Various Techniques of Sentence Embedding using Question-Answering in Game Play

• 영문명: Various Techniques of Sentence Embedding using Question-Answering in Game Play
• 발행기관: 한국컴퓨터게임학회
• 저자명: Trieu Thanh Ngoan 이원형(Won-Hyung LEE)
• 간행물 정보: 『한국컴퓨터게임학회논문지』제35권 4호, 69~80쪽, 전체 12쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2022.12.31

영문 초록

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

1. Introduction

2. Related Research Work

3. PROPOSED METHODOLOGY

4. EXPERIMENTAL ANALYSIS AND COMPARISON OF THE SENTENCE EMBEDDING MODEL

5. Conclusion

Acknowledgemnt

Reference

키워드

Question-Answering Sentence Embedding Game Play