http://www.bibsonomy.org/burst/user/wnpxrz/searchBibSonomy BuRST Feed for /user/wnpxrz/search2008-07-21T02:02:26+02:00http://www.bibsonomy.org/bibtex/2f4873abd71cd109213b349c554cb376d/wnpxrzwnpxrz2008-04-07T16:20:08+02:00ir recommendersystems search recommendation query log <span style="color:#555555;">Z. <a href="http://www.bibsonomy.org/author/Zhang">Zhang</a> and O. <a href="http://www.bibsonomy.org/author/Nasraoui">Nasraoui</a> </span><em>Proceedings of the 15th international conference on World Wide Web</em>(<em>2006</em>)Mon Apr 07 16:20:08 CEST 2008Proceedings of the 15th international conference on World Wide Web1039--1040{Mining search engine query logs for query recommendation}2006ir recommendersystems search recommendation query log Reexamining the cluster hypothesishttp://www.bibsonomy.org/bibtex/29b5a5794e780defff1de777633e97a1b/wnpxrzwnpxrz2007-12-04T16:11:33+01:00search gather ir scatter imported clustering <span style="color:#555555;">Marti A. <a href="http://www.bibsonomy.org/author/Hearst">Hearst</a> and Jan O. <a href="http://www.bibsonomy.org/author/Pedersen">Pedersen</a> </span><em>SIGIR '96: Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval, </em><em>page76--84. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>1996</em>)Tue Dec 04 16:11:33 CET 2007New York, NY, USASIGIR '96: Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval76--84Reexamining the cluster hypothesis: scatter/gather on retrieval results1996search gather ir scatter imported clustering http://www.bibsonomy.org/bibtex/28cafb30efce0f039e1978a7a277f59fa/wnpxrzwnpxrz2007-11-30T20:37:01+01:00web goal search ir intentional user <span style="color:#555555;">M. <a href="http://www.bibsonomy.org/author/Strohmaier">Strohmaier</a> and M. <a href="http://www.bibsonomy.org/author/Lux">Lux</a> and M. <a href="http://www.bibsonomy.org/author/Granitzer">Granitzer</a> and P. <a href="http://www.bibsonomy.org/author/Scheir">Scheir</a> and S. <a href="http://www.bibsonomy.org/author/Liaskos">Liaskos</a> and E. <a href="http://www.bibsonomy.org/author/Yu">Yu</a> </span><em>We Know'07 International Workshop on Collaborative Knowledge Management for Web Information Systems, in conjunction with WISE'07, Nancy, France, </em>(<em>2007</em>)Fri Nov 30 20:37:01 CET 2007We Know'07 International Workshop on Collaborative Knowledge Management for Web Information Systems, in conjunction with WISE'07, Nancy, FranceHow Do Users Express Goals on the Web? - An Exploration of Intentional Structures in Web Search2007web goal search ir intentional user http://www.bibsonomy.org/bibtex/2ac49c33e114ca171db40cece6a0ae4d6/wnpxrzwnpxrz2007-11-21T16:12:55+01:00pagerank ir search ranking <span style="color:#555555;">L. <a href="http://www.bibsonomy.org/author/Page">Page</a> and S. <a href="http://www.bibsonomy.org/author/Brin">Brin</a> and R. <a href="http://www.bibsonomy.org/author/Motwani">Motwani</a> and T. <a href="http://www.bibsonomy.org/author/Winograd">Winograd</a> </span><em>Proceedings of the 7th International World Wide Web Conference, </em><em>page161--172. </em><em>Brisbane, Australia, </em>(<em>1998</em>)Wed Nov 21 16:12:55 CET 2007Brisbane, AustraliaProceedings of the 7th International World Wide Web Conference161--172The PageRank citation ranking: Bringing order to the Web1998pagerank ir search ranking dblphttp://www.bibsonomy.org/bibtex/24d2ddff0f0013f7d6cffc782c5eca56c/wnpxrzwnpxrz2007-11-21T16:12:45+01:00ranking ir search machinelearning <span style="color:#555555;">Matthew <a href="http://www.bibsonomy.org/author/Richardson">Richardson</a> and Amit <a href="http://www.bibsonomy.org/author/Prakash">Prakash</a> and Eric <a href="http://www.bibsonomy.org/author/Brill">Brill</a> </span><em>WWW, </em><em>page707-715. </em><em>ACM, </em>(<em>2006</em>)Wed Nov 21 16:12:45 CET 2007WWWconf/www/2006707-715Beyond PageRank: machine learning for static ranking.2006ranking ir search machinelearning http://www.bibsonomy.org/bibtex/276b741061fab004645c3119db5a17bc3/wnpxrzwnpxrz2007-11-21T16:12:16+01:00folksonomy filtering clustering collaborative tags search exploration tag <span style="color:#555555;">Grigory <a href="http://www.bibsonomy.org/author/Begelman">Begelman</a> and Philipp <a href="http://www.bibsonomy.org/author/Keller">Keller</a> and Frank <a href="http://www.bibsonomy.org/author/Smadja">Smadja</a> </span><em>Collaborative Web Tagging Workshop at WWW2006, Edinburgh, Scotland, </em>(<em>2006</em>)Wed Nov 21 16:12:16 CET 2007Collaborative Web Tagging Workshop at WWW2006, Edinburgh, ScotlandAutomated Tag Clustering: Improving search and exploration in the tag space2006folksonomy filtering clustering collaborative tags search exploration tag http://www.bibsonomy.org/bibtex/2fc936cec60b1b7ab69f230f14139e8ab/wnpxrzwnpxrz2007-11-21T16:10:35+01:00web ir search <span style="color:#555555;">Sergey <a href="http://www.bibsonomy.org/author/Brin">Brin</a> and Lawrence <a href="http://www.bibsonomy.org/author/Page">Page</a> </span><em>Computer Networks and ISDN Systems</em><em>30(1-7):107--117</em><em>April1998. </em>Wed Nov 21 16:10:35 CET 2007Computer Networks and ISDN SystemsApril1-7107--117{T}he {A}natomy of a {L}arge-{S}cale {H}ypertextual {W}eb {S}earch {E}ngine301998web ir search CiteULike: Faceted metadata for image search and browsinghttp://www.bibsonomy.org/bibtex/2459da9d9a1fff65925c3e96f97fb685a/wnpxrzwnpxrz2007-11-04T09:09:06+01:00search metadata browsing image faceted <span style="color:#555555;">Ka P. <a href="http://www.bibsonomy.org/author/Yee">Yee</a> and Kirsten <a href="http://www.bibsonomy.org/author/Swearingen">Swearingen</a> and Kevin <a href="http://www.bibsonomy.org/author/Li">Li</a> and Marti <a href="http://www.bibsonomy.org/author/Hearst">Hearst</a> </span><em>Proceedings of the SIGCHI conference on Human factors in computing systems, </em>(<em>2003</em>)Sun Nov 04 09:09:06 CET 2007Proceedings of the SIGCHI conference on Human factors in computing systemsFaceted metadata for image search and browsing2003search metadata browsing image faceted Ontology-Based User Profiles for Search and Browsing (ResearchIndex)http://www.bibsonomy.org/bibtex/27e876459e3a889402eba7dbbe3595b46/wnpxrzwnpxrz2007-11-03T17:27:58+01:00user profile search imported ontology browsing ir <span style="color:#555555;">Susan <a href="http://www.bibsonomy.org/author/Gauch">Gauch</a> and Jason <a href="http://www.bibsonomy.org/author/Chaffee">Chaffee</a> and Alexander <a href="http://www.bibsonomy.org/author/Pretschner">Pretschner</a> </span>(<em>2002</em>)Sat Nov 03 17:27:58 CET 2007Ontology-Based User Profiles for Search and Browsing2002user profile search imported ontology browsing ir Adaptive web search based on user profile constructed without any effort from usershttp://www.bibsonomy.org/bibtex/23db95ec7dc4631629b638eb0230cc55a/wnpxrzwnpxrz2007-10-19T20:37:47+02:00ir imported web profiling adaptive profile search user <span style="color:#555555;">Kazunari <a href="http://www.bibsonomy.org/author/Sugiyama">Sugiyama</a> and Kenji <a href="http://www.bibsonomy.org/author/Hatano">Hatano</a> and Masatoshi <a href="http://www.bibsonomy.org/author/Yoshikawa">Yoshikawa</a> </span><em>WWW '04: Proceedings of the 13th international conference on World Wide Web, </em><em>page675--684. </em><em>New York, NY, USA, </em><em>ACM Press, </em>(<em>2004</em>)Fri Oct 19 20:37:47 CEST 2007New York, NY, USAWWW '04: Proceedings of the 13th international conference on World Wide Web675--684Adaptive web search based on user profile constructed without any effort from users2004ir imported web profiling adaptive profile search user Web search engines help users find useful information on the World Wide Web (WWW). However, when the same query is submitted by different users, typical search engines return the same result regardless of who submitted the query. Generally, each user has different information needs for his/her query. Therefore, the search result should be adapted to users with different information needs. In this paper, we first propose several approaches to adapting search results according to each user's need for relevant information without any user effort, and then verify the effectiveness of our proposed approaches. Experimental results show that search systems that adapt to each user's preferences can be achieved by constructing user profiles based on modified collaborative filtering with detailed analysis of user's browsing history in one day.Collecting community wisdomhttp://www.bibsonomy.org/bibtex/288603ee0903b30dc642aebdaa6a22f93/wnpxrzwnpxrz2007-10-14T11:03:08+02:00social search navigation <span style="color:#555555;">Jill <a href="http://www.bibsonomy.org/author/Freyne">Freyne</a> and Rosta <a href="http://www.bibsonomy.org/author/Farzan">Farzan</a> and Peter <a href="http://www.bibsonomy.org/author/Brusilovsky">Brusilovsky</a> and Barry <a href="http://www.bibsonomy.org/author/Smyth">Smyth</a> and Maurice <a href="http://www.bibsonomy.org/author/Coyle">Coyle</a> </span><em>IUI '07: Proceedings of the 12th international conference on Intelligent user interfaces, </em><em>page52--61. </em><em>New York, NY, USA, </em><em>ACM Press, </em>(<em>2007</em>)Sun Oct 14 11:03:08 CEST 2007New York, NY, USAIUI '07: Proceedings of the 12th international conference on Intelligent user interfaces52--61Collecting community wisdom: integrating social search & social navigation2007social search navigation The goal of this paper is to detail the integration of two "social Web" technologies - social search and social navigation - and to highlight the benefits of such integration on two levels. Firstly, both technologies harvest and harness "community wisdom" and in an integrated system each of the search and navigation components can benefit from the additional community wisdom gathered by the other when assisting users to locate relevant information. Secondly, by integrating search and browsing we facilitate the development of a unique interface that effectively blends search and browsing functionality as part of a seamless social information access service. This service allows users to effectively combine their search and browsing behaviors. In this paper we will argue that this integration provides significantly more than the simple sum of the parts.Blog search and mining in the business domainhttp://www.bibsonomy.org/bibtex/28add5688facb791bda4e6db738eb1654/wnpxrzwnpxrz2007-09-30T18:05:15+02:00ir blog mining business search <span style="color:#555555;">Yun <a href="http://www.bibsonomy.org/author/Chen">Chen</a> and Flora S. <a href="http://www.bibsonomy.org/author/Tsai">Tsai</a> and Kap Luk <a href="http://www.bibsonomy.org/author/Chan">Chan</a> </span><em>DDDM '07: Proceedings of the 2007 international workshop on Domain driven data mining, </em><em>page55--60. </em><em>New York, NY, USA, </em><em>ACM Press, </em>(<em>2007</em>)Sun Sep 30 18:05:15 CEST 2007New York, NY, USADDDM '07: Proceedings of the 2007 international workshop on Domain driven data mining55--60Blog search and mining in the business domain2007ir blog mining business search Interactive Cluster Visualization for Information Retrieval - Allan, Leouski, Swan (ResearchIndex)http://www.bibsonomy.org/bibtex/21e812543ac2929cf85e5ee475efe3c36/wnpxrzwnpxrz2007-08-30T18:26:20+02:00clustering visualization ir proj:et imported search <span style="color:#555555;">J. <a href="http://www.bibsonomy.org/author/Allan">Allan</a> and A. <a href="http://www.bibsonomy.org/author/Leouski">Leouski</a> and R. <a href="http://www.bibsonomy.org/author/Swan">Swan</a> </span>(<em>1997</em>)Thu Aug 30 18:26:20 CEST 2007Interactive Cluster Visualization for Information Retrieval1997clustering visualization ir proj:et imported search This study investigates the ability of cluster visualization to help a user rapidly identify relevant documents. It provides added support for the truth of the Cluster Hypothesis on retrieved documents and shows that clustering of relevant documents is readily visible. The study then shows the visual effect of a technique similar to relevance feedback and shows how to enhance that effect to further help the user locate relevant material. A ranked list returned by a text search engine purports...http://www.bibsonomy.org/bibtex/2a3a38920006837a63ccfdcd7eda4d3fe/wnpxrzwnpxrz2007-08-27T18:29:23+02:00web query search ir <span style="color:#555555;">M. <a href="http://www.bibsonomy.org/author/Whittle">Whittle</a> and B. <a href="http://www.bibsonomy.org/author/Eaglestone">Eaglestone</a> and N. <a href="http://www.bibsonomy.org/author/Ford">Ford</a> and V.J. <a href="http://www.bibsonomy.org/author/Gillet">Gillet</a> and A. <a href="http://www.bibsonomy.org/author/Madden">Madden</a> </span><em>Information Research</em>(<em>2006</em>)Mon Aug 27 18:29:23 CEST 2007Information Research1{Query transformations and their role in Web searching by the general public}122006web query search ir On the use of spreading activation methods in automatic informationhttp://www.bibsonomy.org/bibtex/2994aef0486e69095ee0d8ba5b3e3a91c/wnpxrzwnpxrz2007-08-20T20:37:11+02:00search spreading ir <span style="color:#555555;">G. <a href="http://www.bibsonomy.org/author/Salton">Salton</a> and C. <a href="http://www.bibsonomy.org/author/Buckley">Buckley</a> </span><em>SIGIR '88: Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval, </em><em>page147--160. </em><em>New York, NY, USA, </em><em>ACM Press, </em>(<em>1988</em>)Mon Aug 20 20:37:11 CEST 2007New York, NY, USASIGIR '88: Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval147--160On the use of spreading activation methods in automatic information1988search spreading ir Spreading activation methods have been recommended in information retrieval to expand the search vocabulary and to complement the retrieved document sets. The spreading activation strategy is reminiscent of earlier associative indexing and retrieval systems. Some spreading activation procedures are briefly described, and evaluation output is given, reflecting the effectiveness of one of the proposed procedures.: WWW '07, Dynamic personalized pagerank in ...http://www.bibsonomy.org/bibtex/26edef588be76947d64884e2bc7f3089e/wnpxrzwnpxrz2007-08-20T20:36:36+02:00personalization ranking pagerank dynamic search ir <span style="color:#555555;">Soumen <a href="http://www.bibsonomy.org/author/Chakrabarti">Chakrabarti</a> </span><em>WWW '07: Proceedings of the 16th international conference on World Wide Web, </em><em>page571--580. </em><em>New York, NY, USA, </em><em>ACM Press, </em>(<em>2007</em>)Mon Aug 20 20:36:36 CEST 2007New York, NY, USAWWW '07: Proceedings of the 16th international conference on World Wide Web571--580Dynamic personalized pagerank in entity-relation graphs2007personalization ranking pagerank dynamic search ir http://www.bibsonomy.org/bibtex/2c77ff07c7801271cd31e54a850edf430/wnpxrzwnpxrz2007-08-20T20:35:38+02:00ir search web <span style="color:#555555;">S. <a href="http://www.bibsonomy.org/author/Lawrence">Lawrence</a> and C. <a href="http://www.bibsonomy.org/author/Giles">Giles</a> </span><em>Science</em><em>041998. </em>Mon Aug 20 20:35:38 CEST 2007Science0498-100Searching the world wide web2801998ir search web 03The coverage and recency of the major World Wide Web search engines was analyzed, yielding some surprising results. The coverage of any one engine is significantly limited: No single engine indexes more than about one-third of the "indexable Web," the coverage of the six engines investigated varies by an order of magnitude, and combining the results of the six engines yields about 3.5 times as many documents on average as compared with the results from only one engine. Analysis of the overlap between pairs of engines gives an estimated lower bound on the size of the indexable Web of 320 million pages.http://www.bibsonomy.org/bibtex/2e66f878addd0832ef8c04a6a93337101/wnpxrzwnpxrz2007-08-20T20:34:00+02:00ir search ranking folksonomy <span style="color:#555555;">Andreas <a href="http://www.bibsonomy.org/author/Hotho">Hotho</a> and Robert <a href="http://www.bibsonomy.org/author/Jäschke">J&#228;schke</a> and Christoph <a href="http://www.bibsonomy.org/author/Schmitz">Schmitz</a> and Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> </span><em>European Semantic Web Conference, Budva, Montenegro, 11-14.06.06, </em>(<em>2006</em>)Mon Aug 20 20:34:00 CEST 2007European Semantic Web Conference, Budva, Montenegro, 11-14.06.06Information Retrieval in Folksonomies: Search and Ranking2006ir search ranking folksonomy Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. At the moment, however, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset. http://www.bibsonomy.org/bibtex/221bbcbb780f14f106cbaa72fa8e9aa22/wnpxrzwnpxrz2007-08-15T12:06:33+02:00search social network identity <span style="color:#555555;">D. J. <a href="http://www.bibsonomy.org/author/Watts">Watts</a> and P. S. <a href="http://www.bibsonomy.org/author/Dodds">Dodds</a> and M. E. J. <a href="http://www.bibsonomy.org/author/Newman">Newman</a> </span><em>May2002. </em>Wed Aug 15 12:06:33 CEST 2007MayIdentity and Search in Social Networks2002search social network identity Social networks have the surprising property of being "searchable": Ordinary people are capable of directing messages through their network of acquaintances to reach a specific but distant target person in only a few steps. We present a model that offers an explanation of social network searchability in terms of recognizable personal identities: sets of characteristics measured along a number of social dimensions.http://www.bibsonomy.org/bibtex/20f695a72a5ccaa986dbdfac5e8126ae3/wnpxrzwnpxrz2007-08-15T12:06:16+02:00social network search <span style="color:#555555;">Lada A. <a href="http://www.bibsonomy.org/author/Adamic">Adamic</a> and Eytan <a href="http://www.bibsonomy.org/author/Adar">Adar</a> </span><em>November2004. </em>Wed Aug 15 12:06:16 CEST 2007NovemberHow to search a social network2004social network search We address the question of how participants in a small world experiment are able to find short paths in a social network using only local information about their immediate contacts. We simulate such experiments on a network of actual email contacts within an organization as well as on a student social networking website. On the email network we find that small world search strategies using a contact's position in physical space or in an organizational hierarchy relative to the target can effectively be used to locate most individuals. However, we find that in the online student network, where the data is incomplete and hierarchical structures are not well defined, local search strategies are less effective. We compare our findings to recent theoretical hypotheses about underlying social structure that would enable these simple search strategies to succeed and discuss the implications to social software design.