Abstract:
Provided is a natural language query answering method. The natural language query answering method includes generating a query axiom from an input query, generating answer candidates from the input query, filtering the answer candidates based on a similarity between the query axiom and the answer candidates, reasoning out the answer candidates by using at least one of an inductive reasoning method, a deductive reasoning method, and an abductive reasoning method, calculating reliability of the answer candidates, determining ranks of the answer candidates based on the calculated reliability, and comparing a threshold value with a reliability ratio of reliability of an answer candidate determined as No. 1 rank to reliability of an answer candidate determined as No. 2 rank, readjusting the determined ranks according to a result of the comparison, and detecting a No. 1 rank answer candidate, determined through the readjustment, as a final answer.
Abstract:
The present disclosure relates to an apparatus for outputting a language model from which a bias has been removed. The apparatus according to the present disclosure includes a bias estimation model configured to estimate a bias of text to be generated, a bias determination unit configured to determine a bias of next text to be generated through the bias estimation model, and a deep learning-based text generation model configured to generate the next text based on a result of the determination of the bias of the next text.
Abstract:
Provided is a system for creating a news article containing an indirect advertisement, the system including an advertisement database including an advertisement item and an indirect advertisement composed of text matching the advertisement item, an advertisement search unit configured to, when a text-type original news article to be exposed to a webpage is input, search the database for an indirect advertisement candidate matching the original news article and select an advertisement candidate list, an advertisement position determination unit configured to determine a paragraph of the original news article into which a selected advertisement is to be inserted, and an advertisement phrase creation unit configured to create a news article containing an advertisement by inserting the selected advertisement into the paragraph of the original news article and expose the created news article.
Abstract:
Provided is a method of providing a shared neural model by a question-answering system, the method including: learning a shared neural model on the basis of initial model learning data; providing a plurality of user terminals with the shared neural model upon completing the learning of the shared neural model; upon the user terminal updating the shared neural model to a personalized neural model, collecting the updated personalized neural model; updating the shared neural model on the basis of the collected personalized neural model; and providing the updated shared neural model to the plurality of user terminals.
Abstract:
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.
Abstract:
An apparatus and method for updating a language analysis result are provided. The apparatus includes a storage unit configured to store language analysis result and language analysis metadata to be used for update of the language analysis result, and an update unit configured to reanalyze the language analysis metadata based on language knowledge which is added to language knowledge resources, and update the language analysis result based on the reanalyzed result.
Abstract:
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.
Abstract:
A system and method for constructing a morpheme dictionary based on an automatic extraction of a non-registered word is provided. A non-registered word is automatically extracted based on a language-independent non-registered word automatic extraction method, and performance of a dictionary and a morpheme analysis is verified based on an automatic estimation by constructing a morpheme dictionary based on the automatically extracted non-registered word. Since the morpheme dictionary is constructed using only a dictionary in which a final verification is passed and it is helpful to improve the performance, the morpheme analysis can be properly performed on the non-registered word of a new field or a new word which newly appears as time passes.
Abstract:
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.
Abstract:
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.