WO2016137114A1 - Procédé et dispositif d'établissement de base de données de métaconnaissances et de traitement d'interrogation - Google Patents

Procédé et dispositif d'établissement de base de données de métaconnaissances et de traitement d'interrogation Download PDF

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Publication number
WO2016137114A1
WO2016137114A1 PCT/KR2016/000087 KR2016000087W WO2016137114A1 WO 2016137114 A1 WO2016137114 A1 WO 2016137114A1 KR 2016000087 W KR2016000087 W KR 2016000087W WO 2016137114 A1 WO2016137114 A1 WO 2016137114A1
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Prior art keywords
query
data
meta
service
knowledge database
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PCT/KR2016/000087
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English (en)
Korean (ko)
Inventor
하영국
박진성
이대희
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건국대학교 산학협력단
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Priority claimed from KR1020150068884A external-priority patent/KR101653256B1/ko
Priority claimed from KR1020150190848A external-priority patent/KR101743731B1/ko
Application filed by 건국대학교 산학협력단 filed Critical 건국대학교 산학협력단
Publication of WO2016137114A1 publication Critical patent/WO2016137114A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/16—Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor

Definitions

  • the present invention relates to a method and apparatus for constructing a meta knowledge database and processing a query, and more particularly, to construct a meta knowledge database having a new expression method for more efficient user query response by integrating distributed data among devices. And a method and apparatus for processing queries.
  • the present invention relates to a desire to use a service between a plurality of smart terminals and a plurality of users by establishing a connection relationship of various information.
  • users want to integrate vast amounts of information to obtain deeper and broader processed information.
  • meta knowledge which is knowledge based on the meta knowledge model as knowledge for searching and accessing distributed data and terminal services between connected terminals.
  • a meta knowledge database which is a database for storing and retrieving meta knowledge for accessing data and terminal services, is required.
  • each item of meta knowledge data for each source is converted into a standard meta knowledge data item and managed, and various items are adapted to the format of meta knowledge data. It is necessary to convert the standard meta knowledge data into a form and store it. Accordingly, a lightweight meta knowledge database needs to be constructed, and a discussion about how to apply a method and apparatus for fusion and synthesis of distributed knowledge to a smart terminal is needed. .
  • An object of the present invention is to provide a method and apparatus for constructing a meta knowledge database and processing a query by integrating various services and data generated in each terminal into one.
  • Another problem to be solved by the present invention is to establish a meta-knowledge database, which associates various services with data generated at each terminal, processes a user's query, and provides data corresponding to the user's query. It is to provide a method and apparatus for processing.
  • a method of constructing a meta knowledge database and processing a query includes extracting one or more key words from a query, based on the key words. Retrieving knowledge, and generating and storing a response to the query based on the information included in the retrieved meta-knowledge.
  • the main word is characterized in that it comprises at least one of the object of the query and the purpose of the question.
  • meta-knowledge is associated with access to information, and characterized in that it includes at least one of information search target, information access method, information type.
  • the meta-knowledge database is characterized in that it contains information about the Device (Device), Service (Service) and Agent (Agent).
  • the device is at least one of a smartphone, PC, server, tablet
  • the service includes at least one of a calendar (Calendar), mail, location-based information, photo album, contact application,
  • the information on the agent may include at least one of a birthday, a name, an age, a company, an address, a homepage, a phone number, and a job.
  • the meta-knowledge database is characterized in that the data of the meta-knowledge database can be expanded through user input.
  • the apparatus for building a meta knowledge database and processing a query includes a communication unit for receiving a query and transmitting a response, a storage unit for storing a meta knowledge database, and a communication unit. And a processor configured to be connected with the storage unit, wherein the processor extracts one or more key words from the query, retrieves meta knowledge from the meta knowledge database using the key words, and queries using the information contained in the meta knowledge. Generate a response to the.
  • a method of constructing a meta-knowledge database and processing a query may be applied to at least one of a terminal, a service, and a user from a plurality of terminals in the same network or a short distance.
  • Receiving data generating a proximity user data table containing the received data, receiving a query and accessing the proximity user data table, thereby processing the query and providing the processed result data; It is characterized by.
  • the query is characterized in that it is input by text or voice.
  • the method further comprises updating the proximity user data table by receiving changed or new data from at least one of the plurality of terminals.
  • the step of receiving data and updating the proximity user data table further comprises converting the data into a language in which the proximity user data table is written.
  • the step of providing the result data is characterized in that the step of providing the converted result data in the form of JSON.
  • the providing of the result data may include selecting and providing common data according to a predetermined priority or more than a predetermined number of terminals.
  • the apparatus for constructing a meta knowledge database and processing a query may be applied to at least one of a terminal, a service, and a user from a plurality of terminals existing in the same network or a short distance.
  • An initialization module that receives data, generates a proximity user data table containing the received data, and a query module that receives the query, processes the query by accessing the proximity user data table, and provides the processed result data. It is characterized by.
  • the present invention has the effect of providing a method and apparatus for constructing a meta knowledge database and processing a query by integrating various services and data generated in each terminal into one.
  • the present invention relates to various services and data generated in each terminal, and to build a meta-knowledge database and process the query to process the user's query to provide data corresponding to the user's query Has the effect of providing.
  • FIG. 1 is a block diagram of a meta knowledge database server for providing a meta knowledge database construction method according to an embodiment of the present invention.
  • FIG. 2 is a flowchart illustrating a data retrieval method using a meta knowledge database according to an embodiment of the present invention.
  • FIG. 3 is a diagram illustrating a data retrieval method using a meta knowledge database according to one embodiment.
  • 4A to 4B are diagrams for explaining a superstructure of the meta knowledge database according to an embodiment of the present invention.
  • 5A and 5C are diagrams for describing an infrastructure of a meta knowledge database according to an embodiment of the present invention.
  • FIG. 6 is a diagram illustrating a relationship between a plurality of terminals and a device for processing a query according to an embodiment of the present invention.
  • FIG. 7 illustrates a schematic configuration of an apparatus for processing a query according to an embodiment of the present invention.
  • FIG. 8 illustrates a procedure of processing a query based on data stored in a meta knowledge database according to a method of processing a query according to an embodiment of the present invention.
  • FIG. 9 schematically illustrates an apparatus for processing a query according to an embodiment of the invention.
  • FIG. 10 illustrates a structure of a proximity user data table according to another embodiment of the present invention.
  • first, second, etc. are used to describe various components, these components are of course not limited by these terms. These terms are only used to distinguish one component from another. Therefore, of course, the first component mentioned below may be a second component within the technical spirit of the present invention.
  • each of the features of the various embodiments of the present invention may be combined or combined with each other in part or in whole, various technically interlocking and driving as can be understood by those skilled in the art, each of the embodiments may be implemented independently of each other It may be possible to carry out together in an association.
  • query is used synonymously with a query and means a search word input by a user.
  • the query Through the query, the user can search the data existing in the data table through the user's desired condition and search the searched results.
  • the query may be input by text or voice.
  • the term "ontology” refers to a formalized and explicit description of the shared conceptualization of each field within an information system.
  • the ontology is a conceptual and computer-friendly form of what is reached through discussions between people about what they see, hear, feel and think about the world. Meta knowledge designed using ontologies can be extended and connected indefinitely, making it a unique concept.
  • the meta knowledge database device 100 may include a processor 110, a communication unit 120, a storage unit 130, and a memory 140.
  • the meta knowledge database device 100 is a database server based on a Meta-Knowledge Base.
  • the meta knowledge database device 100 may be a terminal or a server including at least the processor 110, the communication unit 120, the storage unit 130, and the memory 140.
  • the meta knowledge database device 100 is assumed and described as a data server, but is not limited to the data server and may be one of various devices capable of operating as the meta knowledge database device 100.
  • the processor 110 performs various operations in the meta knowledge database device 100.
  • the meta knowledge database device 100 determines the structure of the data through the processor 110, constructs a database according to the identified data structure, and stores the data in the constructed database.
  • the meta knowledge database device 100 retrieves data from the database that matches the user's query through the processor 110.
  • the communication unit 120 plays a role in which the meta knowledge database device 100 transmits and receives data with an external device.
  • the meta knowledge database apparatus 100 through the communication unit 120 may transmit or receive a query and a response to an external device.
  • the communicator 120 may include one or more components that enable communication between external devices.
  • the communication unit 120 may include a short range communication module, a mobile communication module, a wireless internet module, a wired internet module, or the like.
  • the storage unit 130 is a storage medium for storing data in the meta knowledge database device 100.
  • the meta knowledge database device 100 may store electronic document data in the storage unit 130.
  • the storage unit 130 may be a flash memory type, a hard disk type, a multimedia card micro type, or a card type memory (for example, SD or XD memory). Can be.
  • the storage unit 130 is not limited to the above-described device and may include various general-purpose storage devices.
  • the memory 140 temporarily stores data to be processed in the meta knowledge database device 100.
  • the meta knowledge database device 100 may temporarily store electronic document data in the memory 140 and process the same through the processor 110.
  • the memory 140 may be random access memory (RAM) or static random access memory (SRAM).
  • RAM random access memory
  • SRAM static random access memory
  • the memory 140 is not limited to the above-described apparatus and may include various general purpose memories 140.
  • FIG. 2 is a flowchart illustrating a data retrieval method using a meta knowledge database according to an embodiment of the present invention.
  • the meta knowledge database device In order to retrieve data using the meta knowledge database, the meta knowledge database device first receives a query (S210).
  • the meta knowledge database device receives a query from a user through a communication unit.
  • a query might be in the form of questions such as "today's weather”, “time of withdrawal”, and so on.
  • the structure of the query is not limited and may be defined in various forms.
  • the meta knowledge database device extracts one or more key words from the query (S220).
  • the query may consist of a single sentence. Since the sentence structure is a configuration that cannot be recognized by the computer, the meta knowledge database device extracts the key word of a costume from the query so that the computer can recognize it.
  • the key word may include at least one of the object of the query and the purpose of the question. For example, if “weather today” is a query, we can extract “today”, which means time, and “weather”, which indicates the purpose of the question. If “time of withdrawal” is a query, the subject “ Key words can be extracted with the term “schedule” indicating the purpose of withdrawal and the purpose of the question.
  • the meta knowledge database device searches for meta knowledge in the meta knowledge database using key words (S230).
  • the meta knowledge database device retrieves taxonomy and data classification information including key words.
  • the corresponding meta knowledge can be searched using the taxonomy and data classification information.
  • the meta knowledge is information for access to information, and includes at least one of an information search object, an information access method, and an information type, and means information about knowledge, not knowledge itself. For example, if the key words are “withdrawal” and schedule, the database device can search for the calendar service on the withdrawal's smartphone with the texonomi and data classification information, and find the “withdrawal schedule” with the calendar service on the withdrawal's smartphone. You can search for meta knowledge.
  • a database construction method for the meta knowledge storage method will be described in detail later with reference to FIGS. 4A to 5C.
  • the meta knowledge database device generates a response to the query by using the information included in the meta knowledge (S240).
  • the meta knowledge database device may generate a response to the query using meta knowledge. For example, a calendar service in the smartphone of the withdrawal may be searched for "departure schedule" to notify the user of the specific schedule of the withdrawal.
  • a database In order to provide a response to such a user's query, a database must be constructed to systematically classify meta knowledge.
  • a method of constructing such a meta knowledge database of the present invention is included and will be described below in detail with reference to FIGS. 4A to 5C.
  • FIG. 3 is a diagram illustrating a data retrieval method using a meta knowledge database according to one embodiment.
  • the meta-knowledge database device 100 When the meta-knowledge database device 100 receives the query "311 is a schedule of withdrawal" from the user, the meta-knowledge database device 100 receives the key words 312 in the query 311 and the schedule Extract '
  • the meta knowledge database device 100 may search where the meta knowledge is stored in the meta knowledge database through the extracted main word 312. For example, one may search for meta knowledge 321 that “the schedule of withdrawal” may be obtained from the calendar service of his smartphone. When the meta knowledge 321 is found, the meta knowledge database device 100 sends information on the “schedule of the withdrawal” to the calendar service of the withdrawal smartphone 341, which is a device corresponding to the meta knowledge 321. May request and receive the desired response from the withdrawn smartphone 341.
  • This process is the same as obtaining a response corresponding to the query in the meta knowledge database apparatus 100 according to the flowchart of FIG. 2.
  • 4A to 4B are diagrams for explaining a superstructure of the meta knowledge database according to an embodiment of the present invention.
  • the meta knowledge database includes information about the Device 420, the Service 410, and the Agent 430.
  • the device 420 represents a device for providing a service and a meta knowledge database.
  • the device 420 may correspond to a physical device such as a smartphone, a meta knowledge database server, and a notebook.
  • the service 410 represents a service provided from the device and the meta knowledge database, and may be, for example, a software configuration such as a calendar service, a mail service, a location service, a common sense service, an encyclopedia service, and the like.
  • the agent 430 refers to an owner of a device providing a service or a subject receiving a service from the device.
  • the agent 430 may correspond to a user, an organization, or an organization.
  • the meta knowledge database can store and store meta knowledge in the above three configurations.
  • the device 420 is a smartphone
  • the service 410 is one of a calendar service, an address book service, and a mail service
  • the agent 430 is a TOM, which is a subject obtaining information through the smartphone.
  • 5A and 5C are diagrams for describing an infrastructure of a meta knowledge database according to an embodiment of the present invention.
  • the service 410 includes a plurality of lower taxonomies 510, 520, and 530.
  • the taxonomies 510, 520, and 530 mean lower concepts for distinguishing and expressing a higher service.
  • the taxonomies 510, 520, 530 of the service 410 may be calendar services, address book services, mail services, or the like.
  • Such a taxonomy is not limited to the above description, and various services corresponding to sub-concepts of a service may be a taxonomy.
  • This taxonomy includes data classification information 511, 512, 513 for classifying and storing data.
  • Data classification information refers to a sub-concept for classifying information of texonomies.
  • the calendar service corresponds to the taxonomy 510
  • the data classification information refers to information that the calendar service may include, such as a date, a place, and an appointment.
  • the device 420 includes a plurality of lower taxonomies 540, 550, and 560.
  • the texonomies 540, 550, and 560 mean lower concepts for distinguishing and representing devices, which are higher concepts.
  • the texonomi of device 420 may be a smartphone, notebook, server, or the like.
  • the texonomi is not limited to the above description, and various devices corresponding to sub-concepts of the device may be texonomi.
  • the taxonomy includes data classification information 541, 542, and 543 for classifying and storing data.
  • the data classification information refers to information that the smartphone has, such as the owner, phone number, and model name of the smartphone.
  • agent 430 includes a plurality of lower taxonomies 570, 580, 590.
  • the texonomies 570, 580, and 590 mean lower concepts for distinguishing and representing devices, which are higher concepts.
  • the taxonomy of the agent 430 may be withdrawal (person's name), Alice (person's name), a corporation.
  • These texonomies are not limited to those described above, and various agents corresponding to the agent sub-concepts may be texonomies.
  • the taxonomy includes data classification information 571, 572, and 573 for classifying and storing data.
  • the data classification information refers to information that is withdrawn, such as withdrawal height, withdrawal weight, and withdrawal occupation.
  • the advantageous effect of the present invention is that the database can be built around the service instead of the device.
  • FIG. 6 is a diagram illustrating a relationship between a plurality of terminals and a device for processing a query according to an embodiment of the present invention.
  • the host terminal 611 and the plurality of terminals 612 and 613 are in the same network or near field. Among them, the host terminal 611 collects data of the plurality of terminals 612 and 613 and stores them in the local database 611a of the host terminal 611. The stored data is stored in a table form in the local database 611a.
  • the host terminal 611 stores data from the plurality of terminals 612 and 613 in the local database 611a with meta knowledge that is divided into a terminal, a service, and a user.
  • a query is input to a program such as Siri
  • the query is processed using data of the terminal itself and information accessible through the Internet.
  • the host terminal 611 collects data, that is, meta knowledge, of the plurality of terminals 612 and 613 in the same network or connected by communication, and stores the metadata in the local database 611a to store the meta knowledge. Process queries based on knowledge
  • terminals existing in the same network or local area can share data to search and access data, and process queries with ontology-based meta knowledge generated based on the data.
  • FIG. 7 illustrates a schematic configuration of an apparatus for processing a query according to an embodiment of the present invention.
  • the query processing apparatus 700 in the host terminal includes an initialization module 710, a data management module 720, a query module 730, and a proximity user data table 740.
  • the proximity user data table 740 is a table in which data is stored and is included in the meta knowledge database.
  • the initialization module 710 receives data from a plurality of terminals present in the same network or near field.
  • the initialization module 720 receives data on at least one of a terminal, a service provided from the terminal, and a terminal user.
  • the initialization module 710 includes a transformation module 711, a table generation module 712, and an input module 713.
  • the conversion module 711 converts the data received from the plurality of terminals into a language in which the proximity user data table 740 is to be written.
  • the language in which proximity user data table 740 is to be written may be SQL.
  • the table generation module 712 generates a table to store data received from the plurality of terminals.
  • the table generated by the table generation module 712 is the proximity user data table 740, and may be written in SQL, for example.
  • the data stored in the proximity user data table 740 is data for at least one of the terminal, service, and user.
  • the input module 713 inputs data for at least one of the terminal, the service, and the user into the proximity user data table 740 generated by the table generation module 712.
  • a detailed proximity user data table 740 will be described later with reference to FIG. 5.
  • the data management module 720 receives the changed or new data from the plurality of terminals to update the proximity user data table 740. Specifically, when data already stored in the proximity user data table 740 generated by the initialization module 710 is changed, the data management module 720 receives the changed data from at least one of the plurality of terminals. . In addition, the data management module 720 receives new data not stored in the proximity user data table 740 generated by the initialization module 710 from at least one terminal of the plurality of terminals.
  • the data management module 720 includes a conversion module 721, an input module 722, a deletion module 723, and a modification module 724.
  • the conversion module 721 converts the received changed data or new data into the language in which the proximity user data table 740 is written.
  • the input module 722 inputs the data converted by the conversion module 721 into the language in which the proximity user data table 740 is written into the proximity user data table 740.
  • the data input by the input module 722 into the proximity user data table 740 is new data received from at least one of the plurality of terminals that the initialization module 710 did not store in the proximity user data table 740.
  • the deletion module 723 deletes data that the initialization module 710 inputs into the proximity user data table 740.
  • the modification module 724 modifies the data that the initialization module 710 stores in the proximity user data table 740.
  • the modification module 724 modifies the data stored in the proximity user data table 740 by the initialization module 710 with the changed data received from at least one of the plurality of terminals.
  • the query module 730 receives the query and processes the query by accessing the proximity user data table 740.
  • the query module 730 then provides the processed result data.
  • the result data represents the results for the query processed by the query module 730.
  • the query module 730 receives the query from the host terminal to access the proximity user data table 740, thereby providing the result data present in the proximity user data table 740.
  • Query module 730 includes a transformation module 731, a user query module 732, a terminal query module 733, an input and output value query module 734, a service query module 735, and a provision module 736. do.
  • the transformation module 731 converts the received query and the result data retrieved by the user query module 732, the terminal query module 733, the input and output value query module 734, and the service query module 735 into JSON format.
  • JSON format is a format that uses user-readable text. In other words, JSON format means a format for representing characters.
  • the conversion module 731 may identify the type of query and transmit the type of query to an appropriate module among the user query module 732, the terminal query module 733, the input and output value query module 234, and the service query module 735. have.
  • the user query module 732 queries the data of the service associated with the user present in the proximity user data table 740 based on the converted query.
  • the terminal query module 733 queries the data of the service related to the terminal present in the proximity user data table 740 based on the converted query.
  • the input and output value query module 734 queries the data of the service with the specific input and result values present in the proximity user data table 740 based on the converted query.
  • the classification query module 735 queries the data of the service having a particular classification present in the proximity user data table 740 based on the converted query.
  • the user query module 732, the terminal query module 733, the input and output value query module 734, and the service query module 735 may receive the query and query the data at the same time, or the transformation module 731 may query the query. If one of the user query module (732), the terminal query module (733), the input and output value query module (734), and the service query module (735) can search for data, You may.
  • the providing module 736 outputs video / audio to the host terminal the result data inquired by the user query module 732, the terminal query module 733, the input and output value query module 734, and the service query module 735. Provided through wealth.
  • the providing module 736 may also provide the inquired result data to at least one terminal of the plurality of terminals.
  • the result data provided by the providing module 736 is sent to the conversion module 731 and converted into JSON format.
  • the query processing apparatus 700 stores and manages data received from a plurality of terminals, thereby providing data of other users to the user so that necessary data can be shared with each other.
  • FIG. 8 illustrates a procedure of processing a query based on data stored in a meta knowledge database according to a method of processing a query according to an embodiment of the present invention.
  • FIG. 7 illustrates a procedure of processing a query based on data stored in a meta knowledge database according to a method of processing a query according to an embodiment of the present invention.
  • the query providing method is initiated by the initialization module 710 receiving data on at least one of a terminal, a service, and a user (S810).
  • the initialization module 710 receives data for at least one of a terminal, a service, and a user from a plurality of terminals existing in the same network or local area.
  • the data about the terminal means a terminal type such as a tablet PC or a smart phone, a specification of the terminal, a terminal name, and a terminal ID.
  • a service is a program installed in a terminal that provides a specific function to a user, that is, an application.
  • the data for a service is the name, input values, output values, classifications, data contained in the service, and the service URI.
  • the data for the user is the name of the terminal user. Data for at least one of the terminal, service, and user is translated into the language in which the proximity user data table is to be written.
  • the initialization module 710 generates a proximity user data table (S820).
  • the initialization module 710 generates a proximity user data table including data received from the plurality of terminals.
  • the proximity user data table 740 includes terminal ID, user ID, user name, terminal name information, terminal type, terminal specification, service name information, input of service, output of service, classification of service and service URI. .
  • a detailed structure of the proximity user data table will be described later with reference to FIG. 5.
  • the initialization module 710 can generate the proximity user data table 240 in SQL.
  • the data management module 720 changes or changes new data from at least one terminal of the plurality of terminals. It is possible to update the proximity user data table 740 by receiving. Here, the received new or changed data is converted into the language in which the proximity user data table is written and stored in the proximity user data table 740.
  • the query module 730 receives the query and processes the query by accessing the proximity user data table (S830).
  • the query module 730 processes the query by accessing the proximity user data table 740 to receive the query from the host terminal and perform the query.
  • the query is a query for receiving data of a service related to a user, a query for receiving data of a service related to a terminal type, a query for receiving data of a service having an input value and an output value, and a data of a service having a classification.
  • the search word may be provided.
  • the query for receiving data of the service related to the user may be the name of the user.
  • the query for receiving data of a service related to the terminal type may be a terminal type, that is, a smart phone or a tablet PC.
  • a query for receiving data of a service having an input value and an output value may be a type of a service input value and a type of a service output value.
  • the query for the calendar application may be an event that is a date and a service output value that are input values of the calendar application.
  • the date and event means that the type of the input value of the service is the date, and the type of the output value of the service is the event, not the actual date and the event such as the meeting.
  • the query for receiving data of a service having a classification may be calendar, contact, weather, etc., which is a classification of an application. Because the query is in JSON format, it is translated into the language in which the proximity user data table is written to access the proximity user data table. Thus, query module 730 accesses a proximity user data table to provide data associated with the query.
  • the query module 730 provides processed result data (S840).
  • the query module 730 has a query for receiving data of a service related to a user, a query for receiving data of a service related to a terminal type, a query for receiving data of a service having an input value and an output value, and a classification.
  • Provides result data which is data associated with at least one of the queries for receiving data of the service.
  • the result data may be a service name and a URI.
  • the query module 730 may select and provide common data according to a predetermined priority or more than a predetermined number of terminals. In detail, when there is a plurality of data associated with a query, the query module 730 may select and provide data according to a predetermined priority. For example, if the data associated with the query is XXX calendar, YYY calendar, ZZZ calendar, AAA calendar, the predetermined priority of the data to be provided is YYY calendar, followed by ZZZ calendar, AAA calendar, XXX calendar. Accordingly, query module 730 provides the service name and URI in the order of YYY calendar, ZZZ calendar, AAA calendar, XXX calendar.
  • the query module 730 may select and provide common data of more than a predetermined number of terminals. For example, when a service query called calendar is received in the query module 730, the calendar service is accessed from the proximity user data table 740 to retrieve a name of a terminal and a calendar service using the calendar service. Accordingly, when there is data that five terminals use the XXX calendar and two terminals use the YY calendar, the query module 730 may select and provide XXX calendars that are four or more pieces of common data, which is a predetermined number of terminals. The result data provided by the query module 730 is converted into a JSON format and provided. Detailed result data will be described later with reference to FIG. 9.
  • the query processing apparatus stores data received from a plurality of terminals to provide the user with data according to priority or common data over a predetermined number of terminals so that the user can obtain accurate and various data.
  • FIG. 9 schematically illustrates an apparatus for processing a query according to an embodiment of the invention.
  • the query processing apparatus may include a user name 410, a terminal type 420, a service name 430, a service classification 440, a service input value 450, and a service output value from the terminal.
  • 460 receives data about the terminal, the service, and the user, and stores the data in the proximity user data table.
  • the data are semantically matched with each other.
  • semantic matching means that data is matched so that the device can understand the meaning of the data and even make logical inference.
  • the query processing apparatus when a query for which the user name 910 is Hong Gil Dong is received, the query processing apparatus provides a service name and URI used by Hong Gil Dong.
  • the query processing apparatus when a query is received in which the terminal type 920 is a smartphone, the query processing apparatus provides a service name and a URI used in the smartphone.
  • the query processing device When a query is received whose service classification 930 is calendar, the query processing device provides the name and URI of the calendar service being used, and receives a query whose service input value 950 and service output value 960 are dates and events. If so, the query processing apparatus provides the name and URI of the service using the date and event as the service input value 950 and service output value 960.
  • the query processing apparatus may provide the result data for the query as well as the name and URI of the service as well as all data associated with the query, i.e., meta knowledge.
  • the service classification 930 all user names 910, terminal types 920, and service names 940 using services of the classification corresponding to the query may be provided.
  • the service classification 930 using the service input value 950 and the service output value 960 corresponding to the query, the service name. 940 and data of a user name 910 and a terminal type 920 using the corresponding service may be provided.
  • the query processing apparatus collects a user name, a terminal type, a service name, a service classification, a service input value, and a service output value using a semantic matched terminal from a plurality of terminals, and provides the user with query result data. do.
  • FIG. 10 illustrates a structure of a proximity user data table included in a meta knowledge database constructed according to another embodiment of the present invention.
  • the proximity user data table 1000 includes data of at least one of a terminal, a service, and a user from a plurality of terminals.
  • the data for the terminal includes the terminal ID, the terminal name and the terminal type.
  • the data for the service includes a service name, a service input value, a service output value, a service classification, and a service URI
  • the data for the user includes a user ID and a user name.
  • the proximity user data table 500 is composed of ten columns and may be written in SQL.
  • the proximity user data table 1000 includes first data 1010 that is data about a terminal, a service, and a user received from a terminal having a terminal ID of 0.
  • the first data 1010 includes a terminal ID value of 0, a user ID value of 0, a user name value of Hong Gil-dong, a terminal type value of a smartphone, and a terminal name value of GalaxyX4.
  • the first data 1010 may include a XXX calendar, which is a service name value used by the user Hong Gil-dong, date data such as a service input value that is input into the XXX calendar, such as 2015.12.23, and a 3 o'clock meeting, which is a service output value output according to the service input value.
  • the first data 1010 is a contact list which is another service name value used by the user Hong Gil-dong, name data such as Kim Young-hee which is a service input value input to the contact list, and a service output value 010-1234-5678 which is output according to the service input value.
  • Telephone number data such as a contact list, which is a classification value of a contact list, and a URI value of a contact list.
  • the proximity user data table 1000 includes second data 1020, which is data about a terminal, a service, and a user, received from a terminal having a terminal ID value of 1.
  • the second data 1020 includes a terminal ID value of 1, a user ID value of 1, a user name value of Kim Chul-soo, a terminal type value of a smartphone, and a terminal name value of GalaxyY6.
  • the second data 1020 may include YY weather, which is a service name value used by the user, Kim Chul Soo, date data such as service input values, which are input into YY weather, such as 12/12/2015, and cloudiness and weather data, which are service output values that are output according to service input values.
  • the URI values for weather and YY weather which are classification values for YY weather.
  • the proximity user data table 1000 may additionally include data according to the service regardless of the type of service and the size of the data when there is another service used by the user.
  • the terminal ID and the user ID may be assigned in the order of data input to the proximity user data table 1000, or may be assigned a random number.
  • the query processing apparatus receives data about a terminal, a service, and a user from a plurality of terminals, and generates a proximity user data table including the received data, thereby expanding the data including a plurality of user related information to the user. That is, the result data generated based on the meta knowledge can be provided, and the data can be provided at a high speed because the data is classified according to the criteria.
  • each block or each step may represent a portion of a module, segment or code containing one or more executable instructions for executing a specified logical function (s). It should also be noted that in some alternative embodiments the functions noted in the blocks or steps may occur out of order. For example, the two blocks or steps shown in succession may in fact be executed substantially concurrently or the blocks or steps may sometimes be performed in the reverse order, depending on the functionality involved.
  • the steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, software module, or a combination of the two executed by the processor 110.
  • the software module may be RAM memory 140, flash memory 140, ROM memory 140, EPROM memory 140, EEPROM memory 140, registers, hard disk, removable disk, CD-ROM or any known in the art. May reside in other forms of storage media.
  • An exemplary storage medium is coupled to the processor 110, which can read information from and write information to the storage medium.
  • the storage medium may be integral to the processor 110.
  • the processor 110 and the storage medium may reside within an application specific integrated circuit (ASIC).
  • the ASIC may reside in a user terminal.
  • the processor 110 and the storage medium may reside as discrete components in a user terminal.

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  • Computer Hardware Design (AREA)
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  • General Engineering & Computer Science (AREA)
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  • Data Mining & Analysis (AREA)
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  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

La présente invention concerne un procédé et un dispositif d'établissement de base de données de métaconnaissances et de traitement d'une interrogation, et le procédé d'établissement d'une base de données de métaconnaissances et de traitement d'une interrogation, conformément à la présente invention, qui comprend les étapes consistant : à extraire au moins un mot-clé à partir d'une interrogation ; à récupérer les métaconnaissances à partir d'une base de données de métaconnaissances au moyen des mots-clés ; à générer une réponse pour l'interrogation au moyen des informations contenues dans les métaconnaissances ; à recevoir des données sur au moins un terminal, un service, et un utilisateur en provenance du même réseau ou une pluralité de terminaux à l'intérieur d'une courte distance ; à générer une table de données utilisateur proche comprenant les données reçues ; à traiter l'interrogation en recevant l'interrogation et en accédant la table de données utilisateur proche ; et à fournir les données de résultat traité, ce qui permet d'établir efficacement les bases de données de métaconnaissances sur la base des métaconnaissances, et à traiter l'interrogation.
PCT/KR2016/000087 2015-02-23 2016-01-06 Procédé et dispositif d'établissement de base de données de métaconnaissances et de traitement d'interrogation WO2016137114A1 (fr)

Applications Claiming Priority (6)

Application Number Priority Date Filing Date Title
KR10-2015-0025368 2015-02-23
KR20150025368 2015-02-23
KR10-2015-0068884 2015-05-18
KR1020150068884A KR101653256B1 (ko) 2015-02-23 2015-05-18 사용자 질의 응답을 위한 메타지식데이터베이스 구축 방법
KR1020150190848A KR101743731B1 (ko) 2015-12-31 2015-12-31 분산된 데이터를 통합하여 생성한 온톨로지를 기반으로 쿼리를 처리하는 방법 및 장치
KR10-2015-0190848 2015-12-31

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