Special Session- New research introduction

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  • Special Session- New research introduction
▶ 인공지능 기술 제품 적용 사례

▶ Discovery of topic flows of authors

       

정영섭 교수(순천향대)

학력
한국과학기술원 전산학과 박사
한국과학기술원 전산학과 석사
한양대학교 컴퓨터공학과 학사

경력
네이버 랩스 연구원

연구분야
- 토픽모델링을 통한 연구토픽 흐름 분석
- 인공신경망을 이용한 스마트폰 소지방식 예측
- 토픽모델링을 통한 이미지 세그멘테이션
- 한국어 문서로부터의 시간 정보 추출

관심분야
- 텍스트 마이닝
- 인공지능형 대화시스템
- 센서 기반 행동인식

강의제목

Discovery of topic flows of authors

강의요약

With an increase in the number of Web documents, the number of proposed methods for knowledge discovery on Web documents have been increased as well. The documents do not always provide keywords or categories, so unsupervised approaches are desirable, and topic modeling is such an approach for knowledge discovery without using labels. Further, Web documents usually have time information such as publish years, so knowledge patterns over time can be captured by incorporating the time information. The temporal patterns of knowledge can be used to develop useful services such as a graph of research trends, finding similar authors (potential co-authors) to a particular author, or finding top researchers about a specific research domain. In this paper, we propose a new topic model, Author Topic-Flow (ATF) model, whose objective is to capture temporal patterns of research interests of authors over time, where each topic is associated with a research domain. The state-of-the-art model, namely Temporal Author Topic model, has the same objective as ours, where it computes the temporal patterns of authors by combining the patterns of topics. We believe that such ‘indirect’ temporal patterns will be poor than the ‘direct’ temporal patterns of our proposed model. The ATF model allows each author to have a separated variable which models the temporal patterns, so we denote it as ‘direct’ topic flow. The design of the ATF model is based on the hypothesis that ‘direct’ topic flows will be better than the ‘indirect’ topic flows. We prove the hypothesis is true by a structural comparison between the two models and show the effectiveness of the ATF model by empirical results.

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