Information processing device, information processing system, information processing method, and information processing program
The information processing system addresses the challenge of managing user dictionaries by using client-generated requests with standard and user-specific dictionaries, ensuring accurate morphological analysis without data volume and security risks.
Patent Information
- Application Number
- JP2023117699
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2023-07-19
- Publication Date
- 2025-01-30
AI Technical Summary
Existing morphological analysis systems face challenges in managing user dictionaries, leading to increased data volume and security risks, and making it difficult for users to access personalized analysis without uploading their dictionaries.
An information processing system that performs morphological analysis without managing user dictionaries by using a client to generate requests with analysis documents and dictionary lists, which are processed by a server using standard and user-specific dictionaries to provide accurate analysis results.
Enables accurate morphological analysis for each user without managing user dictionaries, reducing data volume and security risks while allowing for efficient processing of user-specific words.
Smart Images
Figure 2025014827000001_ABST
Abstract
Description
[Technical field]
[0001] The present invention relates to an information processing device, an information processing system, an information processing method, and an information processing program. [Background technology]
[0002] Conventionally, morphological analysis is used to execute various tasks in natural language processing. FIG. 10 is a diagram for explaining the conventional technology. In the example shown in FIG. 10, a client 10a and a morphological analysis device 20 are connected to each other via a network. The client 10a is a terminal device used by a user A. The client 10a accepts designation of text to be analyzed from the user A, and transmits a request in which the text is set to the morphological analysis device 20 (step S1).
[0003] When the morphological analysis device 20 receives a request from the client 10a, it executes a morphological analysis on the text set in the request (step S2). For example, the morphological analysis executed by the morphological analysis device 20 includes word division, part of speech estimation, inflection estimation, etc. The morphological analysis device 20 transmits the execution result of the morphological analysis to the client 10a as a response (step S3).
[0004] If there is an error in the result of the morphological analysis performed by the morphological analysis device 20, the standard dictionary used by the morphological analysis device 20 is updated. When performing morphological analysis corresponding to a specific user, the morphological analysis device 20 uses a dictionary specific to the user. In the following description, the dictionary specific to the user is referred to as a "user dictionary." For example, when performing morphological analysis in response to a request received from the client 10a, the morphological analysis device 20 uses a user dictionary specific to user A managed by the morphological analysis device 20. [Prior art documents] [Non-patent literature]
[0005] [Non-Patent Document 1] Yahoo Japan Corporation, "Japanese morphological analysis", [online], [searched on July 3, 2023], Internet<URL:https: / / developer.yahoo.co.jp / webapi / jlp / ma / v2 / parse.html> Summary of the Invention [Problem to be solved by the invention]
[0006] However, there is room for improvement in the above-mentioned conventional techniques. For example, when the morphological analysis device 20 manages the user dictionary of each user, not only does the amount of data increase, but also security risks and access control for each user arise. In addition, it is difficult for a user to obtain the analysis result that the user desires unless the user uploads his / her own user dictionary to the morphological analysis device 20.
[0007] For this reason, it is desirable for the morphological analysis device 20 to perform morphological analysis corresponding to each user with high accuracy without managing a user dictionary.
[0008] The present application has been made in consideration of the above, and aims to provide an information processing device, an information processing system, an information processing method, and an information processing program that can accurately perform morphological analysis corresponding to each user without managing a user dictionary. [Means for solving the problem]
[0009] The information processing device according to the present application includes a receiving unit, an analyzing unit, and a notifying unit. The receiving unit receives, from a user terminal, a pair of an analysis document and a dictionary list to be used when performing morphological analysis. The analyzing unit performs morphological analysis of the analysis document based on the dictionary list. The notifying unit notifies the user terminal of the analysis result by the analyzing unit. Effect of the Invention
[0010] According to one aspect of the embodiment, it is possible to provide an effect that morphological analysis corresponding to each user can be performed with high accuracy without managing a user dictionary. [Brief description of the drawings]
[0011] [Figure 1] FIG. 1 is a diagram showing the configuration of an information processing system according to this embodiment. [Diagram 2] FIG. 2 is a diagram showing the configuration of a client according to this embodiment. [Diagram 3] FIG. 3 is a diagram illustrating an example of a data structure of the user dictionary. [Figure 4] FIG. 4 is a diagram illustrating an example of a process performed by the setting unit. [Diagram 5] FIG. 5 is a diagram showing the configuration of an information processing device according to this embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of a data structure of the standard dictionary. [Figure 7] FIG. 7 is a diagram for explaining the process in which the analysis unit infers a part of speech. [Figure 8] FIG. 8 is a flowchart showing the processing procedure of the information processing system according to this embodiment. [Figure 9] FIG. 9 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device according to the embodiment. [Figure 10] FIG. 10 is a diagram for explaining the prior art. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0012] Hereinafter, the information processing device, information processing system, information processing method, and information processing program according to the present application (hereinafter, referred to as "embodiments") will be described in detail with reference to the drawings. Note that the information processing device, information processing system, information processing method, and information processing program according to the present application are not limited to these embodiments. In addition, each embodiment can be appropriately combined as long as the processing contents are not contradictory. In addition, the same parts in each of the following embodiments are given the same reference numerals, and duplicated explanations will be omitted.
[0013] 1. Configuration of Information Processing System 1 First, an example of the configuration of an information processing system 1 according to this embodiment and information processing executed by the information processing system 1 will be described with reference to Fig. 1. Fig. 1 is a diagram showing the configuration of the information processing system according to this embodiment. As shown in Fig. 1, this information processing system 1 has a client 30a and an information processing device 100. The client 30a and the information processing device 100 are connected to each other via a network.
[0014] The client 30a is a terminal device used by a user A. The client 30a corresponds to a desktop personal computer (PC), a notebook PC, a tablet terminal, a smartphone, etc. The client 30a holds a user dictionary 341.
[0015] User dictionary 341 holds information about unique words set in advance by user A. For example, user dictionary 341 holds, for each unique word, the spelling of the word, the pronunciation of the word, the part of speech, etc. in association with each word.
[0016] In the example shown in FIG. 1, the case will be described where the information processing system 1 includes the client 30a, but the information processing system 1 may further include other clients used by other users.
[0017] The information processing device 100 is a server that performs morphological analysis on an analysis document. The information processing device 100 holds a standard dictionary 101.
[0018] The standard dictionary 101 is a dictionary that is used when the information processing device 100 executes morphological analysis. The standard dictionary 101 holds information on each common word, such as the spelling, pronunciation, part of speech, conjugation form, and meaning of the word, in association with the word.
[0019] When user A operates the input unit of client 30a to input an analysis document to be subjected to morphological analysis, client 30a generates a request 40 and transmits the generated request 40 to information processing device 100 (step S11). For example, request 40 includes analysis document 41 and dictionary list 42. Analysis document 41 is a document specified by user A. Dictionary list 42 includes a plurality of entries. Each entry is set with information such as the spelling, pronunciation, and part of speech of words included in analysis document 41.
[0020] The information of the entries included in the dictionary list 42 may be set manually by the user A himself / herself, or may be set automatically by the client 30a. When the client 30a sets the entries automatically, the client 30a uses the user dictionary 341. A specific example of the process in which the client 30a sets the entries using the user dictionary 341 will be described later.
[0021] When the information processing device 100 receives the request 40 from the client 30a, it executes a morphological analysis on the analysis document 41 stored in the request 40 (step S12). For example, the information processing device 100 executes a morphological analysis on the analysis document 41 based on the dictionary list 42 stored in the request 40 and the standard dictionary 101, and generates an analysis result. A specific example of the morphological analysis executed by the information processing device 100 will be described later.
[0022] The information processing device 100 notifies the client 30a of the analysis result of the morphological analysis as a response 45 (step S13). For example, the response 45 includes a plurality of morphemes obtained from the analyzed document 41 and parts of speech for each morpheme.
[0023] In the example shown in FIG. 1, the client 30a and the information processing device 100 transmit and receive the request 40 and the response 45 in JSON format, but the request 40 and the response 45 may be transmitted and received in another data format.
[0024] As described above, in the information processing system 1 according to this embodiment, the information processing device 100 accepts a request 40 including a pair of an analysis document 41 and a dictionary list 42 from the client 30a, executes a morphological analysis based on the standard dictionary 101 and the dictionary list 42, and notifies the client 30a of a response 45 that is the analysis result. This allows the information processing device 100 to execute morphological analysis for each user with high accuracy, even without managing a user dictionary.
[0025] 2. Configuration of client 30a An example of the configuration of the client 30a shown in Fig. 1 will be described. Fig. 2 is a diagram showing the configuration of the client 30a according to this embodiment. As shown in Fig. 2, the client 30a has a communication unit 31, an input unit 32, a display unit 33, a storage unit 34, and a control unit 35.
[0026] The communication unit 31 is realized by a NIC (Network Interface Card) or the like. The communication unit 31 is connected to a network by wire or wirelessly, and transmits and receives information to and from various other devices. For example, a control unit 35 described later uses the communication unit 31 to transmit and receive information to and from the information processing device 100.
[0027] The input unit 32 is a device for inputting various pieces of information to the control unit 35 of the client 30a. The input unit 32 is an input device such as a keyboard, a mouse, a touch panel, etc. User A operates the input unit 32 to input the analysis document 41.
[0028] The display unit 33 is a device for displaying information output from the control unit 35. The display unit 33 is a display device such as a display or a touch panel. The display unit 33 may display information of the response 45 received from the information processing device 100.
[0029] The storage unit 34 is realized by a semiconductor memory element such as a flash memory, or a storage device such as a hard disk. For example, the storage unit 34 has a user dictionary 341.
[0030] The user dictionary 341 holds information about unique words that are set in advance by the user A. FIG. 3 is a diagram showing an example of the data structure of the user dictionary 341. As shown in FIG. 3, the user dictionary 341 has a notation, a reading, a part of speech, and a same category. The notation is the notation (character string) of the corresponding word. The reading is the reading of the word corresponding to the notation. The part of speech is the part of speech of the word corresponding to the notation. The same category is a word that belongs to the same category as the word corresponding to the notation and is registered in the standard dictionary 101. For example, it is set in the user dictionary 341 that the reading of the notation "Kurobe Dam" is "Kurobe Damu" and the word in the same category as the notation "Kurobe Dam" is "Shosoin."
[0031] The data structure of the user dictionary 341 can also be realized by a trie structure. In order to enable a hash search for the notations registered in the user dictionary 341, the notations in the user dictionary 341 may be associated with hash values for the notations.
[0032] The control unit 35 is a controller, and is realized by, for example, a processor such as a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) executing various programs stored in a storage device (for example, the storage unit 34) in the client 30a using a RAM as a working area. The control unit 35 is also a controller, and is realized by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).
[0033] The control unit 35 has a reception unit 351, a setting unit 352, a transmission unit 353, and a reception unit 354, and realizes or executes the functions and actions of the processes described below. Note that the internal configuration of the control unit 35 is not limited to the configuration shown in Fig. 2, and may be other configurations as long as they perform the processes described below.
[0034] The reception unit 351 receives the designation of the analysis document from the input unit 32 operated by the user A. In addition to the analysis document, the reception unit 351 may also receive designation of the notation of words and the pronunciation of the related words. In the following description, the information on the notation of words and the pronunciation of the related words is referred to as "entry information." Note that the entry information designated by the user A does not necessarily have to include the notation, pronunciation, or part of speech, and may include only the notation.
[0035] When the receiving unit 351 receives only the designation of the analysis document from the input unit 32, it outputs the analysis document to the setting unit 352. When the receiving unit 351 receives the designation of the analysis document and the entry information, it outputs the analysis document and the entry information to the setting unit 352.
[0036] The setting unit 352 is a processing unit that generates a request in which an analysis document and a dictionary list are set (for example, request 40 shown in FIG. 1). The analysis document that the setting unit 352 sets in the request is the analysis document acquired from the receiving unit 351. The dictionary list that the setting unit 352 sets in the request is generated, for example, by performing the following process.
[0037] Fig. 4 is a diagram for explaining an example of the processing of the setting unit 352. In the explanation of Fig. 4, it is assumed that the analysis document 41 contains the character string "Haruto-kun and Haruki-chan...the news about Kurobe Dam came in...". The setting unit 352 adds the character string contained in the analysis document 41 one character at a time and performs dictionary lookup in the user dictionary 341. Adding the character string contained in the analysis document 41 one character at a time indicates that the character string to be looked up in the dictionary goes as follows: "Hi" -> "Haruto" -> "Haruto-ku" -> "Haruto-kun" -> "Haruto-kun and".
[0038] For example, by performing dictionary lookup, the setting unit 352 finds that "Haruto" in the analysis document 41 matches the spelling "Haruto" in the user dictionary 341. Based on the dictionary lookup result, the setting unit 352 sets the spelling "Haruto", the reading "Haruto", and the part of speech "proper noun" in the user dictionary 341 as the entry information 42-1.
[0039] The setting unit 352 performs dictionary lookup and finds that "Himari" in the analysis document 41 matches the spelling "Himari" in the user dictionary 341. Based on the dictionary lookup result, the setting unit 352 sets the spelling "Himari," the reading "Himari," and the part of speech "proper noun" in the user dictionary 341 as entry information 42-2.
[0040] The setting unit 352 performs dictionary lookup and finds that "Kurobe Dam" in the analysis document 41 matches the spelling "Kurobe Dam" in the user dictionary 341. Based on the dictionary lookup result, the setting unit 352 sets the spelling "Kurobe Dam", the reading "kurobe dam", the part of speech "kara (no part of speech set)", and the same category "Shosoin" in the user dictionary 341 as entry information 42-3.
[0041] In addition, when performing the above dictionary lookup, the setting unit 352 may perform a hash search based on the hash value of the character string to be looked up in the dictionary and the hash value that is set in advance for each notation in the user dictionary 341.
[0042] 4, the setting unit 352 generates entry information and sets the generated entry information in the dictionary list. For example, the entry information 42-1 to 42-3 are set in the dictionary list 42. Note that, when entry information is specified in advance via the input unit 32, the setting unit 352 may skip the process of generating the entry information and set the specified entry information in the dictionary list 42.
[0043] Here, the setting unit 352 may set all the entries of the user dictionary 341 in the dictionary list 42 without performing the dictionary lookup. Note that, if all the entries of the user dictionary 341 are set in the dictionary list 42, the amount of data communication may increase, which may lead to a decrease in speed. Therefore, the setting unit 352 may perform the dictionary lookup and give priority to the process of generating entry information.
[0044] The setting unit 352 generates a request 40 in which the analysis document 41 and the dictionary list 42 are set. The setting unit 352 outputs the request 40 to the transmission unit 353.
[0045] The transmission unit 353 transmits the request 40 acquired from the setting unit 352 to the information processing device 100 .
[0046] The receiving unit 354 receives the response 45 from the information processing device 100. The receiving unit 354 may output information of the response 45 to the display unit 33 for display. Note that the client 30a may execute various tasks of natural language processing based on the response 45.
[0047] 3. Configuration of Information Processing Device 100 An example of the configuration of the information processing device 100 shown in Fig. 1 will be described. Fig. 5 is a diagram showing the configuration of the information processing device 100 according to this embodiment. As shown in Fig. 5, the client 30a has a communication unit 110, an input unit 120, a display unit 130, a storage unit 140, a temporary storage unit 145, and a control unit 150.
[0048] The communication unit 110 is realized by a NIC or the like. The communication unit 110 is connected to a network by wire or wirelessly, and transmits and receives information to and from various other devices. For example, the control unit 150, which will be described later, uses the communication unit 110 to transmit and receive information to and from the client 30a (and other clients not shown).
[0049] The input unit 120 is a device for inputting various types of information to the control unit 150 of the information processing device 100. The input unit 120 is an input device such as a keyboard, a mouse, or a touch panel.
[0050] The display unit 130 is a device for displaying information output from the control unit 150. The display unit 130 is a display device such as a display or a touch panel.
[0051] The storage unit 140 is realized by a semiconductor memory element (non-volatile memory) such as a flash memory, or a storage device such as a hard disk. For example, the storage unit 140 has the standard dictionary 101.
[0052] The standard dictionary 101 is a dictionary used when the information processing device 100 executes morphological analysis. The standard dictionary 101 holds information such as the notation, pronunciation, part of speech, conjugation, and meaning of each general word in association with the word. Fig. 6 is a diagram showing an example of the data structure of the standard dictionary 101. As shown in Fig. 6, the standard dictionary 101 has words (notation), pronunciation, part of speech, conjugation, and the like. Words registered in the standard dictionary 101 are general words.
[0053] The data structure of the standard dictionary 101 can also be realized by a trie structure. In order to enable a hash search for the notations registered in the standard dictionary 101, a word in the standard dictionary may be associated with a hash value for the word.
[0054] The temporary storage unit 145 is a storage device that temporarily stores information. For example, the temporary storage unit 145 is a RAM (Random Access Memory) or the like. The temporary storage unit 145 stores a request 40 transmitted from the client 30a. The request 40 includes an analysis document 41 and a dictionary list 42.
[0055] The control unit 150 is a controller, and is realized, for example, by a processor such as a CPU or an MPU, which executes various programs stored in a storage device (for example, the storage unit 140) inside the information processing device 100 using a RAM as a working area. The control unit 150 is also a controller, and is realized, for example, by an integrated circuit such as an ASIC or an FPGA.
[0056] The control unit 150 has a receiving unit 151, an analyzing unit 152, and a notifying unit 153, and realizes or executes the functions and actions of the processes described below. Note that the internal configuration of the control unit 150 is not limited to the configuration shown in Fig. 5, and may be other configurations as long as they perform the processes described below.
[0057] The reception unit 151 receives the request 40 from the client 30a. The reception unit 151 stores the received request 40 in the temporary storage unit 145.
[0058] The analysis unit 152 executes a morphological analysis on the analysis document 41 included in the request 40 based on the standard dictionary 101 and the dictionary list 42 included in the request 40. The analysis unit 152 outputs the result of the morphological analysis to the notification unit 153.
[0059] For example, the analysis unit 152 analyzes character strings in the analysis document 41 with reference to the standard dictionary 101 and the dictionary list 42, divides words, estimates parts of speech, and determines conjugations, thereby identifying combinations of multiple morphemes and parts of speech. Based on the cost minimization method, the analysis unit 152 outputs, as the analysis result of the morpheme analysis, the combination of morphemes and parts of speech that has the smallest cost from among the identified combinations of morphemes and parts of speech.
[0060] Here, the analysis unit 152 infers the part of speech based on the standard dictionary 101 for entry information set in the dictionary list 42 that has no part of speech and is set to the same category.
[0061] FIG. 7 is a diagram for explaining the process of estimating a part of speech by the analysis unit 152. In the example shown in FIG. 7, the description will be given using the entry information 42-3. In the entry information 42-3, the part of speech is left blank, and therefore the part of speech of the spelling "Kurobe Dam" is not set. In this case, the analysis unit 152 compares "Shosoin" set in the same category of the entry information 42-3 with each word in the standard dictionary 101, and uses the part of speech "noun" corresponding to Shosoin as the part of speech of the spelling "Kurobe Dam" when performing morphological analysis.
[0062] By executing the above process, the analysis unit 152 executes a morphological analysis of the analysis document 41 included in the request 40. After executing the morphological analysis of the analysis document 41, the analysis unit 152 deletes the request 40 from the temporary storage unit 145.
[0063] The notification unit 153 sets the analysis result of the analysis unit 152 in the response 45, and notifies the response 45 to the client 30a.
[0064] 4. Processing Procedure
[0065] Next, an example of a processing procedure of the information processing system 1 according to this embodiment will be described. Fig. 8 is a flowchart showing the processing procedure of the information processing system 1 according to this embodiment. As shown in Fig. 8, the receiving unit 351 of the client 30a receives an analysis document (step S101).
[0066] The setting unit 352 of the client 30a generates a dictionary list based on the user dictionary 341 (step S102). The sending unit 353 of the client 30a sends a request in which the analysis document and the dictionary list are set to the information processing device 100 (step S103).
[0067] The accepting unit 151 of the information processing device 100 accepts the request and stores it in the temporary storage unit 145 (step S104). The analyzing unit 152 of the information processing device 100 executes a morphological analysis of the analysis document based on the standard dictionary 101 and the dictionary list (step S105).
[0068] The notification unit 153 of the information processing device 100 notifies the client 30a of a response in which the analysis result is set (step S106). The receiving unit 354 of the client 30a receives the response (step S107). Meanwhile, the analysis unit 152 deletes the request from the temporary storage unit 145 (step S108).
[0069] [5. Hardware Configuration] The client 30a or the information processing device 100 according to the embodiment described above is realized by a computer 80 having a configuration as shown in Fig. 9, for example. The information processing device 100 will be described below as an example. Fig. 9 is a hardware configuration diagram showing an example of a computer 80 that realizes the functions of the information processing device 100 according to the embodiment. The computer 80 has a CPU 81, a RAM 82, a ROM (Read Only Memory) 83, a HDD (Hard Disk Drive) 84, a communication interface (I / F) 85, an input / output interface (I / F) 86, and a media interface (I / F) 87.
[0070] The CPU 81 operates and controls each part based on a program stored in the ROM 83 or the HDD 84. The ROM 83 stores a boot program executed by the CPU 81 when the computer 80 is started up, a program dependent on the hardware of the computer 80, and the like.
[0071] The HDD 84 stores programs executed by the CPU 81, data used by such programs, etc. The communication interface 85 receives data from other devices via the network and sends it to the CPU 81, and transmits data generated by the CPU 81 to other devices via the network N.
[0072] The CPU 81 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse, via the input / output interface 86. The CPU 81 acquires data from the input devices via the input / output interface 86. The CPU 81 also outputs data generated via the input / output interface 86 to the output devices.
[0073] The media interface 87 reads a program or data stored in a recording medium 88 and provides it to the CPU 81 via the RAM 82. The CPU 81 loads the program from the recording medium 88 onto the RAM 82 via the media interface 87 and executes the loaded program. The recording medium 88 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase change rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.
[0074] For example, when the computer 80 functions as the information processing device 100 according to the embodiment, the CPU 81 of the computer 80 executes a program loaded on the RAM 82 to realize the function of the control unit 150. The request 40 transmitted from the client 30a is temporarily stored in the RAM 82. In addition, the data in the storage unit 140 is stored in the HDD 84. The CPU 81 of the computer 80 reads and executes these programs from the recording medium 88, but as another example, these programs may be obtained from another device via the network N.
[0075] [6. Other] In addition, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by a known method. In addition, the information including the processing procedures, specific names, various data and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.
[0076] In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc.
[0077] For example, the information processing device 100 described above may be realized by multiple server computers, and depending on the functions, the configuration can be flexibly changed by calling an external platform using an API (Application Programming Interface) or network computing.
[0078] Furthermore, the above-described embodiments and modifications can be appropriately combined as long as the processing contents are not contradictory.
[0079] [7. Effects] As described above, the information processing device 100 according to the embodiment includes the receiving unit 151, the analysis unit 152, and the notification unit 153. The receiving unit 151 receives a pair of an analysis document and a dictionary list to be used when performing morphological analysis from a user terminal (client 30a). The analysis unit 152 performs morphological analysis of the analysis document based on the dictionary list. The notification unit 153 notifies the user terminal of the analysis result by the analysis unit 152. This allows the information processing device 100 to accurately perform morphological analysis corresponding to each user without managing a user dictionary.
[0080] Furthermore, the analysis unit 152 executes a morphological analysis of the analysis document based on a standard dictionary and a dictionary list set in advance, thereby making it possible to execute a morphological analysis by supplementing information on user-specific words that are not set in the standard dictionary with the dictionary list.
[0081] Furthermore, the accepting unit 151 stores the dictionary list in a volatile memory (temporary storage unit 145), and the analyzing unit 152 executes a morphological analysis of the analysis document based on the standard dictionary stored in the non-volatile memory (storage unit 140) and the dictionary list stored in the non-volatile memory, and then deletes the dictionary list from the volatile memory. This makes it possible to reduce the amount of data stored in the information processing device 100. It also makes it possible to reduce security risks.
[0082] The dictionary list also includes the spellings of the words included in the analysis document, and the analysis unit 152 identifies the part of speech of the word based on the spelling and performs a morphological analysis of the analysis document based on the spelling and the part of speech. This makes it possible to perform a morphological analysis of the analysis document with high accuracy.
[0083] The dictionary list includes the notation of the word included in the analysis document and the notation of other words, and the analysis unit 152 identifies the part of speech of the word based on the notation of the other words, and performs morphological analysis of the analysis document based on the notation and the part of speech. For example, a standard dictionary is a dictionary that associates words with the parts of speech corresponding to the words, and the analysis unit 152 identifies the parts of speech of the other words based on the other words and the standard dictionary. This makes it possible to estimate the part of speech corresponding to the notation of the word included in the analysis document even if it is not included in the request.
[0084] Based on the standard dictionary and the dictionary list, the analysis unit 152 divides the character string contained in the analyzed document into multiple morphemes, calculates the cost of multiple combinations of morphemes and parts of speech, and outputs the combination of morphemes and parts of speech with the smallest cost as the result of the morphological analysis.
[0085] The user terminal (client 30a) includes a setting unit 352 and a transmission unit 353. The setting unit 352 identifies the spelling of words included in the analysis document, and sets the spelling of the identified words in the dictionary list. The transmission unit 353 transmits a set of the analysis document and the dictionary list to be used when performing morphological analysis to the information processing device. For example, even if user A does not manually input information about the dictionary list, the information processing device 100 can be notified of the information about the dictionary list and morphological analysis can be performed.
[0086] In addition, the setting unit 352 identifies the spellings of words included in the analysis document by using a user dictionary whose dictionary structure is a trie structure or a user dictionary whose dictionary structure is a hash table. This makes it possible to efficiently identify the spellings of words in the analysis document.
[0087] The above describes the embodiment of the present application in detail based on the drawings, but this is merely an example, and the present invention can be implemented in other forms that include various modifications and improvements based on the knowledge of those skilled in the art, including the aspects described in the Disclosure of the Invention section.
[0088] Furthermore, the above-mentioned "section, module, unit" can be read as "means" or "circuit", etc. For example, an acquisition section can be read as an acquisition means or an acquisition circuit. [Explanation of symbols]
[0089] 10a Client 20 Morphological analysis device 30a Client 31,110 Communications Department 32,120 Input section 33,130 Display section 34,140 storage unit 35,150 Control section 100 Information processing device 101 Standard Dictionary 145 Temporary storage 151 Reception 152 Analysis Department 153 Notification Department 341 User Dictionary 351 Reception 352 Settings 353 Transmitter 354 Receiving section
Claims
1. a reception unit for receiving, from a user terminal, a pair of an analysis document and a dictionary list to be used when performing morphological analysis; an analysis unit that performs a morphological analysis of the analysis document based on the dictionary list; A notification unit that notifies the user terminal of the analysis result by the analysis unit.
23. An information processing apparatus comprising:
2. 2. The information processing apparatus according to claim 1, wherein the analysis unit executes a morphological analysis of the analysis document based on a standard dictionary set in advance and the dictionary list.
3. The information processing device according to claim 2, characterized in that the reception unit stores the dictionary list in a volatile memory, and the analysis unit deletes the dictionary list from the volatile memory after performing a morphological analysis of the analysis document based on the standard dictionary stored in the non-volatile memory and the dictionary list stored in the non-volatile memory.
4. The information processing device according to claim 1, characterized in that the dictionary list includes spellings of words included in the analysis document, and the analysis unit identifies parts of speech of the words based on the spellings, and performs morphological analysis of the analysis document based on the spellings and the parts of speech.
5. The information processing device according to claim 2, characterized in that the dictionary list includes notations of words included in the analysis document and notations of other words, and the analysis unit identifies the part of speech of the word based on the notations of the other words, and performs morphological analysis of the analysis document based on the notations and the parts of speech.
6. The information processing device according to claim 5, characterized in that the standard dictionary is a dictionary in which words are associated with parts of speech corresponding to the words, and the analysis unit identifies the parts of speech of the other words based on the other words and the standard dictionary.
7. The information processing device according to claim 2, characterized in that the analysis unit divides a character string contained in the analysis document into a plurality of morphemes based on the standard dictionary and the dictionary list, calculates costs for a plurality of combinations of morphemes and parts of speech, and outputs the combination of morphemes and parts of speech that has the smallest cost as a result of morphological analysis.
8. An information processing system having a user terminal and an information processing device, The user terminal includes: a transmitting unit that transmits a set of an analysis document and a dictionary list to be used when performing a morphological analysis to the information processing device; The information processing device includes: a reception unit that receives a pair of the analysis document and the dictionary list from the user terminal; an analysis unit that performs a morphological analysis of the analysis document based on the dictionary list; A notification unit that notifies the user terminal of the analysis result by the analysis unit. An information processing system comprising:
9. The user terminal includes:
9. The information processing system according to claim 8, further comprising a setting unit that identifies spellings of words included in the analysis document based on a user dictionary and sets the spellings of the identified words in the dictionary list.
10. The information processing system according to claim 9, characterized in that the setting unit identifies the spellings of words contained in the analysis document using a user dictionary whose dictionary structure is a trie structure or a user dictionary whose dictionary structure is a hash table.
11. 1. A computer-implemented information processing method, comprising: a receiving step of receiving, from a user terminal, a set of an analysis document and a dictionary list to be used when performing morphological analysis; an analysis step of performing a morphological analysis of the analysis document based on the dictionary list; A notification step of notifying the user terminal of the analysis result by the analysis step.
23. An information processing method comprising:
12. a receiving step of receiving, from a user terminal, a set of an analysis document and a dictionary list to be used when performing morphological analysis; an analysis step of performing a morphological analysis of the analysis document based on the dictionary list; a notification procedure for notifying the user terminal of an analysis result obtained by the analysis procedure.
23. An information processing program comprising: