PPT-Improving Search Relevance for Short Queries in
Author : lois-ondreau | Published Date : 2019-02-11
Community Question Answering Date 20140925 Author Haocheng Wu Wei Wu Ming Zhou Enhong Chen Lei Duan HeungYeung Shum Source WSDM14 Advisor
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Improving Search Relevance for Short Queries in: Transcript
Community Question Answering Date 20140925 Author Haocheng Wu Wei Wu Ming Zhou Enhong Chen Lei Duan HeungYeung Shum Source WSDM14 Advisor . Zhao School of Law University of Washington fczuwashingtonedu Douglas W Oard Coll of Info Stu UMIACS University of Maryland College Park MD 20742 oardumdedu Jason R Baron Of64257ce of the General Counsel National Archives and Records Administration These slides are modified from those by . Anand. . Rajaram. & Jeff . Ullman. History of web advertising. Banner ads (1995-2001). Initial form of web advertising. Popular websites charged X$ for every 1000 “impressions” of ad. Exploring . Intrinsic Diversity . in . Web Search . Karthik Raman (Cornell University). Paul N. Bennett (MSR, Redmond). Kevyn. . Collins-Thompson (MSR, Redmond). Whole-Session Relevance. Typical search model : . Sai . Vallurupalli. What are query logs useful for?. In Social Sciences, Medical & Health, Advertising & Marketing, Law Enforcement etc. . Understanding Search Behavior – Trends and Hot Trends. Ryan . McIntyre. MCITP. , MCPD. Director. , Portals & Collaboration. SharePoint 2013 Search Overview. Changes from 2010. Search Solutions. OOTB Web . Parts Review. API. Server side. Client side. Leave Now…Or…. Search Relevance in SharePoint 2013 . Victor Poznanski . Principal Program . Manager. Jan Inge Bergseth . Architect. SPC145. When You Leave, You Should Know…. What: . …our view of relevance is. Information Retrieval in Practice. All slides ©Addison Wesley, 2008. Information Needs. An . information need. is the underlying cause of the query . that a . person submits to a search . engine. sometimes called . Ruirui. Li, Ben Kao, Bin Bi, . Reynold. Cheng, Eric Lo. Speaker:. . Ruirui. Li. 1. The University of Hong Kong. Outline. Motivation. Problem Statement. DQR Model. Experiments & Evaluation. 2. sparsity. in web search click data. Qi . Guo. , Dmitry . Lagun. , . Denis Savenkov. , . Qiaoling. Liu. [qguo3. ,dlagun,denis.savenkov,. qiaoling.liu. ]. @. emory.edu. Mathematics . & . Computer . All slides ©Addison Wesley, 2008. Evaluation. Evaluation is key to building . effective. and . efficient. search engines. measurement usually carried out in controlled laboratory experiments. online. All slides ©Addison Wesley, 2008. Evaluation. Evaluation is key to building . effective. and . efficient. search engines. measurement usually carried out in controlled laboratory experiments. online. All slides ©Addison Wesley, 2008. Evaluation. Evaluation is key to building . effective. and . efficient. search engines. measurement usually carried out in controlled laboratory experiments. online. Evaluation. Evaluation is key to building . effective. and . efficient. search engines. Measurement usually carried out in controlled laboratory experiments. Online. testing can also be done. Anand. . Rajaram. & Jeff . Ullman. History of web advertising. Banner ads (1995-2001). Initial form of web advertising. Popular websites charged X$ for every 1000 “impressions” of ad. Called “CPM” rate.
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