Earticle

초록

영어

Automatic question-answering is a classical problem in natural language processing, which aims at designing systems that can automatically answer a question, in the same way as human does. The need to query information content available in various formats including structured and unstructured data has become increasingly important. Thus, Question Answering Systems (QAS) are essential to satisfy this need. QAS aim at satisfying users who are looking to answer a specific question in natural language.Moreover, it is a representative of open domain QA systems, where the answer selection process leans on syntactic and semantic similarities between the question and the answering text snippets. Such approach is specifically oriented to languages with fine grained syntactic and morphologic features that help to guide the correct QA match. Furthermore, word and sentence embedding have become an essential part of any Deep-Learning-based natural language processing systems as they encode words and sentences in fixed-length dense vectors to drastically improve the processing of textual data. The paper will concentrate on incorporating the sentence embedding with its various techniques like Infersent, ElMo and BERT in the construction of Question Answering systems, and also it can be used in game play.

목차

ABSTRACT
1. Introduction
2. Related Research Work
3. PROPOSED METHODOLOGY
3.1 Stanford Question Answering Dataset (SQuAD):
3.2 PRE-PROCESSING:
3.3 FLOW OF THE QUESTION-ANSWERING
3.4 VARIOUS TECHNIQUES USED FOR BUILDING THE SYSTEM
4. EXPERIMENTAL ANALYSIS AND COMPARISON OF THE SENTENCE EMBEDDING MODEL
4.1 APIs used for evaluation:
4.2. Results after testing each model on datasets
5. Conclusion
Acknowledgemnt
Reference

키워드

저자

• Trieu Thanh Ngoan [ College of IInformation and Communication Technology, Can Tho University, Vietnam ]
• Won-Hyung LEE [ Graduate School of A.I.M., Chung-Ang University ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  컴퓨터게임및콘텐츠논문지(구 한국컴퓨터게임학회논문지) [Journal of Computer Games and Contents]

• 간기

  월간

• pISSN

  3091-7409

• eISSN

  3092-3638

• 수록기간

  2002~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 691 DDC 793