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Smoothing clickthrough data for web search ranking

Jianfeng Gao, Wei Yuan, Xiao Li, Kefeng Deng, Jian-Yun Nie
2009 Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '09  
Incorporating features extracted from clickthrough data (called clickthrough features) has been demonstrated to significantly improve the performance of ranking models for Web search applications.  ...  Both methods are evaluated on real-world data in three Web search domains.  ...  Previous work has utilized clickthrough data as implicit feedback for Web search ranking in two different ways.  ... 
doi:10.1145/1571941.1572003 dblp:conf/sigir/GaoYLDN09 fatcat:s6sj6jzejfdz3nst4nzea7icra

Smoothing Click Counts for Aggregated Vertical Search [chapter]

Jangwon Seo, W. Bruce Croft, Kwang Hyun Kim, Joon Ho Lee
2011 Lecture Notes in Computer Science  
Clickthrough data is a critical feature for improving web search ranking.  ...  Using real clickthrough data from a vertical recorded in an aggregated search environment, we show empirically that clickthrough data smoothed by this technique is effective for improving the vertical  ...  Acknowledgments This work was supported in part by the Center for Intelligent Information Retrieval, in part by NHN Corp. and in part by NSF grant #IIS-0711348.  ... 
doi:10.1007/978-3-642-20161-5_39 fatcat:3j74o4muc5d2nnez6cxighblty

CubeSVD

Jian-Tao Sun, Hua-Jun Zeng, Huan Liu, Yuchang Lu, Zheng Chen
2005 Proceedings of the 14th international conference on World Wide Web - WWW '05  
This paper focuses on utilizing clickthrough data to improve Web search.  ...  As the competition of Web search market increases, there is a high demand for personalized Web search to conduct retrieval incorporating Web users' information needs.  ...  However, it was not used for Web search application. The technique introduced in [14] uses clickthrough data in order to improve the quality of Web search.  ... 
doi:10.1145/1060745.1060803 dblp:conf/www/SunZLLC05 fatcat:wkfoq6bvfnhq5jrrcq7jek5wrm

Click-based evidence for decaying weight distributions in search effectiveness metrics

Yuye Zhang, Laurence A. F. Park, Alistair Moffat
2009 Information retrieval (Boston)  
We describe a process for extrapolating user observations from query log clickthroughs, and employ this user model to measure the quality of effectiveness weighting distributions.  ...  In addition, using past TREC data as to indicate likelihood of relevance, we also show that the distributions employed in the BPref and MRR metrics are the best fit out of the measures for which static  ...  One simple way of forming an observation model is to note the rank positions of users' clickthroughs, data that is readily available in the web search context.  ... 
doi:10.1007/s10791-009-9099-7 fatcat:zaxd4u6sdfdhjj4qvgkskxx6hy

Implementation of Ontology based Personalized Search Filtering (OBPSF) on Smartphone

Ms. Devayani L. Phadke, Prof. Jyoti. N. Nandimath
2017 International Journal of Engineering Research and  
The user preferences are organized in an ontology-based, multifacet user profile, which are used to adapt a personalized ranking function for rank adaptation of future search results.  ...  In a ontology based personalized search filtering (OBPSF) on smart phone that captures the users' preferences in the form of concepts by mining their clickthrough data.  ...  These interactions can serve as a significant source of information for improving web search result ranking.  ... 
doi:10.17577/ijertv6is040789 fatcat:2ljwuff6njeyxl2dgvfxdstebe

Reranking search results for sparse queries

Elif Aktolga, James Allan
2011 Proceedings of the 20th ACM international conference on Information and knowledge management - CIKM '11  
However, when a new or unusual query appears, or when a system is not as widely used as a mainstream web search system, there may be little to no click data available to improve the results.  ...  In this work we describe a way to boost rarely-clicked queries in a system where limited clickthrough data is available for all queries.  ...  INTRODUCTION Clickthrough data from query logs is widely used to improve document ranking [1, 8, 9, 10, 14, 15, 25] . But how does it work for new or unusual queries in a search system?  ... 
doi:10.1145/2063576.2063606 dblp:conf/cikm/AktolgaA11 fatcat:nlcya5iaf5hc3pspioxvv4vblq

Improving retrieval accuracy by weighting document types with clickthrough data

Peter C. K. Yeung, Charles L. A. Clarke, Stefan Büttcher
2007 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '07  
For enterprise search, there exists a relationship between work task and document type that can be used to refine search results [3] .  ...  Using the W3C collection from the TREC Enterprise track for evaluations, our approach leads to significant improvements on search precision.  ...  Our objective is to find relevant document type(s) for the expert search task and rank documents from this type higher to improve search precisions.  ... 
doi:10.1145/1277741.1277895 dblp:conf/sigir/YeungCB07 fatcat:jdldlhxlyfet7mdt72s2h3tlpi

Discovering missing click-through query language information for web search

Xing Yi, James Allan
2011 Proceedings of the 20th ACM international conference on Information and knowledge management - CIKM '11  
The click-through information in web query logs has been widely used for web search tasks.  ...  In this paper, we adapt two language modeling based approaches to address this issue in the context of using web query logs for web search.  ...  For example, click-through information can be used to derive labeled training data for optimizing web ranking functions used by web search engines [14, 26] ; user clicks can be directly used as relevance  ... 
doi:10.1145/2063576.2063604 dblp:conf/cikm/YiA11 fatcat:or4ulroflnexjl6hpgxmoepeyy

Query expansion using path-constrained random walks

Jianfeng Gao, Gu Xu, Jinxi Xu
2013 Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '13  
Evaluation is performed on the Web document ranking task using a real-world data set.  ...  This paper exploits Web search logs for query expansion (QE) by presenting a new QE method based on path-constrained random walks (PCRW), where the search logs are represented as a labeled, directed graph  ...  CONCLUSIONS This paper exploits search logs for QE for Web search ranking.  ... 
doi:10.1145/2484028.2484058 dblp:conf/sigir/GaoXX13 fatcat:tizvpq6w4beltp5d2lfowht2xa

Spying Out Accurate User Preferences for Search Engine Adaptation [chapter]

Lin Deng, Wilfred Ng, Xiaoyong Chai, Dik-Lun Lee
2006 Lecture Notes in Computer Science  
Recently, some researchers have studied the use of clickthrough data to adapt a search engine's ranking function. Clickthrough data indicate for each query the results that are clicked by users.  ...  As a kind of implicit relevance feedback information, clickthrough data can easily be collected by a search engine.  ...  Introduction The information on the Web is huge and growing rapidly. An effective search engine is an important means for users to find the desired information from billions of Web pages.  ... 
doi:10.1007/11899402_6 fatcat:o4difh5ntjfpdgkaknocvo6kay

Clickthrough-based latent semantic models for web search

Jianfeng Gao, Kristina Toutanova, Wen-tau Yih
2011 Proceedings of the 34th international ACM SIGIR conference on Research and development in Information - SIGIR '11  
This paper presents two new document ranking models for Web search based upon the methods of semantic representation and the statistical translation-based approach to information retrieval (IR).  ...  These models are evaluated on the Web search task using a real world data set. Results show that they significantly outperform their corresponding baseline models, which are state-of-the-art.  ...  In this paper we present two new document ranking models for Web search, a bilingual topic model and a discriminative projection model. Both models are learned on clickthrough data.  ... 
doi:10.1145/2009916.2010007 dblp:conf/sigir/GaoTY11 fatcat:wcre2utsz5ekpiwu73wa3saq4e

Clickthrough-based translation models for web search

Jianfeng Gao, Xiaodong He, Jian-Yun Nie
2010 Proceedings of the 19th ACM international conference on Information and knowledge management - CIKM '10  
Web search is challenging partly due to the fact that search queries and Web documents use different language styles and vocabularies.  ...  This paper provides a quantitative analysis of the language discrepancy issue, and explores the use of clickthrough data to bridge documents and queries.  ...  ACKNOWLEDGMENTS The authors would like to thank Chris Quirk, Xiaolong Li, Kuansan Wang and Guihong Cao for the very helpful discussions and collaboration.  ... 
doi:10.1145/1871437.1871582 dblp:conf/cikm/GaoHN10 fatcat:orrfszivqnavfbjpxhpgswwyxe

Learning deep structured semantic models for web search using clickthrough data

Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, Larry Heck
2013 Proceedings of the 22nd ACM international conference on Conference on information & knowledge management - CIKM '13  
The new models are evaluated on a Web document ranking task using a real-world data set.  ...  The proposed deep structured semantic models are discriminatively trained by maximizing the conditional likelihood of the clicked documents given a query using the clickthrough data.  ...  Web search.  ... 
doi:10.1145/2505515.2505665 dblp:conf/cikm/HuangHGDAH13 fatcat:6kuujlxihvfh7asjrbdfovgdkm

Mining User preference using Spy voting for search engine personalization

Wilfred Ng, Lin Deng, Dik Lun Lee
2007 ACM Transactions on Internet Technology  
We present a new approach to mining a user's preferences on the search results from clickthrough data and using the discovered preferences to adapt the search engine's ranking function for improving search  ...  This paper addresses search engine personalization.  ...  Then, the user submits queries and clicks on the search results while the search engine logs the user's actions as clickthrough data for analysis.  ... 
doi:10.1145/1278366.1278368 fatcat:ww6m3z53unforod3irnxf5b6ti

PMSE: A Personalized Mobile Search Engine

Kenneth Wai-Ting Leung, Dik Lun Lee, Wang-Chien Lee
2013 IEEE Transactions on Knowledge and Data Engineering  
We propose a personalized mobile search engine, PMSE, that captures the users' preferences in the form of concepts by mining their clickthrough data.  ...  The user preferences are organized in an ontology-based, multi-facet user profile, which are used to adapt a personalized ranking function for rank adaptation of future search results.  ...  ACKNOWLEDGMENTS We would like to express our sincere thanks to the editors and the reviewers for giving very insightful and encouraging comments.  ... 
doi:10.1109/tkde.2012.23 fatcat:24uwnbkzpjdsjawd3niyjuuet4
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