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Semi-supervised learning for Web Search MPMeister

Kevin Duh

生駒 : 奈良先端科学技術大学院大学, 2012.4

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Holdings:
  Volume Printing year Location Call Number Material ID Circulation class Status Waiting
1 MPMeister   Digital Library LA-I-R[Flash][Mobile] M009745   0
Contents Intro. : Search is a core activity performed by Internet users. The growth of the Internet is, to a large extent, supported by advances in search technology. Search enables users to discover content, perform tasks, and navigate through the World "Wild" Web.In this talk, we will begin by discussing the how web search works under the hood. In particular, we will see that web search can be framed as a ranking problem and tackled via machine learning methods. Then I will discuss my work on improving the cost-effectiveness of building search engines through the use of semi-supervised learning. Finally, we will briefly discuss other ranking problems, such as those in computational biology and natural language processing, that can be addressed in a similar framework.
Publication year : 2012
Form : 電子化映像資料(26分38秒)
Series title :

情報科学研究科・ゼミナール講演 ; 平成24年度

Note :

講演者所属: 奈良先端科学技術大学院大学 情報科学研究科 自然言語処理学研究室

講演日: 平成24年4月16日

講演場所: 情報科学研究科大講義室L1

Country of publication : Japan
Title language : English (eng)
Language of texts : Japanese (jpn)
Author information :

Duh, Kevin