Presentation 2017-11-24
A Web Contents Classification by The Context
Tomomi Sanjo, Akito Sakurai,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) Nowadays, it is getting popular to find some information on the Internet so that many sites turn to have similar information. Therefore if a user want to find information by searching, the user should find appropriate combination of words for searching. Otherwise the searching results are massive and messy. To solve the problem, we built a service that provides pages with similar meanings sorted in relevance order.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) web contents / Doc2Vec / supervised learning / classificatio / context / LDA
Paper # AI2017-11
Date of Issue 2017-11-17 (AI)

Conference Information
Committee AI
Conference Date 2017/11/24(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Tsunenori Mine(Kyushu Univ.)
Vice Chair Daisuke Katagami(Tokyo Polytechnic Univ.) / Naoki Fukuta(Shizuoka Univ.)
Secretary Daisuke Katagami(Ritsumeikan Univ.) / Naoki Fukuta(Univ. of Electro-Comm.)
Assistant Yuko Sakurai(AIST)

Paper Information
Registration To Technical Committee on Artificial Intelligence and Knowledge-Based Processing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Web Contents Classification by The Context
Sub Title (in English)
Keyword(1) web contents
Keyword(2) Doc2Vec
Keyword(3) supervised learning
Keyword(4) classificatio
Keyword(5) context
Keyword(6) LDA
1st Author's Name Tomomi Sanjo
1st Author's Affiliation LIFULL Co., Ltd.(LIFULL)
2nd Author's Name Akito Sakurai
2nd Author's Affiliation Keio University(Keio Univ.)
Date 2017-11-24
Paper # AI2017-11
Volume (vol) vol.117
Number (no) AI-326
Page pp.pp.25-30(AI),
#Pages 6
Date of Issue 2017-11-17 (AI)