Electronics and Telecommunications Research Institute

Myung Gil Jang

Jeong Mu Heo

Chung Hee Lee

Hyun Ki Kim

Mi Ran Choi

Yong Jin Bae

Soo Jong Lim

Joon Ho Lim

Hyo Jung Oh

Pum Mo Ryu

Yeo Chan Yoon

Ji Hyun Wang

Hyung Jik Lee

Sang Kyu Park

Hyo-Jung Oh

Soojong Lim

Miran Choi

Hyunki Kim

Hyeon Jin Kim

Changki Lee

Chang Ki Lee

Yi Gyu Hwang

Yo Han Jo

Yoon Jae Choi

Kyung Man Bae

Min Ho Kim

Eui Sok Chung

YiGyu Hwang

Ji Hee Ryu

Hyun Suk Kim

Young Jik Lee

Chee Sun Won

Soo-Jun Park

Sung Hee Park

Young Rae Kim

Ji Ae Shin

Soojung Lim

Dong-Kwon Park

Hyunjin Kim

Yoonjae Choi

The present invention relates to an apparatus and method for automatically generating machine reading comprehension training data, and more particularly, to an apparatus and method for automatically generating and managing machine reading comprehension training data based on text semantic analysis. The apparatus for automatically generating machine reading comprehension training data according to the present invention includes a domain selection text collection unit configured to collect pieces of text data according to domains and subjects, a paragraph selection unit configured to select a paragraph using the pieces of collected text data and determine whether questions and correct answers are generatable, and a question and correct answer generation unit configured to generate questions and correct answers from the selected paragraph.

Apparatus and method for automatic generation of machine reading comprehension training data

A chatbot system and method conversing with other chatbots in place of a user. The chatbot system and method understand the purpose of conversation of a user, select chatbots to which the purpose of the user is to be transferred, converse with the selected chatbots in place of the user, and present the user with a result of conversation undertaken. The chatbot system converses with provider chatbots provided by property and service providers. The chatbot system includes a consumer chatbot that understands a purpose of conversation of a user, converses with the provider chatbots in place of the user, and provides a result of the conversation to the user.

Chatbot system and service method thereof

The language analysis method includes collecting an online document, performing coined word filtering on the collected document based on a predetermined coined word extraction pattern and a dictionary to extract a coined word candidate which corresponds to the coined word extraction pattern and is not registered in a coined stop word dictionary, performing morpheme analysis on the extracted coined word candidate to verify a coined word candidate which does not correspond to a predetermined part of speech and is not registered in a pre-stored morpheme dictionary, refining the coined word extraction pattern, based on a result of the verification and updating the verified coined word candidate in the coined stop word dictionary, and updating the verified coined word candidate in the morpheme dictionary, based on the result of the verification.

Online contextual advertisement intellectualization apparatus and method based on language analysis for automatically recognizing coined word

Provided are an interactive question answering apparatus and method, which improve an unnatural question sentence and prevent the impossibility of a question in a state which does not know additional information, thereby providing a multimodal-based question answering method enabling a person to provide a question like conversing. Also, a question answering service is exposed to potential product purchasers of content such as an image, video, audio, etc., thereby providing an environment available to advertisement market.

Interactive question-answering apparatus and method thereof

Provided are a system and method for answering a natural language question which show improved information retrieval performance. The system includes an index unit configured to analyze text of previously stored irregular documents and classify and index the irregular documents according to meanings of sentences or paragraphs, a database configured to receive and store the irregular documents indexed according to the meanings and transmitted from the index unit, a retrieval unit configured to extract an index word by semantically analyzing an input question and search the database for documents related to the extracted index word, and a provision unit configured to generate a correct answer to the question by analyzing the documents searched by the retrieval unit and provide the search results and the correct answer.

System and method for answering natural language question

An apparatus for amending a language analysis error includes: a main language analyzer, which includes a plurality of language processing modules being sequentially connected to each other, and generates one best main analysis result for each processing module; a subsidiary language analyzer, which includes the plurality of language processing modules, and generates a plurality of subsidiary analysis results for each of the plurality of language processing modules; and an analysis result amender to in response to an error occurring in the main analysis result, acquire a subsidiary analysis result, and transmit the subsidiary analysis result to the main language analyzer.

Apparatus and method for amending language analysis error

Disclosed are a question answering system for structured knowledgebase using deep natural language question analysis, and a method thereof, the question answering system for structured knowledgebase using deep natural language question analysis includes a deep natural language question analysis unit configured to create a structure of a semantic frame by analyzing a natural language question that is input, a question-intermediate expression creation unit configured to create a question-intermediate expression of a lexicon level based on the semantic frame, a knowledgebase-specialized query creation unit configured to create a query used to search in knowledgebase that is a subject of search, based on the question-intermediate expression, and a knowledgebase search unit configured to find a correct answer in the knowledgebase that is subject of search based on the query, to provide an accuracy of the correct answer, a confidence of the correct answer and an evidence for the correct answer.

Question answering system and method for structured knowledgebase using deep natural language question analysis

A natural language question answering system and method, and a paraphrase module are provided. The natural language question answering system includes a conversion module configured to generate a plurality of modified questions by paraphrasing a user's question; a plurality of question answering engines configured to receive each of the user's question and the modified questions, and select candidate answers corresponding to each of the user's question and the modified questions; and a detection module configured to detect at least one among the selected candidate answers as an answer.

Natural language question answering system and method, and paraphrase module

Disclosed are an apparatus, a system, and a method for searching for a power user in social media. The apparatus according to the present invention includes an input unit configured to receive a keyword corresponding to an interested object from a user; a communication unit configured to transmit a search request message including the received keyword and receive a search response message corresponding to the transmitted search request message; a controller configured to, when receiving the search response message, extract a search list in which power users related to the keyword are arranged according to a preset power ranking from the received search response message; a display unit configured to sequentially display the power users related to the keyword received from the user according to the preset power ranking based on the extracted search list; and a storage unit configured to store the extracted search list.

Apparatus, system, and method for searching for power user in social media

Disclosed are an apparatus, a system, and a method for detecting complex issues based on social media analysis according to the present invention. A system for detecting complex issues based on social media analysis according to the present invention includes: a unit issue detecting unit configured to receive a keyword from a user terminal, and to detect per-type unit issues associated with the received keyword; a complex issue detecting unit configured to detect per-type complex issues from the detected per-type unit issues; a complex issue ranking unit configured to analyze the detected per-type complex issues, and to rank the per-type complex issues based on the analysis result; and a complex issue configuring unit configured to configure the ranked per-type complex issues in a predetermined form that enable users to induce a micro trend, and to provide the configured form to a user.

Apparatus, system, and method for detecting complex issues based on social media analysis

The present invention relates to a social media question and answer service, and discloses a social media issue processing device and method. The method includes a question analyzing unit which analyzes a question type of an input question through a question pattern dictionary which is stored in advance; a social media analyzing unit which performs issue period recognition for the question, question type based analysis, question based summary creation, and question based reliability calculation; and a report creating unit which creates a summary in accordance with at least one of correlation between the question type and the question based summary, correlation between the issue period and the question type based analysis result, and correlation between the reliability and the question based summary.

Processing method for social media issue and server device supporting the same

A question type and domain identifying apparatus includes: a question type identifier for recognizing the number of words of a user's question to identify whether the user's question is a query for performing information searching or a question for performing a question and answer (Q&A); a question domain distributor for distributing one of plural preset domain specialized Q&A engines, as a Q&A engine of the user's question based on the recognized word number; and a Q&A engine block, including the domain specialized Q&A engines, for selectively performing information searching or a Q&A with respect to the user's question in response to the distribution of the question domain distributor.

Question type and domain identifying apparatus and method

A topic map based indexing apparatus analyzes community Q/A lists to acquire Q/A analysis information, removes redundant answers depending on the Q/A analysis information, removes insignificant answers based on the degree of reliability, ranks answer lists, and extracts the highest ranking answer as a best answer, to thereby store, in a community Q/A topic map, index information containing the community Q/A lists and the Q/A analysis information. A topic map based searching apparatus analyzes a user question to acquire question analysis information, searches similar questions from community Q/A lists belonging to a specific topic node of a pre-stored community Q/A topic map, ranks the searched similar questions depending on the question analysis information, removes redundant answers among answers to the ranked similar questions, ranks the answers, and extracts the highest ranking answer as a best answer.

Topic map based indexing and searching apparatus

An apparatus for verifying training data using machine learning includes: a training data separation unit for separating provided initial training data into N training data and N verification data, where N is a natural number; a machine learning unit for performing machine learning on the separated training data to generate a training model; an automatic tagging unit for automatically tagging an original text of the verification data using the generated training model to provide automatic tagging results; and an error determination unit for comparing the verification data to the automatic tagging results to determine error candidates of the training data.

Apparatus and method for verifying training data using machine learning

A method for stabilizing a knowledge graph includes: generating a knowledge graph in which same entities in a semantic relation list between entities provided as an input are represented as a single node based on names and types of the entities; computing, on the knowledge graph, semantic similarities between all potential entity pairs of same entity types by comparing, for each potential entity pair, a type of relation associated with an entity in the entity pair and an opponent entity to the entity; and selecting, based on the semantic similarities, a representative entity from each of semantically similar entity pairs on the knowledge graph and integrating an opponent entity to the representative entity into the representative entity. The method further includes computing relation weighted values between the entities by using a graph analysis and statistic information, and adding the weighted values to the knowledge graph.

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Daejeon, South Korea

Myung Gil Jang