KEYWORD RECOMMENDATION PROGRAM, KEYWORD RECOMMENDATION METHOD, AND INFORMATION PROCESSING APPARATUS

Abstract

To provide a program, a method, and an apparatus which can recommend a keyword in creating an introductory text.SOLUTION: In the method, a first keyword extracted from a first sentence of a first user is accepted, and a candidate keyword recommended to be used instead of or along with the first keyword is specified from second keywords extracted from a second sentence of another user on the basis of data defining semantic inclusive relations between a plurality of keywords and is transmitted to a terminal of the first user.SELECTED DRAWING: Figure 9

Description

[Technical field]

[0001] The present invention relates to a keyword recommendation program, a keyword recommendation method, and an information processing device. [Background technology]

[0002] In recent years, meetups have been held on the Internet as events aimed at meeting and interacting with people who share the same goals. As the number of participants in meetups has increased and the scale of these events has grown, it has become possible to interact with people you have never met before.

[0003] However, when the number of participants is large, the number of introductions of participants also becomes huge, making it difficult to determine which participants to meet. It is possible to connect participants based on the words contained in the introductions created by each meetup participant.

[0004] There is a known technique for creating software deliverables with a unified task granularity by using the same subject vocabulary, action vocabulary, and parameter vocabulary contained in software deliverables by different creators. In addition, a technique has been proposed for realizing information retrieval that matches the searcher's intention by using keywords that indicate vague relationships or thoughts unique to the searcher. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2008-112246 A [Patent Document 2] JP 2007-018350 A Summary of the Invention [Problem to be solved by the invention]

[0006] The introductions of meetup participants vary in the words and expressions used. Some introductions are written using specific words, while others are written abstractly using general words.

[0007] If the level of detail of the words used in the introduction varies, it is difficult to accurately match participants with the same purpose. This is because many participants are not good at writing introductions.

[0008] Thus, one aspect is to create appropriate documentation. [Means for solving the problem]

[0009] According to one embodiment, a first user The first user's A keyword recommendation program is provided that causes a computer to perform a process of extracting a first keyword from a first sentence, identifying a candidate keyword that more specifically expresses an object represented by the first keyword from second keywords extracted from second sentences of other users based on data that defines a semantic inclusion relationship between multiple keywords, instead of the first keyword, and transmitting the candidate keyword to a terminal of the first user. Effect of the Invention

[0010] Able to create appropriate documentation. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 illustrates an example of a network configuration of a system according to an embodiment of the present invention. [Diagram 2] FIG. 2 illustrates an example of a hardware configuration according to the present embodiment. [Diagram 3] FIG. 2 is a diagram illustrating an example of a functional configuration of an information processing device according to the present embodiment. [Figure 4] FIG. 2 is a sequence diagram for explaining an overview of processing in the system according to the present embodiment. [Diagram 5] FIG. 11 is a diagram showing a time series of keyword detection states. [Figure 6] FIG. 11 is a diagram illustrating an example of ontology information. [Figure 7] FIG. 13 is a diagram illustrating an example of updating a keyword DB. [Figure 8] FIG. 13 is a diagram showing an example of an input screen for inputting an introduction message and displayed on the terminal in the present embodiment. [Figure 9] FIG. 4 is a diagram showing a specific example of input on a terminal in the present embodiment. [Figure 10] 11 is a flowchart illustrating an overall keyword recommendation process. [Figure 11] FIG. 11 is a flowchart illustrating an extraction process. [Figure 12] FIG. 11 is a flowchart for explaining a determination process. [Figure 13] FIG. 11 is a flowchart illustrating a recommendation process. [Figure 14] FIG. 11 is a sequence diagram when the number of users is increased midway in the system according to the embodiment. [Figure 15] 15 is a diagram showing an example of data transition in a keyword DB in the case of the operation example of FIG. 14. [Figure 16] FIG. 13 is a diagram showing an example of a screen when creation support information is provided by push notification. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In this embodiment, among the multiple words included in the introduction, a word used for matching is called a keyword. Also, the level of detail expressing the object represented by the keyword is called granularity. Also, the participants of the meetup are called users. In this embodiment, a keyword recommendation process is disclosed below that recommends keywords when participants write introductions so that the granularity of keywords is unified in the same category. The keyword recommendation process in this embodiment can be realized by an information processing device in a system such as that shown in FIG. 1.

[0013] Fig. 1 is a diagram showing an example of a network configuration of a system in this embodiment. The system 1000 shown in Fig. 1 includes an information processing device 100 and a plurality of terminals 3. The information processing device 100 is a computer that provides a meetup service over the Internet 2 and executes a program that realizes the keyword recommendation process in this embodiment.

[0014] The multiple terminals 3 are terminals used by users 1 who participate in the meetup by connecting to the information processing device 100 via the Internet 2. The terminals 3 may be mobile terminals or standalone computers.

[0015] In the system 1000, after the terminal 3 is connected to the information processing device 100, when the user 1 inputs an introduction 3a to the terminal 3, the introduction 3a being input is transmitted from time to time to the information processing device 100. An example of the introduction 3a is a sentence (self-introduction) in which the user 1 introduces himself / herself, but this embodiment is not limited to this example.

[0016] In order to standardize the granularity of keywords contained in the introductions 3 sent from each terminal 3, the information processing device 100 transmits creation support information 3b to the terminal 3 including more detailed keyword candidates to replace the input words.

[0017] The user 1 of the terminal 3 edits the introduction 3a into a sentence that includes the candidate keywords displayed on the screen during input. By the user 1 editing the introduction 3a using the keywords displayed on the screen, the granularity of the keywords used for matching between the introductions 3a of the user 1 and those of other users 1 can be roughly unified.

[0018] The creation support information 3b transmitted from the information processing device 100 to the terminal 3 includes one or more keywords, a message encouraging the use of the keywords, and information indicating words recommended for use as specific expressions in the introduction text 3a being entered or their positions within the introduction text 3a.

[0019] Candidates based on the creation support information 3b are displayed on the screen of the terminal 3 while the introduction 3a is being input, thereby prompting the user 1 to input specific content. The method of notifying the candidates is not limited to displaying them on the screen while inputting. The terminal 3 may have a mechanism for receiving the creation support information 3b by push notification. In this case, when the user 1 selects the notification on the terminal 3, the input screen for the introduction 3a is displayed, and the introduction 3a input by the user 1, the keywords, and the message are displayed.

[0020] Fig. 2 is a diagram showing an example of a hardware configuration in this embodiment. In Fig. 2, the information processing device 100 is a computer having a CPU 11, a main storage device 12, an auxiliary storage device 13, an input device 14, a display device 15, a communication I / F 17, and a drive device 18, and is connected to a bus B1. The main storage device 12, the auxiliary storage device 13, and an external storage device accessible by the information processing device 100 correspond to a storage unit 130 in a functional block diagram (Fig. 3) described later.

[0021] The CPU 11 corresponds to a processor that controls the information processing device 100, and executes programs stored in the storage unit 130 to realize various processes according to the present embodiment described below. The input device 14 is operated by a user and inputs data in response to the operation, and the display device 15 displays various screens as a user interface. The communication I / F 17 controls communication with external devices.

[0022] The keyword recommendation program according to this embodiment stored in a storage medium 19 (for example, a CD-ROM (Compact Disc Read-Only Memory) or the like) is installed in the storage unit 130 via the drive device 18 and becomes executable by the CPU 11.

[0023] The storage medium 19 for storing the program according to the present embodiment is not limited to a CD-ROM, but may be one or more non-transitory, tangible media having a structure that can be read by a computer. As a computer-readable storage medium, in addition to a CD-ROM, a DVD (Digital Versatile Disk), a portable recording medium such as a USB memory, or a semiconductor memory such as a flash memory may be used.

[0024] 2, terminal 3 is an information processing terminal such as a tablet type or a mobile phone controlled by a computer. Terminal 3 has a CPU 311, a main memory device 312, a user I / F 316, a communication I / F 317, and a drive device 318, and is connected to bus B3.

[0025] The CPU 311 corresponds to a processor that controls the terminal 3, and executes programs stored in the main memory device 312 or the like to realize various processes according to this embodiment described below. The user I / F 316 displays various types of information required under the control of the CPU 311, and is a touch panel or the like that allows the user to input operations. Communication via the communication I / F 317 is not limited to being wireless or wired.

[0026] The drive device 318 provides an interface between a storage medium 319 (e.g., a Secure Digital (SD) memory card, etc.) set in the drive device 318 and the terminal 3. The storage medium 319 may be one or more non-transitory, tangible media having a structure that can be read by a computer.

[0027] The terminal 3 may be an information processing terminal of a desktop type, a notebook type, a laptop type, or the like, and the hardware configuration thereof is similar to that of FIG. 2, so a description thereof will be omitted.

[0028] Fig. 3 is a diagram showing an example of a functional configuration of an information processing device in this embodiment. Fig. 3 shows a processing unit according to this embodiment, and omits other processing units. As an example, a processing unit that performs a meetup service is omitted.

[0029] The information processing device 100 in Fig. 3 has a keyword recommendation unit 40. In response to receiving an introduction 3a being input to a terminal 3 connected via the Internet 2, the keyword recommendation unit 40 generates creation support information 3b and transmits it to the terminal 3 when the introduction 3a contains coarse-grained (highly abstract) words. The keyword recommendation unit 40 further has an extraction unit 41, a determination unit 42, and a recommendation unit 43. Each of the processing units 41, 42, and 43 is realized by a process that a program installed in the information processing device 100 causes the CPU 11 of the information processing device 100 to execute.

[0030] The storage unit 130 also stores an introduction DB 51, a keyword DB 52, ontology information 53, and the like.

[0031] In response to receiving the introduction 3a for each user 1 of the terminal 3, the extraction unit 41 stores the introduction 3a in the introduction DB 51 and extracts keywords 3d from the introduction 3a. The extraction unit 41 stores the extracted keywords 3d and a user ID that identifies the user 1 in the keyword DB 52. When extracting the keywords 3d, the extraction unit 41 extracts the keywords 3d from the introduction 3a being input by the user 1 at any time. When storing the keywords 3d in the keyword DB 52, the extraction unit 41 adds new keywords 3d that have not yet been stored to the keyword DB 52 so as not to duplicate the keywords 3d.

[0032] In response to the addition of the keyword 3d to the keyword DB 52, the determination unit 42 determines the granularity relationship between the keyword 3d associated with the other user 1 and stored in the keyword DB 52, based on the ontology information 53. The information is not limited to the ontology information 53, and may be any data that specifies a semantic inclusion relationship.

[0033] When the recommendation unit 43 detects the addition of the keyword 3d to the keyword DB 52, it refers to the ontology information 53 and acquires a keyword 3d' associated with another user ID from the keyword DB 52 among words with finer granularity than the added keyword 3d. The recommendation unit 43 generates creation support information 3b using the acquired keyword 3d' and transmits the generated creation support information 3b to the user terminal 3 used by the user 1 having the user ID associated with the added keyword 3d.

[0034] In this embodiment, among words with finer granularity than the keyword 3d added to the keyword DB 52, keywords 3d' included in the introduction text 3a of another user 1 are displayed as candidates on the terminal 3 of the user 1 who entered the coarser granularity keyword 3d.

[0035] When words with finer granularity than the keyword 3d obtained by referring to the ontology information 53 are displayed as candidates on the terminal 3 of the user 1 who has entered the coarse keyword 3d, the number of candidates may be too large. The user 1 feels that it is time-consuming to determine words to use from too many candidates and create a document, and tends not to be specific about the keyword 3d in the introduction 3a that he is entering.

[0036] Fig. 4 is a sequence diagram for explaining an outline of the processing in the system in this embodiment. In Fig. 4, a case will be explained in which users u1, u2, and u3 connect to the information processing device 100 using their respective terminals 3 and create an introduction 3a for participating in a meetup. In this embodiment, the number of users 1 is not limited to three.

[0037] Each of the users u1, u2, and u3 uses the terminal 3 to input a self-introduction including the purpose of participating in the meetup or categories of interest, on an input screen provided by the information processing device 100 (step S101).

[0038] In the information processing device 100, when the extraction unit 41 receives the introductions 3a from the users u1 to u3, the extraction unit 41 extracts keywords 3d from each introduction 3a (step S102).

[0039] When the determination unit 42 detects the addition of a keyword 3d to the keyword DB 52 at a fixed interval using a timer or the like, it refers to the ontology information 53 and determines the granularity of the detected keyword 3d (step S103). When it is determined that the granularity of the detected keyword 3d is coarse, the determination unit 42 notifies the recommendation unit 43 of the determined keyword 3d' and the user ID of the user u1. It is assumed that the keyword 3d included in the introduction 3a of the user u1 is detected and the granularity is determined.

[0040] The recommendation unit 43 generates creation support information 3b and transmits it to the terminal 3 of the user u1 (step S104). The recommendation unit 43 extracts words (hereinafter, referred to as refined words) that are finer than the granularity of the keyword 3d from the ontology information 53. Then, the recommendation unit 43 determines, from the refined words obtained by extraction, the keyword 3d' obtained from the introduction text 3a of other users u2 and u3 that exists in the keyword DB 52, as a recommended candidate. The recommendation unit 43 generates creation support information 3b including information such as the keyword 3d', the message, and the position of the keyword 3d in the introduction text 3a of the user u1, and transmits the generated creation support information 3b to the terminal 3 of the user u1.

[0041] The user u1 refers to the keywords 3d' and the message displayed on the terminal 3 based on the creation support information 3b and edits the introduction 3a being input (step S105). The edited introduction 3a is transmitted to the information processing device 100, and the same process as described above is repeated until the user u1 closes the input screen.

[0042] 5 is a diagram showing a time series of keyword detection states. In FIG. 5, at time T1, keywords kw1, kw2, and kw3 are detected from the introduction 3a of user u1 and stored in the keyword DB 52.

[0043] After that, at time T2, keywords kw1a and kw1b are detected from the introduction 3a of user u2. At almost the same time, keyword kw3b is detected from the introduction 3a of user u3. At time T3, a little after time T2, keyword kw3ca is detected from the introduction 3a of user u3.

[0044] In this example, keywords kw1, kw2, and kw3 are the most abstract keywords 3d, and the more letters in the subscript, the more specific the keywords 3d become. As an example, keywords kw1a and kw1b are vocabulary that more specifically expresses the meaning of keyword kw1. Keyword kw3b is vocabulary that more specifically expresses the meaning of keyword kw3. Keyword kw3ca is vocabulary that more specifically expresses the meaning of keyword kw3. Such semantic relationships between keywords 3d are represented by ontology information 53 as shown in FIG. 6.

[0045] Fig. 6 is a diagram showing an example of ontology information. In Fig. 6, ontology information 53 is represented as a tree structure with a base as the root, and various abstract vocabulary branches from the base. That is, it branches from the base to keywords kw1, kw2, kw3, etc. located at the first level.

[0046] In the second hierarchy, keyword kw1 located in the first hierarchy branches into keywords kw1a, kw1b, and kw1c. Keyword kw2 located in the first hierarchy branches into keywords kw2a, kw2b, and kw2c. Keyword kw3 located in the first hierarchy branches into keywords kw3a, kw3b, and kw3c.

[0047] At the third level, keyword kw3a at the second level is refined to keyword kw3aa. At the fourth level, keyword kw3aa at the third level is refined to keyword kw3ab, and at the fifth level, keyword kw3ac is refined.

[0048] Similarly, the keyword kw3c located at the second level is refined to a keyword kw3ca at the third level, then to a keyword kw3cb at the fourth level, and then to a keyword kw3cc at the fifth level. Such ontology information 53 is referred to by the recommendation unit 43.

[0049] Fig. 7 is a diagram showing an example of updating the keyword DB. In Fig. 7, the left side shows an example of data in the keyword DB 52 when the keywords are extracted in Fig. 5. The keywords kw1, kw2, and kw3 extracted from the introduction 3a of the user u1 are stored in association with the user ID "u1". The keywords kw1a and kw1b extracted from the introduction 3a of the user u2 are also stored in association with the user ID "u2". Furthermore, the keywords kw3b and kw3ca extracted from the introduction 3a of the user u3 are also stored in association with the user ID "u2".

[0050] By referring to the ontology information 53, it is determined that the granularity of the keyword kw1 of the user u1 is coarser than the keywords kw1a and kw1b of the user u2, and that the granularity of meaning is not uniform between the users. The keyword kw1 of the user u1 is notified to the recommendation unit 43 from the determination unit 42.

[0051] Thereafter, the user u1 adds a more specific sentence based on the creation support information 3b generated by the recommendation unit 43, thereby updating the keyword DB 52. As a result of the update, a record 5a indicating the keyword kw1a associated with the user ID "u1" is added to the keyword DB 52.

[0052] Next, an example of a screen operated by the user 1 will be described with reference to Fig. 8 and Fig. 9. In Fig. 8 and Fig. 9, a case where the user u1 in Fig. 5 is inputting the introduction 3a will be described as an example.

[0053] Fig. 8 is a diagram showing an example of an input screen for inputting an introduction displayed on a terminal in this embodiment. In Fig. 8, on the screen where user u1 inputs "I am interested in kw1. I am also interested in kw2 and kw3", a message 4m such as "Why don't you make kw1 more specific so that other people will be more interested in it?" is displayed. In the message 4m, the keywords kw1a and kw1b correspond to the keyword 3d' selected by the recommendation unit 43.

[0054] The message 4m area also points to the relevant keyword kw1 in the introduction 3a, and prompts the user to specifically write the meaning of the keyword kw1. In the message 4, the keywords kw1a and kw1b are shown as selectable. If the user u1 selects the keyword kw1a, a fixed phrase 7a such as "Specifically, regarding kw1a, ~~~" is inserted. The user u1 completes the "~~~" part. This operation adds a record of the keyword "kw1a" associated with the user ID "u1" to the keyword DB 52.

[0055] FIG. 9 is a diagram showing a specific input example at a terminal in this embodiment. FIG. 9 illustrates an input example of user 1. When user 1 inputs "I'm interested in vegetables. I'm also interested in meat and fish" into the input screen of terminal 3, a message 4m such as "Why don't you specify vegetables to get other people more interested?" from the recommendation unit 43 is displayed. The message 4m points to "vegetables" in the input sentence. In addition, the message 4m displays "tomato" and "onion" as keywords 3d' selected by the recommendation unit 43 so that the user 1 can select them.

[0056] When user 1 selects "tomatoes", a standard text 7b such as "Specifically, about tomatoes, ~~~" is inserted immediately after the sentence including "vegetables". User 1 replaces the "~~~" part in this inserted standard text with a sentence related to "tomatoes", such as "I grow cherry tomatoes". In this way, standard text 7b is input as user 1's text 7c. The completed introduction text 3a is created with the same level of granularity for other users, so matching can be performed accurately.

[0057] In the above description, the fixed phrase 7b is inserted to allow the user 1 to input specific content incidentally, but the user 1 can also appropriately replace the word "vegetables" that the message 4m is pointing to with "tomatoes."

[0058] Next, each processing unit will be described with reference to a flowchart.

[0059] Fig. 10 is a flow chart for explaining the entire keyword recommendation process. In Fig. 10, when the keyword recommendation unit 40 receives the introduction 3a (step S201), the extraction unit 41 performs an extraction process for extracting keywords 3d from the introduction 3a (step S202). The extracted keywords 3d are added to the keyword DB 52 as long as they are not duplicated in the keyword DB 52. If there is no new keyword 3d to be added, the subsequent steps S203 to S205 are omitted, the keyword recommendation process is terminated, and the reception of the next introduction 3a is awaited.

[0060] In response to the addition of the keyword 3d to the keyword DB 52, the determination unit 42 performs a determination process to determine the granularity of the added keyword 3d (step S203). The determination unit 42 refers to the ontology information 53 and determines whether the keyword 3d is coarser than the words included in the introduction 3a of the other user 1 (step S203). If the determination unit 42 does not determine that the keyword 3d is coarse (YES in step S203), the keyword recommendation unit 40 ends this keyword recommendation process and waits for the reception of the next introduction 3a.

[0061] If the determining unit 42 determines that the granularity is coarse (YES in step S203), the recommending unit 43 performs a recommendation process for recommending a candidate keyword 3d' (step S205). Creation support information 3b is generated and transmitted to the terminal 3. Upon completion of the recommendation process, the keyword recommendation unit 40 ends this keyword recommendation process and waits for reception of the next review 3a.

[0062] Fig. 11 is a flow chart for explaining the extraction process. In Fig. 11, the extraction unit 41 judges whether the received introduction 3a is a new introduction or an update of the introduction 3a (step S211). If the received introduction 3a is neither a new introduction nor an update of the introduction 3a (NO in step S211), the extraction unit 41 ends this extraction process.

[0063] On the other hand, if the received review 3a is a new review or an update to the review 3a (YES in step S211), the extraction unit 41 associates the received review 3a with the user ID, stores it in the review DB 51, and updates the review DB 51 (step S212).

[0064] Then, the extraction unit 41 extracts the keyword 3d from the received review 3a, and if there is no overlap, adds a new record in which the extracted keyword 3d is recorded in association with the user ID to update the keyword DB 52 (step S214). After that, the extraction unit 41 ends the extraction process and waits for the next review to be received.

[0065] Fig. 12 is a flow chart for explaining the determination process. In Fig. 12, the determination unit 42 determines whether the keyword DB 52 has been updated at regular intervals (step S211). If the keyword DB 52 has not been updated (NO in step S211), the determination unit 42 repeats step S211 at regular intervals.

[0066] If the keyword DB 52 has been updated (YES in step S211), the determination unit 42 refers to the ontology information 53 and compares the granularity of the added keyword 3d (step S221).

[0067] Then, the determination unit 42 determines whether the added keyword 3d is a target keyword for elaboration (step S223). The determination unit 42 determines whether any of the words in a lower layer than the position of the added keyword 3d in the ontology information 53 matches the keyword 3d extracted from the introduction text 3a of another user 1 in the keyword DB 52. If a matching keyword 3d exists, the determination unit 42 determines that the added keyword 3d is a target keyword for elaboration. If it is determined that the added keyword 3d is not a target keyword for elaboration (NO in step S223), the determination unit 42 returns to step S221 and repeats the same process described above.

[0068] When it is determined that the keyword is a target keyword for elaboration (YES in step S223), the determination unit 42 notifies the recommendation unit 43 that there is a keyword to be elaboration (step S224). The information notified to the recommendation unit 43 includes at least the keyword to be elaboration and the user ID.

[0069] Fig. 13 is a flow chart for explaining the recommendation process. In Fig. 13, the recommendation unit 43 judges at regular intervals whether or not a notification has been received from the judgment unit 42 (step S231). If no notification has been received (NO in step S231), the recommendation unit 43 repeats step S231.

[0070] When the notification is received (YES in step S231), the recommendation unit 43 refers to the ontology information 53 and identifies candidate keywords to be recommended for use instead of or incidental use in place of the target keyword specified in the notification (step S232). The recommendation unit 43 refers to the ontology information 53 to identify the hierarchy in which the target keyword for refinement is located, and acquires a word if there is a hierarchy deeper than the identified hierarchy. The recommendation unit 43 further acquires from the keyword DB 52 a keyword 3d' included in the introduction 3a of another user 1 that matches any of the acquired words.

[0071] Then, the recommendation unit 43 creates creation support information 3b including the identified candidate keyword 3d' and transmits it to the terminal 3 (step S233). The creation support information 3b further includes position information of the keyword to be detailed or the keyword to be detailed within the introduction 3a, a message, etc. The position information may be the number of characters from the first character of the introduction 3a to the keyword to be detailed. The creation support information 3b may further include a fixed phrase.

[0072] Next, a case where, after the keywords 3d are extracted from the introductions 3a of the three users u1 to u3 as shown in FIG. 4, an introduction 3a from a user u4 is further received will be described with reference to FIGS.

[0073] Fig. 14 is a sequence diagram when the number of users is increased in the system in this embodiment. Fig. 14 shows a sequence when a user u4 joins after the keywords 3d are extracted from the introductions 3a of the three users u1 to u3.

[0074] After extracting keywords 3d from the introduction text 3a of each of users u1 to u3 (step S102-1), the keyword 3d is extracted from the introduction text 3a of user u4 (step S102-2).

[0075] 4, the granularity of the keyword 3d is determined (step S103), and in this example, the introduction 3a of the user u4 contains a keyword 3d with a coarse granularity. The creation support information 3b is transmitted to the terminal 3 of the user u4 (step S105), the user u4 edits the introduction 3a, and the text being input is transmitted to the information processing device 10 (step S106), and the same processing as described above is repeated.

[0076] Fig. 15 is a diagram showing an example of data transition in the keyword DB in the case of the operation example of Fig. 14. Fig. 15(A) shows an example of data at the end of step S102-1 in Fig. 14, and Fig. 15(B) shows an example of data at the end of step S102-2 in Fig. 14. Also, Fig. 15(C) shows an example of data at the end of step S106 in Fig. 14.

[0077] In this way, even if a lower-level word exists when referring to the ontology information 53, if the introduction 3a of the other user 1 does not contain a keyword 3d that indicates a specific meaning, it is not recommended to refine it. With this mechanism, matching can be performed with high accuracy.

[0078] Fig. 16 is a diagram showing an example of a screen when creation support information is provided by push notification. In Fig. 16, the user 1 can display an editing screen for the created introduction 3a on the terminal 3 by selecting the push notification 8p. The editing screen includes a message 4m and candidate keywords 3d'. By selecting one of the candidate keywords 3d', the introduction 3a can be made more specific by the operation described in Fig. 9.

[0079] The user 1 is prompted by a message 4m displayed on the terminal 3 to select candidate keywords 3d' and edit the template 7b (Figure 9), so that even if the user 1 is not good at creating introduction texts 3a, he or she can create an introduction text 3a that can perform appropriate matching.

[0080] All examples and specific terms cited herein are intended for instructional purposes to aid the reader in understanding the concepts contributed by the inventors to the advancement of the invention and the art, and should not be construed as limiting the scope of any example configuration herein, or any such specifically cited examples and conditions, with respect to showing the advantages and disadvantages of the invention.

[0081] In the above, the present embodiment has been described using the introductory text 3a at a meetup as an example, but the present embodiment is not limited to the introductory text 3a at a meetup. The present embodiment can be effectively applied to support specific description in various documents.

[0082] Although the embodiments of the present invention have been described in detail, it should be understood that various changes, substitutions and alterations can be made thereto without departing from the spirit and scope of the present invention.

[0083] The following supplementary notes are further disclosed regarding the embodiments including the above examples. (Appendix 1) Accepting a first keyword extracted from a first sentence of a first user; Identifying a candidate keyword that is recommended for use instead of or in conjunction with the first keyword from second keywords extracted from second sentences of other users based on data defining a semantic inclusion relationship between a plurality of keywords; Transmitting the candidate keywords to a terminal of the first user. A keyword recommendation program that uses a computer for processing. (Appendix 2) The computer includes: A keyword recommendation program as described in Appendix 1, which sends the first keyword and the candidate keywords to the terminal of the first user, specifies the first keyword in the first sentence displayed on the terminal, and displays the candidate keywords. (Appendix 3) The computer includes: If there is a word having a more detailed meaning than the first keyword in the semantic inclusion relationship defined in the data, the first keyword is determined to have a coarse granularity. 3. A keyword recommendation program according to claim 1 or 2 for performing processing. (Appendix 4) A keyword recommendation program as described in Appendix 3. If there is a word having a more detailed meaning than the first keyword in the semantic inclusion relationship defined in the data, and the second keyword does not match the word, the candidate keyword is not identified. (Appendix 5) Accepting a first keyword extracted from a first sentence of a first user; Identifying a candidate keyword that is recommended for use instead of or in conjunction with the first keyword from second keywords extracted from second sentences of other users based on data defining a semantic inclusion relationship between a plurality of keywords; Transmitting the candidate keywords to a terminal of the first user. A keyword recommendation method in which processing is performed by a computer. (Appendix 6) a receiving unit that receives a first keyword extracted from a first sentence of a first user; an identification unit that identifies a candidate keyword that is recommended for use instead of or in conjunction with the first keyword from second keywords extracted from second sentences of other users based on data that specifies a semantic inclusion relationship between a plurality of keywords; a transmission unit that transmits the candidate keywords to a terminal of the first user; An information processing device having the above configuration. (Appendix 7) The transmission unit transmits the first keyword and the candidate keywords to the terminal of the first user; 7. The information processing device of claim 6, wherein the terminal specifies the first keyword in the first sentence displayed on the terminal and displays the candidate keywords. [Explanation of symbols]

[0084] 1 User 2. Internet 3. Terminal 3a Introduction 3b Creation support information 3d, 3d' keywords 40 Keyword Recommendation Section 41 Extraction part 42 Judgment section 43 Recommendation Department 51 Testimonial DB 52 Keyword Database 53 Ontology Information 53 100 Information processing device

Claims

1. Extracting a first keyword from a first sentence of a first user received from a terminal of the first user; Identifying, from second keywords extracted from second sentences of other users based on data defining semantic inclusion relationships between a plurality of keywords, a candidate keyword that, instead of the first keyword, more specifically expresses an object represented by the first keyword; Transmitting the candidate keywords to a terminal of the first user. A keyword recommendation program that uses a computer for processing.

2. The computer includes: The keyword recommendation program according to claim 1 , further comprising a process for causing the terminal of the first user to display a notification including the first keyword, a message specifying the first keyword, and the candidate keyword.

3. The computer includes: If there is a word having a more detailed meaning than the first keyword in the semantic inclusion relationship defined by the data, the first keyword is determined to have a coarse granularity; 3. The keyword recommendation program according to claim 1, further comprising a step of specifying the candidate keywords when the granularity of the primary keywords is determined to be coarse.

4. Extracting a first keyword from a first sentence of a first user received from a terminal of the first user; Identifying, from second keywords extracted from second sentences of other users based on data defining semantic inclusion relationships between a plurality of keywords, a candidate keyword that, instead of the first keyword, more specifically expresses an object represented by the first keyword; Transmitting the candidate keywords to a terminal of the first user. A keyword recommendation method in which processing is performed by a computer.

5. an extraction unit that extracts a first keyword from a first sentence of a first user received from a terminal of the first user; an identification unit that identifies, instead of the first keyword, a candidate keyword that more specifically expresses an object represented by the first keyword from second keywords extracted from second sentences of other users based on data that specifies a semantic inclusion relationship between a plurality of keywords; a transmitting unit that transmits the candidate keywords to a terminal of the first user; An information processing device having the above configuration.

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