• Title, Summary, Keyword: question answering

Search Result 220, Processing Time 0.041 seconds

Literature Review of Queston Taxonomy for Developing User-participatory Reference Service (이용자 참여형 참고 서비스 개발을 위한 질문 유형 구분에 대한 문헌적 고찰)

  • Park, Jong-Do
    • Journal of the Korean Society for Library and Information Science
    • /
    • v.49 no.4
    • /
    • pp.401-417
    • /
    • 2015
  • Question taxonomy is one of main approaches to understand the questioner's information need so that we can assign relevant answerers to the question submitted by the user. The goal of this study is to investigate question taxonomy of question and answering services, which are available online and in libraries and understand the characteristics of question answering services by type. In order to achieve the goal, this study examines the types of questions appeared in literature, specifically focusing on social reference, question answering systems, and reference services, and then provides a summary of question taxonomy found in question answering services.

Korean TableQA: Structured data question answering based on span prediction style with S3-NET

  • Park, Cheoneum;Kim, Myungji;Park, Soyoon;Lim, Seungyoung;Lee, Jooyoul;Lee, Changki
    • ETRI Journal
    • /
    • v.42 no.6
    • /
    • pp.899-911
    • /
    • 2020
  • The data in tables are accurate and rich in information, which facilitates the performance of information extraction and question answering (QA) tasks. TableQA, which is based on tables, solves problems by understanding the table structure and searching for answers to questions. In this paper, we introduce both novice and intermediate Korean TableQA tasks that involve deducing the answer to a question from structured tabular data and using it to build a question answering pair. To solve Korean TableQA tasks, we use S3-NET, which has shown a good performance in machine reading comprehension (MRC), and propose a method of converting structured tabular data into a record format suitable for MRC. Our experimental results show that the proposed method outperforms a baseline in both the novice task (exact match (EM) 96.48% and F1 97.06%) and intermediate task (EM 99.30% and F1 99.55%).

Deep Analysis of Question for Question Answering System (질의 응답 시스템을 위한 질의문 심층 분석)

  • Shin Seung-Eun;Seo Young-Hoon
    • The Journal of the Korea Contents Association
    • /
    • v.6 no.3
    • /
    • pp.12-19
    • /
    • 2006
  • In this paper, we describe a deep analysis of question for question answering system. It is difficult to offer the correct answer because general question answering systems do not analyze the semantic of user's natural language question. We analyze user's question semantically and extract semantic features using the semantic feature extraction grammar and characteristics of natural language question. They are represented as semantic features and grammatical morphemes that consider semantic and syntactic structure of user's questions. We evaluated our approach using 100 questions whose answer type is a person in the web. We showed that a deep analysis of questions which are comparatively short but enough to mean can analysis the user's intention and extract semantic features.

  • PDF

A Natural Language Question Answering System-an Application for e-learning

  • Gupta, Akash;Rajaraman, Prof. V.
    • Proceedings of the Korea Inteligent Information System Society Conference
    • /
    • /
    • pp.285-291
    • /
    • 2001
  • This paper describes a natural language question answering system that can be used by students in getting as solution to their queries. Unlike AI question answering system that focus on the generation of new answers, the present system retrieves existing ones from question-answer files. Unlike information retrieval approaches that rely on a purely lexical metric of similarity between query and document, it uses a semantic knowledge base (WordNet) to improve its ability to match question. Paper describes the design and the current implementation of the system as an intelligent tutoring system. Main drawback of the existing tutoring systems is that the computer poses a question to the students and guides them in reaching the solution to the problem. In the present approach, a student asks any question related to the topic and gets a suitable reply. Based on his query, he can either get a direct answer to his question or a set of questions (to a maximum of 3 or 4) which bear the greatest resemblance to the user input. We further analyze-application fields for such kind of a system and discuss the scope for future research in this area.

  • PDF

Concept-based Question Answering System

  • Kang Yu-Hwan;Shin Seung-Eun;Ahn Young-Min;Seo Young-Hoon
    • International Journal of Contents
    • /
    • v.2 no.1
    • /
    • pp.17-21
    • /
    • 2006
  • In this paper, we describe a concept-based question-answering system in which concept rather than keyword itself makes an important role on both question analysis and answer extraction. Our idea is that concepts occurred in same type of questions are similar, and if a question is analyzed according to those concepts then we can extract more accurate answer because we know the semantic role of each word or phrase in question. Concept frame is defined for each type of question, and it is composed of important concepts in that question type. Currently the number of question type is 79 including 34 types for person, 14 types for location, and so on. We experiment this concept-based approach about questions which require person s name as their answer. Experimental results show that our system has high accuracy in answer extraction. Also, this concept-based approach can be used in combination with conventional approaches.

  • PDF

Question and Answering System through Search Result Summarization of Q&A Documents (Q&A 문서의 검색 결과 요약을 활용한 질의응답 시스템)

  • Yoo, Dong Hyun;Lee, Hyun Ah
    • KIPS Transactions on Software and Data Engineering
    • /
    • v.3 no.4
    • /
    • pp.149-154
    • /
    • 2014
  • A user should pick up relevant answers by himself from various search results when using user participation question answering community like Knowledge-iN. If refined answers are automatically provided, usability of question answering community must be improved. This paper divides questions in Q&A documents into 4 types(word, list, graph and text), then proposes summarizing methods for each question type using document statistics. Summarized answers for word, list and text type are obtained by question clustering and calculating scores for words using frequency, proximity and confidence of answers. Answers for graph type is shown by extracting user opinion from answers.

Strategies for Improving Electronic Question/Answering Function for the Activation of Archival Information Service of National Archives & Records Service (기록정보서비스 활성화를 위한 전자적 질의/응답 기능 개선방안 - 국가기록원을 중심으로 -)

  • Woo, Su-Young
    • Journal of Korean Society of Archives and Records Management
    • /
    • v.6 no.1
    • /
    • pp.113-136
    • /
    • 2006
  • This study aims for the above mentioned. After all, through the analysis of Electronic Question/Answering Function to understand a user's demand under online circumstances, groping for the method to provide an appropriate Archival Information Service is the most important thing. For this, in this study, it researched the users interviews and the research related to users as a precedence study, and the studies having examined the state of demanding information by users through analyzing the e-mail actually. Additionally, by looking over the study of Library and Information Science that is activated in a field of Electronic Question/Answering Function rather than Archival Science, as a matter of fact, the study has come up with the standard for analyzing Electronic Question/Answering Function. And based on the precedence study, the instances for the National Archives from USA, England, Australia and Canada were analyzed, and the chance of activating Archival Information Service were tried to grope for in the study. This study might be one of methodologies in examining the users study that is not activated yet in Archival Science. Therefore, the users study can be carried out in various methods as well as Electronic Archives/Answering Service. This study might be the important information in providing far better Archival Information Services. It is desirable that based on this opportunity, the study related to the various users by examining not only Electronic Archives/Answering Function but also Question/Answering of the users and the Archivists in the filed to the larger extend will be activated for Archival Science.

Experimental Analysis of Correct Answer Characteristics in Question Answering Systems (질의응답시스템에서 정답 특징에 관한 실험적 분석)

  • Han, Kyoung-Soo
    • Journal of Digital Contents Society
    • /
    • v.19 no.5
    • /
    • pp.927-933
    • /
    • 2018
  • One of the factors that have the greatest influence on the error of the question answering system that finds and provides answers to natural language questions is the step of searching for documents or passages that contain correct answers. In order to improve the retrieval performance, it is necessary to understand the characteristics of documents and passages containing correct answers. This paper experimentally analyzes how many question words appear in the correct answer documents, how the location of the question word is distributed, and how the topic of the question and the correct answer document are similar using the corpus composed of the question, the documents with correct answer, and the documents without correct answer. This study explains the causes of previous search research results for question answer system and discusses the necessary elements of effective search step.

Answer Pattern for Definitional Question-Answering System (정의형 질의응답 시스템을 위한 정답 패턴)

  • Seo Young-Hoon;Shin Seung-Eun
    • The Journal of the Korea Contents Association
    • /
    • v.5 no.3
    • /
    • pp.209-215
    • /
    • 2005
  • In this paper, we describe the answer pattern for definitional question-answering system. The .answer extraction method of a definitional question-answering system is different from the general answer extraction method because it presents the descriptive answer for a definitional question. The definitional answer extraction using the definitional answer pattern can extract the definitional answer correctly without the semantic analysis. The definitional answer pattern is consist of answer pattern, conditional rule and priority to extract the correct definitional answer. We extract the answer pattern from the definitional training corpus and determine the optimum conditional rule using F-measure. Next, we determine the priority of answer patterns using precision and syntactic structure. Our experiments show that our approach results in the precision(0.8207), the recall(0.9268) and the F-measure(0.8705). It means that our approach can be used efficiently for a definitional question-answering system.

  • PDF

Semantic Fuzzy Implication Operator for Semantic Implication Relationship of Knowledge Descriptions in Question Answering System (질의 응답 시스템에서 지식 설명의 의미적 포함 관계를 고려한 의미적 퍼지 함의 연산자)

  • Ahn, Chan-Min;Lee, Ju-Hong;Choi, Bum-Ghi;Park, Sun
    • The Journal of the Korea Contents Association
    • /
    • v.11 no.3
    • /
    • pp.73-83
    • /
    • 2011
  • The question answering system shows the answers that are input by other users for user's question. In spite of many researches to try to enhance the satisfaction level of answers for user question, there is a essential limitation. So, the question answering system provides users with the method of recommendation of another questions that can satisfy user's intention with high probability as an auxiliary function. The method using the fuzzy relational product operator was proposed for recommending the questions that can includes largely the contents of the user's question. The fuzzy relational product operator is composed of the Kleene-Dienes operator to measure the implication degree by contents between two questions. However, Kleene-Dienes operator is not fit to be the right operator for finding a question answers pair that semantically includes a user question, because it was not designed for the purpose of finding the degree of semantic inclusion between two documents. We present a novel fuzzy implication operator that is designed for the purpose of finding question answer pairs by considering implication relation. The new operator calculates a degree that the question semantically implies the other question. We show the experimental results that the probability that users are satisfied with the searched results is increased when the proposed operator is used for recommending of question answering system.