JP2006313501A - Common query graph pattern generation device and method, program for generation and common subgraph retrieving device and method using the same and program for retrieval - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a common query graph pattern generation device and method and a program for generation for generating a query graph pattern for acquiring information with a structure having common implications relevant to information input by a user or preset information when retrieving information with which a query graph pattern is matched from among a large amount of data having the graph structure. <P>SOLUTION: A common query graph pattern generating device acquires a retrieval subgraph matched with a retrieval query graph pattern for retrieving a path existing among a plurality of nodes or property acquired from a graph structure database 30 based on information input from a user terminal 20 or preset information. Then, the graph structure included in the retrieval subgraph which appears several times in the combination of property names is extracted, and arbitrary node names and property names included in the extracted graph structure are made variable, so that a common query graph pattern is generated. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a common query graph pattern generation device, a generation method, a generation program, and a common subgraph search device, a search method, and a search using the same, which are used for searching information required by a user from a large amount of data. Related to the program.

  In recent years, a large amount of data exists on a computer network, and it has become difficult for a user to search for desired data. Therefore, a highly accurate search technique for easily obtaining desired data from a large amount of data has attracted attention.

  The Semantic Web is a technique used to perform such a high-precision search. This Semantic Web adds semantics (semantic information) as metadata on a Web site and creates a space where data can be processed mechanically without using human hands.

Non-Patent Document 1 describes a technique using the Semantic Web. This document uses the Semantic Web to search the necessary data by matching the graph pattern as a query from the data of the graph structure expressed by the Resource Description Framework (RDF) that defines the metadata description method. Is described. In this document, a specification for acquiring a matched portion as a subgraph is defined.
SPARQL Query Language for RDF URL: http://www.w3.org/TR/RDF-sparql-query/ gSpan: Graph-Based Substructure Pattern Mining, Proceedings of the 2002 IEEE International Conference on Data Mining (ICDM'02), IEEE Computer Society, Washington, DC, USA

  However, in the technique described in Non-Patent Document 1, when a desired subgraph is extracted from a large amount of data having a graph structure, the structure of the subgraph to be extracted must be known in advance. This is because it is not specified how to create a query graph pattern from user search history data and user profile data information, so the user must input the graph pattern as a query. Because it will not be. Therefore, even when the query graph pattern is changed according to different interests or interests depending on the user, the user himself / herself has to directly specify the graph pattern to be changed.

  Non-Patent Document 2 describes an algorithm for detecting a subgraph of a frequent portion from a graph set. However, this technique can detect a frequent subgraph structure from an enormous amount of information having a graph structure, but cannot detect it based on the structure associated with the user's interest.

  The present invention has been made in view of the above circumstances, and when searching for information matching a query graph pattern from a large amount of data having a graph structure, information input by a user or preset information is used. A common query graph pattern generation device, a generation method, a generation program, and a common subgraph search device using them, which can automatically generate a query graph pattern capable of acquiring information having a structure of related and common meanings, It is an object to provide a search method and a search program.

  In order to achieve the above object, the present invention is connected to a graph structure database in which data having a graph graph structure is stored, and is acquired from the graph structure database based on information input from a user or preset information. Search query graph pattern generating means for generating a search query graph pattern for searching for a path existing between a plurality of nodes or properties, and a search subgraph matching the generated search query graph pattern is acquired from the graph structure database A search subgraph acquisition means, a graph structure included in the acquired search subgraph, and a combination of property names in the graph structure are extracted multiple times, and an arbitrary node included in the extracted graph structure By making the name and property name variable , And a common query graph pattern generating means for generating a common query graph pattern for information related to the input information or preset information by a user searches for additional data.

  Further, in the common query graph pattern generation means, a graph structure included in the search subgraph and a combination of property names in the graph structure that appear multiple times may be extracted using an ontology.

  Further, a common query graph pattern is generated by substituting information input from a user terminal or preset information into any of the nodes that are variables of the common query graph pattern generated by the common query graph pattern generation unit. It may be.

  Moreover, the data input by the user acquired from the graph structure database by this common query graph pattern or the data of the common subgraph to which information related to the preset information is added is displayed as data for displaying in a tabular format. You may make it provide the display data conversion means to convert.

  According to the present invention, when searching for information having a matching query graph pattern from a large amount of data having a graph structure, information such as a keyword or a concept is input by the user, and the information is related to the information. In addition, since a query graph pattern that can acquire information having a structure with a common meaning can be automatically generated, desired information can be efficiently acquired.

  An embodiment of the common query graph pattern generation apparatus of the present invention will be described with reference to FIGS.

<< Configuration of Search System 1 According to One Embodiment >>
FIG. 1 is an overall view showing a configuration of a search system 1 using a search device 10 having a common query graph generation unit 13 as a common query graph pattern generation device according to an embodiment of the present invention.

  The search system 1 in the present embodiment includes a search device 10, a user terminal 20, a graph structure database 30, and an ontology database 40.

  The search device 10 is connected to the user terminal 20, the graph structure database 30, and the ontology database 40 in an accessible state.

  In addition, the search device 10 generates an input GUI generation unit 11 that generates an input GUI for allowing the user to input search content information, and generates a common query graph pattern based on information input to the input GUI. The common query graph pattern generation unit 12 that acquires information that matches the common query graph pattern from the graph structure database, the common query graph pattern storage unit 13 that stores the generated common query graph pattern, and the search result to the user An output GUI generation unit 14 for generating an output GUI for presenting the

  The graph structure database 30 stores data having a graph structure as shown in FIG. The graph structure data in this embodiment is directed directed graph data, and an arc of data (an arrow connecting nodes) is referred to as a property based on RDF specifications.

  FIG. 3 is an explanatory diagram showing how these graph structure data are generated from data managed in an existing relational database and are graphed. FIG. 3 shows a part of the data shown in FIG. 2. The document “T-041”, the author “Taro Yamada” of the document, the title of the document “Introduction to Semantic Web”, and the keyword “ Data given "Semantic Web" is expressed in RDF using XML format and graph format.

  The ontology database 40 stores ontology data for defining the meaning of words and the classification system expressed using Web Ontology Language (OWL) as shown in FIG. FIG. 4 shows that the property “rm: keyword” and the property “ms: term” are equivalent, and the property “rm: author” and the property “ms: author” are equivalent.

<< Operation of Search System 1 According to One Embodiment >>
Next, the operation of the search system 1 configured as described above will be described with reference to the sequence diagram of FIG.

  First, the input GUI generation unit 11 generates an input GUI (S1). In the input GUI generated in the present embodiment, as shown in FIG. 6, a space for inputting a keyword and a column for selecting a concept (class) are provided.

  Then, the generated input GUI is displayed on the user terminal 20, and the keyword input and concept are selected by the user (S2). In the present embodiment, “Semantic Web” is input as a keyword by the user, and “person” is selected as a concept (class). The input keyword and the selected concept data are output to the common query graph pattern generation unit 12.

  In the common query graph pattern generation unit 12, the graph structure database 30 is accessed based on the acquired keyword (S3).

  Then, a property connected to the keyword “Semantic Web” is extracted from the graph structure database 30 (S4). FIG. 7 shows an example of the graph structure data in which the extracted property arc is indicated by a bold line and the property name is underlined.

  Further, in the graph structure database 30, the property “rm: keyword” or “ms: term” is selected by the user based on the property “rm: keyword” or “ms: term” indicated by these bold lines. A search query graph that can extract a path between the instance “Person: Taro Yamada”, “Person: Ichiro Tanaka”, or “Person: Hanako Suzuki” of the class “Person: People” from the graph structure database 30. All patterns are generated (S5).

  FIG. 8 is an explanatory diagram showing the generated search query graph pattern. In this embodiment, as shown in FIG. 8, the property “rm: keyword” or “ms: term” extracted in step S4, the class “Person: person” selected by the user, and the class “Person: Two types of search queries with fixed property "rdf: type" from "Person: Taro Yamada", "Person: Ichiro Tanaka", or "Person: Hanako Suzuki" to class "Person: Person" A graph pattern has been generated. In FIG. 8, a node having a “?” Mark at the beginning of the name indicates a variable that may have an arbitrary value.

  Next, the common query graph pattern generation unit 12 accesses the graph structure database 30 based on the two types of generated search query graph patterns (S6).

  Then, a search subgraph (subgraph having a path between the variable node “? Keyword” and the variable node “? Person”) that matches the search query graph pattern is extracted in the graph structure database 30 (S7).

  FIG. 9 is an explanatory diagram showing a first search subgraph that is an example of a search subgraph extracted from the graph structure database 30. This first search subgraph shows a search subgraph in which the node “XML” is matched as the variable node “? Keyword”. At this time, only one identical node is displayed for data having the same value of the variable node “? Person”.

  Thus, the variable node “? Keyword” is the node “XML”, and the first search subgraph shown for each identical variable node “? Person” is (1) variable node “? Person” as shown in FIG. Is the node “Person: Taro Yamada”, (2) the variable node “? Person” is the node “Person: Hanako Suzuki”, (3) the variable node “? Person” is the node “Person: Jiro Nakamura” There are three types.

  Next, among these three types of first search subgraphs, two nodes (node “XML” and variable node “? Person”) are composed of two or more paths. A partial first search sub-graph in which the structure of the constructed graph and the property of the path match, and the structure of the graph constructed by the matched plurality of paths and the property of the path exist in the plurality of search results Extracted (S8).

  FIG. 10 is an explanatory diagram illustrating a state in which the properties of the partial first search subgraph extracted from the first search subgraph are indicated by bold lines. In the present embodiment, two properties “rm: keyword” are connected to the node “XML”, and the property “pj: person” and the property “rm: author” are connected to the variable node “? Person”. The partial search subgraph is extracted.

  In this partial first search subgraph, nodes other than the common structure and properties "XML", "A project", "rm: T-041", "B project", "rm: T-057", "Person The common query graph pattern generation unit 12 generates a first common query graph pattern having “: Taro Yamada” and “Person: Hanako Suzuki” as variable nodes (S9).

  The generated first common query graph pattern is transmitted from the common query graph pattern generation unit 12 to the common query graph pattern storage unit 13 and stored (S10).

  FIG. 11 is an explanatory diagram showing the generated first common query graph pattern. In the present embodiment, as shown in FIG. 11, the first common query graph pattern in which the properties “rm: keyword”, “pj: person”, and “tm: author” extracted in step S8 are fixed is generated. Has been.

  On the other hand, the second search subgraph in which the node “Semantic Web” is matched as the variable node “? Keyword” in step S7 will be described.

  FIG. 12 is an explanatory diagram showing a second search subgraph in which the node “Semantic Web” is matched as the variable node “? Keyword”. Again, for data with the same variable node “? Person” value, only one identical node is displayed.

  Thus, the second search subgraph shown for each variable node “? Person” with the variable node “? Keyword” being the node “Semantic Web” is as shown in FIG. ”Is the node“ Person: Taro Yamada ”, (2) the variable node“? Person ”is the node“ Person: Ichiro Tanaka ”, (3) the variable node“? Person ”is the node“ Person: Hanako Suzuki ” There are three types of cases.

  Next, the ontology database 40 is accessed from the common query graph pattern generation unit 12 based on the properties included in the second search subgraph (S11).

  Then, the ontology database 40 is searched for whether any of the properties included in these second search subgraphs are classified into the same meaning. Here, “keyword” and “term” included in the properties of the second search subgraph and classified in the same meaning are extracted and sent to the common query graph pattern generation unit 12 (S12).

  Next, two points (node “Semantic Web” and variable node “? Person”) are composed of two or more paths from the three types of second search subgraphs. A partial second search subgraph in which the structure of the constructed graph and the property of this path match, and the structure of the graph composed of the matched plurality of paths and the property of this path exist in the plurality of search results Extracted. At this time, the words extracted in step S14 are regarded as the same, and the partial second search subgraph is extracted (S8).

  FIG. 13 is an explanatory diagram showing a state in which the properties of the partial second search subgraph extracted from the second search subgraph are indicated by bold lines. In this embodiment, two properties “rm: keyword” or “ms: term” are connected to the node “Semantic Web”, and the property “rm: author” or the property “ms: author” is connected to the variable node “? Person”. A partial second search subgraph having a structure connected to is extracted.

  In this partial second search subgraph, nodes “semantic web”, “rm: T-041”, “ms: PF1-14”, “rm: T-053”, “rm: A second common query graph pattern having variable nodes “T-048”, “Person: Taro Yamada”, and “Person: Ichiro Tanaka” is generated in the common query graph pattern generation unit 12 (S9).

  The generated second common query graph pattern is also transmitted from the common query graph pattern generation unit 12 to the common query graph pattern storage unit 13 and stored (S10).

  FIG. 14 is an explanatory diagram showing the generated second common query graph pattern. In this embodiment, as shown in FIG. 14, the properties “rm: keyword”, “rm: keyword” or “ms: term”, “rm: author”, “rm: author” or “ A second common query graph pattern in which “ms: author” is fixed is generated.

  Next, as shown in FIG. 15, the keyword “Semantic Web” input by the user is substituted into the variable node “? Keyword” of the first query graph pattern generated in step S9, and this first query graph pattern is Based on this, the common query graph pattern generation unit 12 accesses the graph structure database 30 (S13).

  Then, a first common subgraph that matches the first query graph pattern in which the keyword “Semantic Web” is substituted in the graph structure database 30 is extracted (S14).

  FIG. 16 is an explanatory diagram showing the first common sub-graph extracted from the graph structure database 30. In the present embodiment, there is only one extracted first common subgraph, which is the class “people” found in technologies (here “XML”) other than the keyword “Semantic Web” input by the user. This indicates that there is only one piece of strongly related information that exists in common with the class “technology” for the keyword “Semantic Web”.

  Next, as shown in FIG. 17, the keyword “Semantic Web” input by the user is substituted into the variable node “? Keyword” of the second query graph pattern generated in step S9, and this second query graph pattern is substituted. Based on this, the common query graph pattern generation unit 12 accesses the graph structure database 30 (S13).

  Then, a second common subgraph that matches the second query graph pattern in which the keyword “Semantic Web” is substituted in the graph structure database 30 is extracted (S14).

  In this embodiment, there are two extracted second common subgraphs. This is because the strongly related information that exists between the class “person” and the class “technology” is the keyword “Semantic Web”. "Taro Yamada" and "Ichiro Tanaka" shown in the node "Person:" in these two cases have similar information regarding the keyword "Semantic Web" Yes.

  The two extracted second common subgraphs are merged in the common query graph pattern generation unit 12 so that the same node is represented as one node (S15).

  FIG. 18 is an explanatory diagram showing a state where two second common subgraphs are merged.

  Further, the merged second common subgraph is generated in a tabular output GUI as shown in FIG. 19 in the output GUI generation unit 14 (S16) and displayed on the user terminal 20 (S17). At this time, the document whose title is known from the data of the graph structure database is also displayed. In FIG. 19, the title “Introduction to Semantic Web” is displayed together with the document “rm: T-041”.

  According to the above embodiment, when searching for information that matches the query graph pattern from a large amount of data having a graph structure, the meaning is related to the keyword “Semantic Web” and the concept “people” input by the user. In general, information having a common structure can be automatically acquired and provided in a format that is easy for the user to see.

  Further, when the common query graph pattern is accumulated in step 11, even when data is added to the graph structure database 30, if the graph structure database 30 is searched again based on the accumulated common query graph pattern. Information including the added data can be acquired.

  In this embodiment, when a search query graph pattern is generated in step S5, a node between two nodes generates a search query graph pattern for searching for one search subquery. Alternatively, it is possible to generate a search query graph pattern in which two or more nodes exist. It is also possible to generate a search query graph pattern by configuring two points with only nodes restricted by properties connected to keywords or nodes restricted by classes. Furthermore, it is possible to generate a plurality of search query graph patterns according to the direction of the property arrow.

  Further, in the present embodiment, when extracting the partial first search subgraph in step S8, the condition is that the two nodes are composed of two or more paths, but the present invention is not limited to this. Instead, the number of paths can be made variable. At that time, it is possible to change the condition of how many identical structures are extracted in the search result.

  In this embodiment, the common query graph pattern is generated by making the node included in the partial first search subgraph a variable in step S9. However, the present invention is not limited to this method. It is also possible to generate a common query graph pattern.

1 is an overall view showing a configuration of a search system 1 in which a common query graph pattern generation device according to an embodiment of the present invention is used. It is explanatory drawing which shows the data in the graph structure database connected to the common query graph pattern generation apparatus by one Embodiment of this invention. FIG. 2 is a portion of data in a graph structure database connected to a common query graph pattern generation device according to an embodiment of the present invention, and the data in the original relational database and the RDF using the XML format and the graph format. It is explanatory drawing which shows the state expressed by. It is explanatory drawing which shows a part of data in the ontology database connected to the common query graph pattern generation apparatus by one Embodiment of this invention. It is a sequence diagram which shows operation | movement of the search system in which the common query graph pattern generation apparatus by one Embodiment of this invention is used. It is explanatory drawing which shows the input GUI input into the common query graph pattern generation apparatus by one Embodiment of this invention. It is explanatory drawing which shows the graph structure data which showed the property connected with the input keyword with the thick line acquired with the common query graph pattern generation apparatus by one Embodiment of this invention. It is explanatory drawing which shows the search query graph pattern produced | generated with the common query graph pattern production | generation apparatus by one Embodiment of this invention. It is explanatory drawing which shows the example of the search subgraph matched with the search query graph pattern acquired with the common query graph pattern generation apparatus by one Embodiment of this invention. It is explanatory drawing which shows the state which showed the structure and property which are common in the search subgraph acquired with the common query graph pattern generation apparatus by one Embodiment of this invention with the thick line. It is explanatory drawing which shows an example of the common query graph pattern produced | generated by the common query graph pattern production | generation apparatus by one Embodiment of this invention. It is explanatory drawing which shows the example of the search subgraph matched with the search query graph pattern acquired with the common query graph pattern generation apparatus by one Embodiment of this invention. It is explanatory drawing which shows the state which showed the structure and property which are common in the search subgraph acquired with the common query graph pattern generation apparatus by one Embodiment of this invention with the thick line. It is explanatory drawing which shows an example of the common query graph pattern produced | generated by the common query graph pattern production | generation apparatus by one Embodiment of this invention. It is explanatory drawing which shows an example of the state which substituted the keyword input by the user into the common query graph pattern produced | generated with the common query graph pattern production | generation apparatus by one Embodiment of this invention. It is explanatory drawing which shows an example of the common subgraph matched with the common query graph pattern acquired with the common query graph pattern generation apparatus by one Embodiment of this invention. It is explanatory drawing which shows an example of the state which substituted the keyword input by the user into the common query graph pattern produced | generated with the common query graph pattern production | generation apparatus by one Embodiment of this invention. It is explanatory drawing which shows an example of the common subgraph matched with the common query graph pattern acquired with the common query graph pattern generation apparatus by one Embodiment of this invention. It is explanatory drawing which shows the data of the table format displayed on the user terminal connected to the common query graph pattern generation apparatus by one Embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Search system 10 ... Search apparatus 11 ... Input GUI production | generation part 12 ... Common query graph pattern production | generation part 13 ... Common query graph pattern storage part 14 ... Output GUI production | generation part 20 ... User terminal 30 ... Graph structure database 40 ... Ontology The database

Claims (21)

Connected to a graph structure database that stores data with a graph structure,
Search query graph pattern generation for generating a search query graph pattern for searching a path existing between a plurality of nodes or properties acquired from the graph structure database based on information input from a user or preset information Means,
Search subgraph acquisition means for acquiring from the graph structure database a search subgraph that matches the generated search query graph pattern;
The graph structure included in the retrieved search subgraph and the combinations of property names in this graph structure that appear multiple times are extracted, and any node name and property name included in this extracted graph structure are variables A common query graph pattern generating means for generating a common query graph pattern for searching for data added with information input by the user or information related to preset information;
A common query graph pattern generation device comprising: The common query graph pattern generation means extracts, using an ontology, a graph structure included in the search subgraph and a combination of property names in the graph structure that appear multiple times. The common query graph pattern generation device according to 1. Generating a common query graph pattern obtained by substituting information input from the user or preset information into any of the nodes that are variables of the common query graph pattern generated by the common query graph pattern generation unit. The common query graph pattern generation device according to claim 1, wherein the common query graph pattern generation device is a feature of the common query graph pattern generation device. Search query graph for searching paths existing between multiple nodes or properties acquired from graph structure database that stores data with graph structure based on information input by user or preset information A search query graph pattern generation step for generating a pattern;
A search subgraph acquisition step of acquiring from the graph structure database a search subgraph that matches the generated search query graph pattern;
The graph structure included in the retrieved search subgraph and the combination of property names in this graph structure that occur multiple times are extracted, and any node name and property name included in this extracted graph structure are variable A common query graph pattern generating step for generating a common query graph pattern for searching for data added with information input by the user or information related to preset information;
A common query graph pattern generation method comprising: The ontology is used to extract a graph structure included in the search subgraph and a combination of property names in the graph structure that appear multiple times in the common query graph pattern generation step. 5. The common query graph pattern generation method according to 4. Generating a common query graph pattern by substituting information input from the user or preset information into any of the nodes that are variables of the common query graph pattern generated in the common query graph pattern generation step. 6. The common query graph pattern generation method according to claim 4, wherein the common query graph pattern is generated. Search query graph for searching paths existing between multiple nodes or properties acquired from graph structure database that stores data with graph structure based on information input by user or preset information Search query graph pattern generation function to generate patterns,
A search subgraph acquisition function for acquiring a search subgraph that matches the generated search query graph pattern from the graph structure database;
The graph structure included in the retrieved search subgraph and the combination of property names in this graph structure that occur multiple times are extracted, and any node name and property name included in this extracted graph structure are variable A common query graph pattern generation function for generating a common query graph pattern for searching for data added with information input by the user or information related to preset information;
Common query graph pattern generation program for causing a computer to realize The common query graph pattern generation function extracts an occurrence of a plurality of combinations of graph structures included in the search subgraph and property names in the graph structure using an ontology. The common query graph pattern generation program according to claim 7. Generating a common query graph pattern by substituting information input from the user or preset information into any of the nodes that are variables of the common query graph pattern generated by the common query graph pattern generation function. 9. The common query graph pattern generation program according to claim 7, wherein the common query graph pattern generation program is provided. Connected to a graph structure database that stores data with a graph structure,
Search query graph pattern generation for generating a search query graph pattern for searching a path existing between a plurality of nodes or properties acquired from the graph structure database based on information input from a user or preset information Means,
Search subgraph acquisition means for acquiring from the graph structure database a search subgraph that matches the generated search query graph pattern;
The graph structure included in the retrieved search subgraph and the combination of property names in this graph structure that occur multiple times are extracted, and any node name and property name included in this extracted graph structure are variable A common query graph pattern generating means for generating a common query graph pattern for searching for data added with information input by the user or information related to preset information;
A common subgraph acquisition means for acquiring a common subgraph that matches the generated common query graph pattern from the graph structure database;
A common subgraph search device comprising: The common query graph pattern generation means extracts, using an ontology, a graph structure included in the search subgraph and a combination of property names in the graph structure that appear multiple times. The common subgraph search device according to 10. Generating a common query graph pattern obtained by substituting information input from the user or preset information into any of the nodes that are variables of the common query graph pattern generated by the common query graph pattern generation unit. The common subgraph search device according to claim 10, wherein the common subgraph search device is characterized in that: The common subgraph search device according to any one of claims 10 to 12, further comprising display data conversion means for converting the data of the common subgraph into data for displaying in tabular form. Search query graph for searching paths existing between multiple nodes or properties acquired from graph structure database that stores data with graph structure based on information input by user or preset information A search query graph pattern generation step for generating a pattern;
A search subgraph acquisition step of acquiring from the graph structure database a search subgraph that matches the generated search query graph pattern;
The graph structure included in the retrieved search subgraph and the combination of property names in this graph structure that occur multiple times are extracted, and any node name and property name included in this extracted graph structure are variable A common query graph pattern generating step for generating a common query graph pattern for searching for data added with information input by the user or information related to preset information;
A common subgraph acquisition step of acquiring from the graph structure database a common subgraph that matches the generated common query graph pattern;
A common subgraph search method comprising: The ontology is used to extract a graph structure included in the search subgraph and a combination of property names in the graph structure that appear multiple times in the common query graph pattern generation step. 14. The common subgraph search method according to 14. Generating a common query graph pattern by substituting information input from the user or preset information into any of the nodes that are variables of the common query graph pattern generated in the common query graph pattern generation step. The common subgraph search method according to claim 14, wherein the common subgraph search method is characterized in that: The common subgraph search method according to any one of claims 14 to 16, further comprising a display data conversion step of converting the data of the extended subgraph into data for display in a tabular format. Search query graph for searching paths existing between multiple nodes or properties acquired from graph structure database that stores data with graph structure based on information input by user or preset information Search query graph pattern generation function to generate patterns,
A search subgraph acquisition function for acquiring a search subgraph that matches the generated search query graph pattern from the graph structure database;
The graph structure included in the retrieved search subgraph and the combination of property names in this graph structure that occur multiple times are extracted, and any node name and property name included in this extracted graph structure are variable A common query graph pattern generating function for generating a common query graph pattern for searching for data added with information input by the user or information related to preset information;
A common subgraph acquisition function for acquiring a common subgraph that matches the generated common query graph pattern from the graph structure database;
Common subgraph search program for realizing on a computer. The common query graph pattern generation function extracts an occurrence of a combination of a graph structure included in the search subgraph and a property name in the graph structure a plurality of times using an ontology. The common subgraph search program according to claim 18. Generating a common query graph pattern by substituting information input from the user or preset information into any of the nodes that are variables of the common query graph pattern generated by the common query graph pattern generation function. 20. The common subgraph search program according to claim 18 or 19, characterized in that: The common subgraph search program according to any one of claims 18 to 20, further comprising display data conversion means for converting the data of the extended subgraph into data for display in a tabular format.

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