Human–computer information retrieval

Results: 571



#Item
141Information / Relevance / Search engine / Full text search / Usability / Information seeking / Metadata / Relevance feedback / Human–computer information retrieval / Information science / Information retrieval / Science

Microsoft Word - crystal_greenberg_JASISTsubmission_revised_with-figures.doc

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Source URL: ils.unc.edu

Language: English - Date: 2006-02-16 08:51:28
142Internet marketing / Human–computer interaction / Information retrieval / Personalization / World Wide Web / Conversion rate / Landing page / Google Analytics / Web analytics / Marketing / Internet / Business

REAL-TIME WEB PERSONALIZATION For Marketers & Customer Success Professionals VISITATION INTO CONVERSION 25 WAYS TO DO

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Source URL: www.mitx.org

Language: English - Date: 2014-01-24 11:38:18
143Relevance / Usability / Personalization / Human–computer information retrieval / Information science / Information retrieval / Relevance feedback

LNCSA System for Adaptive Information Retrieval

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Source URL: www.dcs.gla.ac.uk

Language: English - Date: 2008-01-05 05:58:37
144Computing / Human–computer interaction / Information retrieval / Personalization / Email / Credit card / Online shopping / Information science / Marketing / World Wide Web

C LU B SU PPLI ES ORDER F ORM MAKE A COPY OF THIS ORDER FOR YOUR RECORDS Name Country

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Source URL: www.lionsclubs.org

Language: English - Date: 2015-04-23 16:19:55
145Website / Web search engine / Computing / Internet marketing / World Wide Web / Web analytics / Human–computer interaction / Internet / Information science / Information retrieval

How to Make the Site Successful Good News Web Designers Association http://gnwda.org/ http://gnwda.org/ Countless numbers of websites are vying for the attention of the people you want to attract to yours. Most people

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Source URL: gnwda.org

Language: English - Date: 2011-05-13 07:45:17
146Human–computer interaction / Human communication / Recommender systems / Groupware / Information retrieval / GroupLens Research / Collaborative filtering / Computer-supported cooperative work / User interface / Collaboration / Human–computer interaction / Information science

See What You Want to See: Visual User-Driven Approach for Hybrid Recommendation Denis Parra PUC Chile Santiago, Chile

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Source URL: web.ing.puc.cl

Language: English - Date: 2014-08-17 22:37:50
147Information / Science / User interface techniques / Knowledge representation / Faceted classification / Faceted search / Usability / Exploratory search / Facet / Information science / Information retrieval / Human–computer interaction

UIs for Faceted Navigation Recent Advances and Remaining Open Problems Marti A. Hearst School of Information UC Berkeley Berkeley, CA 94720

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Source URL: flamenco.berkeley.edu

Language: English - Date: 2008-10-20 17:55:56
148Information retrieval / Information / Software / Data management / Technical communication / Context awareness / Personalization / Adaptation / Recommender system / Information science / Human–computer interaction / User interface techniques

Context-Aware Content Filtering & Presentation for Pervasive & Mobile Information Systems ∗ Kaijian Xu

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Source URL: www-scf.usc.edu

Language: English - Date: 2009-03-04 01:51:33
149Science / Collaboration / Human–computer interaction / Personalization / World Wide Web / Collaborative filtering / Crowdsourcing / Recommender system / Taste / Information science / Social information processing / Information retrieval

A Crowd of Your Own: Crowdsourcing for On-Demand Personalization Peter Organisciak1, Jaime Teevan2, Susan Dumais2, Robert C. Miller3, Adam Tauman Kalai2 1University 2Microsoft Research of Illinois at Urbana-Champaign

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Source URL: research.microsoft.com

Language: English - Date: 2014-08-06 19:43:32
150Human–computer interaction / Collaborative filtering / Collective intelligence / Social information processing / Special Interest Group on Information Retrieval / Information / Gameplay / Orc / Information science / Information retrieval / Science

1 Overview of the Special Issue on Contextual Search and Recommendation PAUL N. BENNETT, Microsoft Research KEVYN COLLINS-THOMPSON, University of Michigan DIANE KELLY, University of North Carolina at Chapel Hill

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Source URL: research.microsoft.com

Language: English - Date: 2014-11-17 20:18:35
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