display device 4 for displaying search results, FD (floppy (R) disk), CD
A storage medium reading device 5 for reading programs, data, etc. stored in a storage medium such as a ROM or a magnetic tape. Further, the storage device 2 stores data such as a document to be searched, and the information search device of the present information search device searches the data stored in the storage device 2 for a plurality of methods using different methods. It is possible to search using.

Further, as shown in FIG. 2, this information retrieval apparatus can be incorporated in the servers 12a, 12b or the clients 13a, 13b, 13c, 13d connected through the network 11 in the server / client system, As a result, for example, each client 13
a, 13b, 13c, 13d to servers 12a, 12b
It becomes possible to retrieve data such as documents and images held by. Furthermore, as shown in FIG. 3, the present information retrieval apparatus can be applied to a terminal 21 that can be connected to the Internet 22, so that the terminal 21 can access the WEB.
It becomes possible to search.

First, a process of registering data such as a document to be searched in the recording device 2 in the information searching apparatus will be described with reference to FIGS. 4 and 5. FIG. 4 is a flowchart showing a processing procedure when registering data such as a document to be searched, and FIG. 5 is step S9 in FIG.
4 is a flowchart showing a detailed procedure of a concept search registration process of No. 4.

When registering data such as a document, FIG.
As shown in, first, in step S91, the registered data (such as a document) is linguistically analyzed. Here, specifically, morphological analysis is performed while referring to a word dictionary, and if necessary, syntactic analysis and semantic analysis are performed. From these analysis results, full-text search index information, phrase search index information, concept search, etc. Create index information etc.

Next, in step S92, the registration data obtained in step S91 and the full-text search index information created from the analysis result are stored in a database of the storage device 2 or the like, and in the following step S93, in the step S91. The obtained registration data and phrase search index information created from the analysis result are stored in a database of the storage device 2. And step S
At 94, the registration data obtained at step S91 and the concept search index information created from the analysis result are stored in the database of the storage device 2 or the like, and this processing is ended.

Here, as the word dictionary, for example, the dictionary shown in Table 1 is used, and the dictionary shown in Table 1 is
Notation, reading, part of speech, classification (meaning), etc. are stored in association with each other. In addition, for example, when registering the document “Trends in image databases Trends in image databases 1997-08-28 Report Engineering Section Kenjiro Kawasaki”, the results shown in Table 2 were obtained by linguistic analysis of this document. To be Then, data (notation, reading, part of speech, document name, appearance position, relationship ID) including the index information created in the analysis result is stored in the storage device 2 as a database as shown in Table 3.

[0030]

[Table 1]

[0031]

[Table 2]

[0032]

[Table 3]

Next, the concept search registration process of step S94 will be described in detail. As shown in FIG. 5, first, in step S101, the language analysis result of the registered document is acquired, and in step S102, the step S101 is executed. The dictionary is searched from the words extracted in step 1, and the feature quantity for each word is obtained for each dimension, and the document vector is generated from the sum of the feature quantities. Then, in step S103, the above step S10
The document vector obtained in 2 is registered in the storage device 2 together with the content of the registered document or the document identifier.

Here, the procedure for registering the data such as the document to be searched in the storage device 2 in the information retrieval device has been described, but in the information management device such as the server holding the data such as the document to be retrieved. Also, data such as a document is registered in the same procedure as the above procedure.

Next, the concept search registration process (step S
Specific examples of No. 94) will be described with reference to Tables 4 and 5.

When registering a concept search, a language analysis result acquisition step (step S101) is first performed when a document is registered.
Then, the words included in the registered document are acquired. Then, in the document vector generation step (step 102), the document vector is calculated from the words appearing in the document using the basic vector dictionary. Here, the basic vector dictionary is shown in Table 4.
As shown in, the feature amount corresponding to each dimension (Dim.) In the vector expression is stored for each word. As a dimension, the criteria classified by the original meaning of the word,
The criteria classified according to the field of use of the word are adopted. For example, it can be seen that the feature amount of Dim.1 of word 1 in Table 4 is 0, and the feature amount of Dim.2 is 23. In this way, it is possible to obtain the feature amount of each dimension (Dim.) In one word from the basic vector dictionary. The feature amount can be interpreted as a value indicating how likely the document is to characterize the classification criterion (= dimension) by using the word. By classification criteria (by dimension) obtained from all the words that make up the document
The feature amount of the entire document is represented by a vector having a classification criterion as a dimension from the feature amount of. The obtained vector is normalized with norm = 1, and its value is stored as a document vector.

Next, in the index registration process (step 103), the document vector is stored in association with the index shown in Table 5. For example, for the document with the document ID = 6947 in Table 5, the document vector Dim.
The feature amount of 1 is 0.183, and the feature amount of Dim.2 is 0.2
It turns out that it is 14.

[0038]

[Table 4]

[0039]

[Table 5]

In this embodiment, an appropriate search mode is determined from among three search methods of full text search, phrase search, and concept search based on the analysis result of the input query.

First, the procedure of the search process of this information search apparatus will be described with reference to FIG. FIG. 6 is a flowchart showing the procedure of a search process by the information search device of FIG.

At the time of retrieval, as shown in FIG. 6, first, in step S51, the query input through the input device 3 is acquired, and in the following step S52, the above-mentioned step S5.
Linguistic analysis is performed on the query acquired in 1. And
In step S53, it is determined which search mode to apply based on the language analysis result of the query in step S52. Here, the number of query words is set as a search application condition for deciding which search mode to apply, and the search method to be applied is determined according to the number of query words. For example, when the number of query words is 1, full-text search is applied, when the number of query words is more than 1 and less than or equal to a predetermined number, phrase search is applied, and when the number of query words exceeds the above-mentioned predetermined number. , Apply concept search.

If the full-text search is applied, the full-text search is performed in step S54, and the subsequent step S5.
In step 7, the search result list of the full text search is displayed on the display device 4. Here, the search results are displayed in a list in descending order of coincidence. Then, this process ends. If it is determined that the phrase search is applied in step S53, step 5
5, the phrase search is performed, and the subsequent step S57.
Then, the search list of the phrase search is displayed on the display device 4. Here again, the search results are similarly displayed in a list in descending order of the degree of matching. Then, this process ends. When it is determined that the concept search is applied in step S53, the concept search is performed in step 56, and the subsequent step S57.
Then, the search list of the concept search is displayed on the display device 4. Here again, the search results are similarly displayed in a list in descending order of the degree of matching. Then, this process ends.

Next, the linguistic analysis of the input query in step S52 will be described with reference to FIG. FIG. 7 is a flowchart showing a detailed procedure of the query language analysis in step S52 of FIG.

In the language analysis of the above input query,
As shown in FIG. 7, first, in step S71, morphological analysis is performed on the input character string of the query with reference to the word dictionary (Table 1), and then in step S71.
At 72, if necessary, the input query is parsed to create syntax information such as dependency analysis. And
In step S73, semantic analysis is performed from the input semantic information of the query, and this processing ends.

Next, details of the phrase search in step S55 will be described with reference to FIG. FIG. 8 is a flowchart showing a detailed procedure of phrase search in step S55 of FIG.

In the phrase search, as shown in FIG. 8, first, in step S81, a query word is obtained from the morpheme analysis result in step S52, and then in step S82, the query word is obtained from the morpheme analysis result in step S52. Get syntax information for. Then, in step S83, the above steps S81 and S82.
The relationship between the query word and the query word acquired in step 1 and the relationship between the document word and the document word are compared to calculate the degree of similarity, and the present process ends.

Next, details of the concept retrieval process in step S56 will be described with reference to FIG. FIG. 9 is a flowchart showing a detailed procedure of the concept search process in step S56 of FIG.

In the concept search process, as shown in FIG. 9, first, in step S111, the query language analysis result generated in step 52 is acquired, and then in step S1.
At 12, a query vector is generated from the analysis result obtained at step 111. And step S
At 113, the similarity is calculated by comparing the query vector obtained at step S112 with the document vector (Table 5) for each document stored in the storage device 2 at the time of registration,
This similarity is listed as a search result, and this processing ends.

Next, a search example by this information search apparatus will be described with reference to FIGS. 10 and 11. Figure 10
Is a diagram showing an example of a query input screen displayed by the information search device of FIG. 1, and FIG. 11 is a diagram showing an example of a search result list display screen displayed by the information search device of FIG.

When performing a search, for example, a query input screen shown in FIG. 10 is displayed, and the input device 3 is displayed on this screen.
The input string entered as a query via is displayed. Here, the case where "Kawasaki" is input as the input character string is shown. This input query is stored in the storage device 2
(Step S51 of FIG. 6). Then, language analysis is performed on the input query (step S52). In this linguistic analysis, first, the word dictionary (shown in Table 3) stored in the storage device 2 is searched by morphological analysis, linguistic analysis is performed, and the word "Kawasaki" is created.

Search method selection step (step S53)
Then, the search method to be applied is selected based on the language analysis result in step S52. Here, since the number of words in the query is one (one word “Kawasaki”), it is determined that the full-text search is applied. In the full-text search step (step S54), the character string "Kawasaki" is searched from the information such as the annotation of the document or image stored in the storage device 2 and the full-text search index in the registration flowchart shown in FIG. Then, as shown in FIG. 11, the search results of this search are displayed in a list on the display device 4 in descending order of coincidence (step S57). The search result list is stored in the storage device 2 as needed.

Next, a phrase search step (step S
55) will be described in detail with reference to FIG.
FIG. 12 is a diagram showing an example of phrase search data.

For example, as shown in FIG. 12A, when "print an image" is input as a query, "image", "o",
Since "print" is extracted as the query word, the phrase search is selected as the search method to be applied from the number of query words. Then, the phrase search (step S55) is executed. In this phrase search step, a query word acquisition step (step S81)
Then, from the above input query, "image", "o",
"Print" is obtained as the query word. Here, phrase search is selected as the applicable search method from the number of query words.

Next, in the inter-word relation acquisition step (step S82), "" the image "is related to" print "" is acquired. Then, in the similarity calculation step (step S83), the degree to which the relationship between words is similar is calculated. Here, for example, as shown in FIG. 12B, if the document 1 includes the word “image” and the word “print”, “the image is related to“ print ”” and “ "High speed is related to" print "" and "Image" is related to "print""
Are similar to each other, the degree of similarity in which the document 1 includes similar phrases = 1-point deduction due to word (0) -point deduction due to relation (0.1 because the distance between words is 1 word) = 0.9. On the other hand, in the case of the document 2 shown in FIG. 12 (c), the similarity is calculated by the same formula, ie, “similarity = 1−point deduction by word (0) −”
Deduction due to the relationship (0.5 with different contact) = 0.5.

Next, the concept retrieval step (step S5
Details of 6) will be described.

In the concept search, first, in the query language processing result acquisition step (step S111), the words included in the query are acquired. Next, in the query vector generation step (step S112), a query vector is generated by referring to the basic vector dictionary as in the document vector generation. Then, in the similarity calculation step (step S113), the similarity between the query feature vector and each document vector is actually calculated.

As described above, in this embodiment, since the search method to be applied is determined according to the number of query words obtained from the analysis result of the input query, the search result according to the user's intention is highly accurate. And can be obtained efficiently.

(Second Embodiment) Next, a second embodiment of the present invention will be described with reference to FIGS. 13 to 16. FIG. 13 is a flowchart showing a search procedure of the information search device according to the second embodiment of the present invention, and FIG. 14 is a diagram showing an example of a query input screen in the information search device according to the second embodiment of the present invention. 15 is a diagram showing an example of a display screen of search results in the information search device according to the second embodiment of the present invention, and FIG. 16 is a diagram when a different query is input in the information search device according to the second embodiment of the present invention. It is a figure which shows the example of an input screen.

The present embodiment is different in that one or more search methods can be applied to the first embodiment in which only one search method is applied.

Specifically, as shown in FIG. 13, when a query is input, first, in step S61, the input query is acquired and stored in the storage device 2, and then in step S62, the acquired query is acquired. Is input, and the query language is analyzed. Then, in step S63,
At least one search method is determined as a search method to be applied based on the query analysis in step S63. In the present embodiment, as the search application condition, if there are no unknown words, full-text search is performed, and if the number of independent words is 8 or less, phrase search is performed.
A condition that a concept search is applied when there are three or more independent words is set, and the search method to be applied is determined according to this condition.

Then, in step S64, it is determined based on the determination result in step S63 whether or not the full text search is applied. When applying the full-text search, step S6
In 5, the full text search is performed, and the process proceeds to step S66.
On the other hand, if the full-text search is not applied, step S
Step 65 is skipped and the process proceeds to step S66.

In step S66, it is determined whether or not the phrase search is applied. If the phrase search is applied, the phrase search is performed in step S67, and the process proceeds to step S68. On the other hand, when the phrase search is not applied, the above step S67 is skipped and the process proceeds to step S68.

In step S68, it is determined whether or not the concept search is applied. Here, when applying the concept search,
In step S69, a concept search is performed and step S
Proceed to 70. On the other hand, when the concept search is not applied, step S69 is skipped and the process proceeds to step S70.

In step S70, the search results obtained by the applied search method are merged and displayed in descending order of coincidence on the display device 4, and the search result list is stored in the storage device 2 as necessary. . Then, this process ends.

For example, as shown in FIG. 14, when the input character string "about the effect of interest rates on the Japanese economy" is input as a query from the input device 3, the query language analysis (step S62) determines that the query word is "Japan", "no", "economy", "at", "interest rate",
“Of”, “impact”, and “about” are acquired. In this case, the number of independent words is 4, and there are no unknown words.
Therefore, it is determined that the phrase search and the concept search are applied to the input query (step S6).
3) The phrase search and concept search are performed (steps S67 and S69). Then, the search results of the phrase search and the concept search are displayed on the display device 4 in descending order of coincidence, as shown in FIG. 15 (step S70).

Further, as shown in FIG. 16, when the input character string "about Jubilo's Khajevsky" is input as a query, in the query language processing step (step S62), "Jubilo" as the query word,
"No", "Hadevsky" and "About" are acquired. In this case, the search determination step (step S63) determines that the number of independent words is 2, there are two unknown words, and that there are no independent words other than the unknown words. Here, as a condition for applying the search method, for example, if there are no unknown words, full-text search is not performed, if the number of independent words other than unknown words is 2 or more and 8 or less, phrase search is performed, and independent words are 3 or more. Then, if the concept search is performed, it is determined that the full-text search is applied to the query (step S63), and the full-text search is performed (step S65). Then, the search results obtained by the full-text search are displayed on the display device 4 in the descending order of coincidence (step S70).

As described above, by applying a plurality of retrieval methods, it is possible to obtain retrieval results with higher accuracy according to the user's intention.

(Third Embodiment) Next, a third embodiment of the present invention will be described with reference to FIG. Figure 1
7 is a flowchart showing a search procedure in the information search device according to the third embodiment of the present invention.

The present embodiment is different from the above-described first and second embodiments in that which search method is applied is determined according to the number of pieces of information to be searched.

Specifically, as shown in FIG. 17, when a query is input, first in step S201, the input query is acquired and stored in the storage device 2, and in the subsequent step S202, the acquired query is acquired. Is input, and the query language is analyzed. Then, in step S203, among the query words obtained by the query language analysis, at least one of full-text search, phrase search, and concept search is applied according to the number of independent words (the number of information items to be searched) as a search method. decide. Here, it is assumed that only full-text search is applied when the number of information items to be searched is a predetermined number or more, and all search methods are applied when the number of information items is less than the predetermined number.

Then, in step S204, it is determined whether or not to apply the full-text search based on the determination result in step S203. When applying the full-text search, the full-text search is performed in step S205, and step S2 is performed.
Proceed to 06. On the other hand, if the full-text search is not applied, the above step S205 is skipped and step S2 is performed.
Proceed to 06.

In step S206, it is determined whether or not the phrase search is applied. If the phrase search is applied, the phrase search is performed in step S207, and the process proceeds to step S208. On the other hand, when the phrase search is not applied, the above step S207 is skipped and the process proceeds to step S208.

In step S208, it is determined whether or not the concept search is applied. Here, when applying the concept search, the concept search is performed in step S209, and the process proceeds to step S210. On the other hand, when the concept search is not applied, the above step S209 is skipped and the process proceeds to step S210.

In step S210, the searches obtained by the applied search method are merged to display the search result list on the display device 4 in descending order of the degree of coincidence, and if necessary, store the search result list in the storage device. Store in 2. And
This process ends.

As described above, in this embodiment, even if the number of pieces of information to be searched increases, it is possible to carry out the search in a fixed search time without changing the program.

On the contrary, if the number of information to be searched is small, a high-speed search method is used. If the number of information to be searched is large, an advanced search method (all search methods) is applied. When the number of pieces of target information is small, the search time becomes shorter, and when the number of pieces of search target information is larger, the search can be performed with higher accuracy and certainty.

The search application conditions (decision of the number of query words, the number of independent words, the number of unknown words and the number of independent words other than unknown words), the number of independent words (the search target information Number)), the number of characters in the query, the number of bytes, the number of words, the cumulative word frequency,
Maximum frequency word, minimum frequency word, word length, cumulative word length,
Maximum word length, minimum word length, independent word frequency, independent word, cumulative independent word frequency, maximum frequency independent word, minimum frequency independent word, maximum independent word length, minimum independent word length, presence of attached words, number of attached words, unknown Number of words, presence / absence of unknown words, number of independent words other than unknown words, presence / absence of morphological analysis processing errors, presence / absence of syntax analysis processing errors,
It is also possible to use the presence or absence of an error in the semantic analysis process or a combination thereof as the search application condition.

Also, the search method to be applied may be determined according to the number of connected clients. For example,
If the number of connected clients is up to 5, all search methods are applied. If the number of independent words other than unknown words is 5 or more and the number of connected clients is 100 or less, concept search is applied. If the number of clients is 50 or less, phrase search is not performed. It is also possible to set a condition to apply, set a condition to apply only full-text search when the number of clients exceeds 100, and determine a search method to apply according to this condition.

In addition to the number of connected clients, the maximum number of connected clients can be used as the application condition, and the client to be applied may be determined according to the maximum number of connected clients.

Furthermore, a combination of the language analysis result, the hardware processing capacity, the number of connected clients, and the like can be used as the search method application determination condition.

The present invention may be applied to either a system composed of a plurality of devices or an apparatus composed of a single device.

Further, an object of the present invention is to supply a storage medium (or recording medium) recording a program code of software for realizing the functions of the above-described embodiments to a system or apparatus, and to supply a computer of the system or apparatus ( Alternatively, by the CPU or MPU) reading and executing the program code stored in the storage medium,
It goes without saying that it will be achieved. In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiments, and the storage medium storing the program code constitutes the present invention.
Further, by executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also based on the instruction of the program code,
An operating system (OS) running on the computer does some or all of the actual processing,
It goes without saying that the processing includes the case where the functions of the above-described embodiments are realized.

Furthermore, after the program code read from the storage medium is written in the memory provided in the function expansion card inserted in the computer or the function expansion unit connected to the computer, based on the instruction of the program code. , The CPU provided in the function expansion card or the function expansion unit performs some or all of the actual processing,
It goes without saying that the case where the processing realizes the functions of the above-described embodiments is also included.

[0085]

As described above, according to the present invention,
Since at least one search means to be applied to the search is determined from among a plurality of different search means according to the search application condition, it is possible to efficiently and efficiently obtain the search result according to the user's intention. it can.

[Brief description of drawings]

FIG. 1 is a block diagram showing a configuration of an information search device according to a first embodiment of the present invention.

FIG. 2 is a diagram showing an example in which the information search device of FIG. 1 is incorporated in a server / client system.

FIG. 3 is a diagram showing an example in which the information search device of FIG. 1 is incorporated in an Internet connection terminal.

FIG. 4 is a flowchart showing a processing procedure when registering data such as a document to be searched.

5 is a flowchart showing a detailed procedure of a concept search registration process of step S94 of FIG.

6 is a flowchart showing the procedure of a search process by the information search device of FIG.

FIG. 7 is a flowchart showing a detailed procedure of query language analysis in step S52 of FIG. 6;

FIG. 8 is a flowchart showing a detailed procedure of phrase search in step S55 of FIG.

9 is a flowchart showing a detailed procedure of a concept search process in step S56 of FIG.

10 is a diagram showing an example of a query input screen displayed by the information search device of FIG. 1. FIG.

11 is a diagram showing an example of a search result list display screen displayed by the information search device of FIG. 1. FIG.

FIG. 12 is a diagram showing an example of phrase search data.

FIG. 13 is a flowchart showing a search procedure of the information search device according to the second embodiment of the present invention.

FIG. 14 is a diagram showing an example of a query input screen in the information search device according to the second embodiment of the present invention.

FIG. 15 is a diagram showing an example of a display screen of search results in the information search device according to the second embodiment of the present invention.

FIG. 16 is a diagram showing an input screen example when a different query is input in the information search device according to the second embodiment of the present invention.

FIG. 17 is a flowchart showing a search procedure in the information search device according to the third embodiment of the present invention.

FIG. 18 is a flowchart showing the procedure of a conventional search method.

FIG. 19 is a diagram showing an example of an operation screen in a conventional search method.

[Explanation of symbols]

1 Central processing unit 2 storage devices 3 input devices 4 display device 5 Storage medium reader

Claims (28)

[Claims] 1. A plurality of search means each having a different method, an input means for inputting a query, a query analysis means for analyzing the input query, and a plurality of search means among the plurality of search means according to a search application condition. Determining means for determining at least one or more search means to be applied to the search, and search executing means for executing a search using the analysis result of the input query by the at least one or more determined search means. An information search device, comprising: a display unit that displays a search result by the executed at least one search unit. 2. The information search device according to claim 1, wherein the search application condition is an analysis result for the input query. 3. The information search device according to claim 1, wherein the query analysis unit includes a plurality of analysis units that respectively perform different analyzes on the input query. 4. The information retrieval apparatus according to claim 3, wherein the plurality of analysis units include a morpheme analysis unit, a syntax analysis unit, and a semantic analysis unit for the input query. 5. The information search apparatus according to claim 1, wherein the plurality of search means include at least one of a full text search means, a phrase search means, and a concept search means. 6. The information retrieving apparatus according to claim 1, wherein the information retrieving apparatus is incorporated in a client of a server / client system. 7. The information search device according to claim 6, wherein the search application condition is the number of clients that are in connection with the server. 8. The information search device according to claim 6, wherein the search application condition is the number of clients connected to the server and an analysis result of the input query. 9. The information search device according to claim 1, wherein the information search device is incorporated in a terminal connectable to a communication network. 10. An input step of inputting a query, a query analysis step of analyzing the input query, and at least a method of applying a search from a plurality of search means having different methods according to search application conditions. A determination step of determining one or more search means, a search execution step of performing a search using an analysis result for the input query by the determined at least one search means, and at least the executed And a display step of displaying a search result by one or more search means on a display means. 11. The information search method according to claim 10, wherein the search application condition is an analysis result of the input query. 12. The information search method according to claim 10, wherein in the query analysis step, a plurality of analyzes are performed on the input query. 13. The information search method according to claim 12, wherein the plurality of analyzes include morphological analysis, syntactic analysis, and semantic analysis for the input query. 14. The plurality of search means are at least:
12. Any one of a full-text search means, a phrase search means, and a concept search means is included.
Information retrieval method of the description. 15. The information retrieval method according to claim 10, wherein the information retrieval method is used on a client in a server / client system. 16. The information search method according to claim 15, wherein the search application condition is the number of clients in connection with the server. 17. The information search method according to claim 15, wherein the search application condition is the number of clients connected to the server and an analysis result of the input query. 18. The information retrieval method according to claim 10, wherein the information retrieval method is used in a terminal connectable to a communication network. 19. A computer-executable program for performing information retrieval, comprising an input step of inputting a query, a query analysis step of analyzing the input query, and a method according to a search application condition. Determining step of determining at least one or more search modules to be applied to the search from a plurality of search modules different from each other, and an analysis result of the input query by the determined at least one or more search modules. A program comprising: a search execution step of executing a search used; and a display step of displaying a search result by the executed at least one or more search modules on a display means. 20. The program according to claim 19, wherein the search application condition is an analysis result of the input query. 21. The program according to claim 19, wherein in the query analysis step, a plurality of analyzes are performed on the input query. 22. The program according to claim 21, wherein the plurality of analyzes include morphological analysis, syntactic analysis, and semantic analysis for the input query. 23. The plurality of search modules are at least a full text search module, a phrase search module,
21. The program according to claim 19, comprising one of the concept search modules. 24. The program according to claim 19, which is executed on a client in a server / client system. 25. The program according to claim 24, wherein the search application condition is the number of clients connected to the server. 26. The program according to claim 24, wherein the search application condition is the number of clients connected to the server and an analysis result for the input query. 27. The program according to claim 19, which is executed on a terminal connectable to a communication network. 28. A storage medium on which the program according to claim 19 is stored so that it can be read by a computer.