http://www.bibsonomy.org/burst/tag/WebSearchBibSonomy BuRST Feed for /tag/WebSearch2008-11-19T05:48:16+01:00http://www.bibsonomy.org/bibtex/20b6c0dc464ba293887fbabe3a96f79c0/sunysuny2008-11-12T10:53:30+01:00information_science www wismasys0809 Websearch <span style="color:#555555;">D. <a href="http://www.bibsonomy.org/author/Rose">Rose</a> </span><em>Proceedings of the 13thInternational World Wide Web Conference</em>(<em>2004</em>)Wed Nov 12 10:53:30 CET 2008Proceedings of the 13thInternational World Wide Web Conference13-19Understanding user goals in Websearch2004information_science www wismasys0809 Websearch http://www.bibsonomy.org/bibtex/20b6c0dc464ba293887fbabe3a96f79c0/juverjuver2008-11-11T14:49:58+01:00World_Wide_Web information_science user wismasys0809 Websearch <span style="color:#555555;">D. <a href="http://www.bibsonomy.org/author/Rose">Rose</a> </span><em>Proceedings of the 13thInternational World Wide Web Conference</em>(<em>2004</em>)Tue Nov 11 14:49:58 CET 2008Proceedings of the 13thInternational World Wide Web Conference13-19Understanding user goals in Websearch2004World_Wide_Web information_science user wismasys0809 Websearch http://www.bibsonomy.org/bibtex/236085c6aefab8fc5bc9903e2ecb96e00/mkroellmkroell2008-11-10T13:15:52+01:00search classification WebSearch toread <span style="color:#555555;">A. <a href="http://www.bibsonomy.org/author/Broder">Broder</a> </span><em>ACM SIGIR Forum</em><em>36(2):3-10</em>(<em>2002</em>)Mon Nov 10 13:15:52 CET 2008ACM SIGIR Forum23-10A taxonomy of Web search362002search classification WebSearch toread http://www.bibsonomy.org/bibtex/28c0c4efd13da94f2a316a995425bac90/saschasascha2008-11-05T17:50:32+01:00goals user wismasys0809 websearch <span style="color:#555555;">D. <a href="http://www.bibsonomy.org/author/Rose">Rose</a> </span><em>Seite13-19. </em>(<em>2004</em>)Wed Nov 05 17:50:32 CET 2008Proceedings of the 13th International World Wide Web Conference13-19Understanding user goals in Websearch2004goals user wismasys0809 websearch http://www.bibsonomy.org/bibtex/20b6c0dc464ba293887fbabe3a96f79c0/fl%C3%B6ckchenflöckchen2008-11-05T17:47:52+01:00information_science www wismasys0809 Websearch <span style="color:#555555;">D. <a href="http://www.bibsonomy.org/author/Rose">Rose</a> </span><em>Proceedings of the 13thInternational World Wide Web Conference</em>(<em>2004</em>)Wed Nov 05 17:47:52 CET 2008Proceedings of the 13thInternational World Wide Web Conference13-19Understanding user goals in Websearch2004information_science www wismasys0809 Websearch http://www.bibsonomy.org/bibtex/20b6c0dc464ba293887fbabe3a96f79c0/saschasascha2008-10-24T16:32:24+02:00goals user wismasys0809 websearch <span style="color:#555555;">D. <a href="http://www.bibsonomy.org/author/Rose">Rose</a> </span><em>Proceedings of the 13thInternational World Wide Web Conference</em>(<em>2004</em>)Fri Oct 24 16:32:24 CEST 2008Proceedings of the 13thInternational World Wide Web Conference13-19Understanding user goals in Websearch2004goals user wismasys0809 websearch http://www.bibsonomy.org/bibtex/2a01f5a47e80e8470cc5c4fdd2c537b93/mkroellmkroell2008-10-22T12:32:28+02:00QueryLogAnalysis search ethics WebSearch toread <span style="color:#555555;">E. <a href="http://www.bibsonomy.org/author/Adar">Adar</a> </span><em>Workshop on Query Log Analysis at the 16th World Wide Web Conference, </em>(<em>2007</em>)Wed Oct 22 12:32:28 CEST 2008Workshop on Query Log Analysis at the 16th World Wide Web Conference{User 4xxxxx9: Anonymizing query logs}2007QueryLogAnalysis search ethics WebSearch toread CIKM Poster on query log analysishttp://www.bibsonomy.org/bibtex/23ded379c40d55e30145f67c2b11010c8/mkroellmkroell2008-10-22T12:28:15+02:00QueryLogAnalysis search ethics WebSearch <span style="color:#555555;">R. <a href="http://www.bibsonomy.org/author/Jones">Jones</a> und R. <a href="http://www.bibsonomy.org/author/Kumar">Kumar</a> und B. <a href="http://www.bibsonomy.org/author/Pang">Pang</a> und A. <a href="http://www.bibsonomy.org/author/Tomkins">Tomkins</a> </span><em>CIKM '07: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management, </em><em>Seite909--914. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2007</em>)Wed Oct 22 12:28:15 CEST 2008New York, NY, USACIKM '07: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management909--914"I know what you did last summer": query logs and user privacy2007QueryLogAnalysis search ethics WebSearch Generating query substitutionshttp://www.bibsonomy.org/bibtex/281bcb23dfbca4f99d51d2033fb8347fe/mkroellmkroell2008-10-13T11:45:28+02:00InformationRetrieval QueryExpansion search WebSearch toread ReadingGroup <span style="color:#555555;">Rosie <a href="http://www.bibsonomy.org/author/Jones">Jones</a> und Benjamin <a href="http://www.bibsonomy.org/author/Rey">Rey</a> und Omid <a href="http://www.bibsonomy.org/author/Madani">Madani</a> und Wiley <a href="http://www.bibsonomy.org/author/Greiner">Greiner</a> </span><em>WWW '06: Proceedings of the 15th international conference on World Wide Web, </em><em>Seite387--396. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2006</em>)Mon Oct 13 11:45:28 CEST 2008New York, NY, USAWWW '06: Proceedings of the 15th international conference on World Wide Web387--396Generating query substitutions2006InformationRetrieval QueryExpansion search WebSearch toread ReadingGroup We introduce the notion of query substitution, that is, generating a new query to replace a user's original search query. Our technique uses modifications based on typical substitutions web searchers make to their queries. In this way the new query is strongly related to the original query, containing terms closely related to all of the original terms. This contrasts with query expansion through pseudo-relevance feedback, which is costly and can lead to query drift. This also contrasts with query relaxation through boolean or TFIDF retrieval, which reduces the specificity of the query. We define a scale for evaluating query substitution, and show that our method performs well at generating new queries related to the original queries. We build a model for selecting between candidates, by using a number of features relating the query-candidate pair, and by fitting the model to human judgments of relevance of query suggestions. This further improves the quality of the candidates generated. Experiments show that our techniques significantly increase coverage and effectiveness in the setting of sponsored search.http://www.bibsonomy.org/bibtex/262ac28c3d46df728a5d577f84d927be3/mkroellmkroell2008-10-08T11:59:17+02:00InformationRetrieval search WebSearch toread <span style="color:#555555;">P. <a href="http://www.bibsonomy.org/author/Jason Morrison">Jason Morrison</a> </span><em>Information Processing &amp; Management</em>(<em>2008</em>)Wed Oct 08 11:59:17 CEST 2008Information Processing & Management1397--1648Tagging and searching: Search retrieval effectiveness of folksonomies on the World Wide Web442008InformationRetrieval search WebSearch toread Many Web sites have begun allowing users to submit items to a collection and tag them with keywords. The folksonomies built from these tags are an interesting topic that has seen little empirical research. This study compared the search information retrieval (IR) performance of folksonomies from social bookmarking Web sites against search engines and subject directories. Thirty-four participants created 103 queries for various information needs. Results from each IR system were collected and participants judged relevance. Folksonomy search results overlapped with those from the other systems, and documents found by both search engines and folksonomies were significantly more likely to be judged relevant than those returned by any single IR system type. The search engines in the study had the highest precision and recall, but the folksonomies fared surprisingly well. Del.icio.us was statistically indistinguishable from the directories in many cases. Overall the directories were more precise than the folksonomies but they had similar recall scores. Better query handling may enhance folksonomy IR performance further. The folksonomies studied were promising, and may be able to improve Web search performance.SpringerLink - Book Chapterhttp://www.bibsonomy.org/bibtex/24462cf1a0c1364eed97392196402735c/mkroellmkroell2008-10-08T11:56:40+02:00social WebSearch toread <span style="color:#555555;">Yusuke <a href="http://www.bibsonomy.org/author/Yanbe">Yanbe</a> und Adam <a href="http://www.bibsonomy.org/author/Jatowt">Jatowt</a> und Satoshi <a href="http://www.bibsonomy.org/author/Nakamura">Nakamura</a> und Katsumi <a href="http://www.bibsonomy.org/author/Tanaka">Tanaka</a> </span><em>Web Engineering</em>(<em>2007</em>)Wed Oct 08 11:56:40 CEST 2008Web Engineering343--357Towards Improving Web Search by Utilizing Social Bookmarks2007social WebSearch toread Social bookmarking services have become recently popular in the Web. Along with the rapid increase in the amount of social bookmarks, future applications could leverage this data for enhancing search in the Web. This paper investigates the possibilityand potential benefits of a hybrid page ranking approach that would combine the ranking criteria of PageRank with the onebased on social bookmarks in order to improve the search in the Web. We demonstrate and discuss the results of analyticalstudy made in order to compare both popularity estimates. In addition, we propose a simple hybrid search method that combinesboth ranking metrics and we show some preliminary experiments using this approach. We hope that this study will shed new lighton the character of data in social bookmarking systems and foster development of new, effective search applications for theWeb.How people recall, recognize, and reuse search resultshttp://www.bibsonomy.org/bibtex/2f6e9352cbde5e7181624672652becf7d/mkroellmkroell2008-10-06T10:08:16+02:00search WebSearchResults WebSearch toread <span style="color:#555555;">Jaime <a href="http://www.bibsonomy.org/author/Teevan">Teevan</a> </span><em>ACM Trans. Inf. Syst.</em><em>26(4):1--27</em>(<em>2008</em>)Mon Oct 06 10:08:16 CEST 2008New York, NY, USAACM Trans. Inf. Syst.41--27How people recall, recognize, and reuse search results262008search WebSearchResults WebSearch toread http://www.bibsonomy.org/bibtex/24ec9d3d165e04cb7d881ed90a49cd3d2/mkroellmkroell2008-09-30T16:37:49+02:00InformationRetrieval intention QueryLogAnalysis search WebSearch ReadingGroup WWW09 goal UserSession <span style="color:#555555;">Doug <a href="http://www.bibsonomy.org/author/Downey">Downey</a> und Dan <a href="http://www.bibsonomy.org/author/Liebling">Liebling</a> und Susan <a href="http://www.bibsonomy.org/author/Dumais">Dumais</a> </span><em>ACM 17th Conference on Information and Knowledge Management</em>(<em>2008</em>)Tue Sep 30 16:37:49 CEST 2008ACM 17th Conference on Information and Knowledge Management Understanding the Relationship between Searchers' Queries and Information Goals2008InformationRetrieval intention QueryLogAnalysis search WebSearch ReadingGroup WWW09 goal UserSession We describe results from Web search log studies aimed at elucidating user behaviors associated with queries and destination URLs that appear with different frequencies. We note the diversity of information goals that searchers have and the differing ways that goals are specified. We examine rare and common information goals that are specified using rare or common queries. We identify several significant differences in user behavior depending on the rarity of the query and the destination URL. We find that searchers are more likely to be successful when the frequencies of the query and destination URL are similar. We also establish that the behavioral differences observed for queries and goals of varying rarity persist even after accounting for potential confounding variables, including query length, search engine ranking, session duration, and task difficulty. Finally, using an information-theoretic measure of search difficulty, we show that the benefits obtained by search and navigation actions depend on the frequency of the information goal.dblphttp://www.bibsonomy.org/bibtex/2664f6f7e2facd5740c753c8fdf0de9b4/mkroellmkroell2008-09-30T12:35:22+02:00personalization QueryLogAnalysis search entropy unsupervised seminal WebSearch ReadingGroup WWW09 <span style="color:#555555;">Qiaozhu <a href="http://www.bibsonomy.org/author/Mei">Mei</a> und Kenneth Ward <a href="http://www.bibsonomy.org/author/Church">Church</a> </span><em>WSDM, </em><em>Seite45-54. </em><em>ACM, </em>(<em>2008</em>)Tue Sep 30 12:35:22 CEST 2008WSDMconf/wsdm/200845-54Entropy of search logs: how hard is search? with personalization? with backoff?2008personalization QueryLogAnalysis search entropy unsupervised seminal WebSearch ReadingGroup WWW09 http://www.bibsonomy.org/bibtex/2109dbdb2db6119acda14a7500ff2747d/lifidealifidea2008-09-19T05:22:09+02:00Graph WebSearch <span style="color:#555555;">Jure <a href="http://www.bibsonomy.org/author/Leskovec">Leskovec</a> und Susan <a href="http://www.bibsonomy.org/author/Dumais">Dumais</a> und Eric <a href="http://www.bibsonomy.org/author/Horvitz">Horvitz</a> </span><em>WWW '07: Proceedings of the 16th international conference on World Wide Web, </em><em>Seite471--480. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2007</em>)Fri Sep 19 05:22:09 CEST 2008New York, NY, USAWWW '07: Proceedings of the 16th international conference on World Wide Web471--480Web projections: learning from contextual subgraphs of the web2007Graph WebSearch Mining related queries from Web search engine query logs using an improved association rule mining modelhttp://www.bibsonomy.org/bibtex/20dd9ce31df5499ecaf16a2a54bb1a4e5/mkroellmkroell2008-09-16T15:33:55+02:00mining QueryLogAnalysis query WebSearch AssociationRules toread <span style="color:#555555;">Xiaodong <a href="http://www.bibsonomy.org/author/Shi">Shi</a> und Christopher C. <a href="http://www.bibsonomy.org/author/Yang">Yang</a> </span><em>J. Am. Soc. Inf. Sci. Technol.</em><em>58(12):1871--1883</em>(<em>2007</em>)Tue Sep 16 15:33:55 CEST 2008New York, NY, USAJ. Am. Soc. Inf. Sci. Technol.121871--1883Mining related queries from Web search engine query logs using an improved association rule mining model582007mining QueryLogAnalysis query WebSearch AssociationRules toread Identifying ambiguous queries in web searchhttp://www.bibsonomy.org/bibtex/20c45940081f44703dd7e60e956f008aa/mkroellmkroell2008-09-12T15:31:07+02:00intention query ambiguity WebSearch WWW09 <span style="color:#555555;">Ruihua <a href="http://www.bibsonomy.org/author/Song">Song</a> und Zhenxiao <a href="http://www.bibsonomy.org/author/Luo">Luo</a> und Ji-Rong <a href="http://www.bibsonomy.org/author/Wen">Wen</a> und Yong <a href="http://www.bibsonomy.org/author/Yu">Yu</a> und Hsiao-Wuen <a href="http://www.bibsonomy.org/author/Hon">Hon</a> </span><em>WWW '07: Proceedings of the 16th international conference on World Wide Web, </em><em>Seite1169--1170. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2007</em>)Fri Sep 12 15:31:07 CEST 2008New York, NY, USAWWW '07: Proceedings of the 16th international conference on World Wide Web1169--1170Identifying ambiguous queries in web search2007intention query ambiguity WebSearch WWW09 Web search intent induction via automatic query reformulation - CiteSeerXhttp://www.bibsonomy.org/bibtex/29a1356c4176c1eaa579ccc61dc9b7677/mkroellmkroell2008-09-10T12:31:23+02:00intention search query WebSearch toread WWW09 <span style="color:#555555;">Hal Daume <a href="http://www.bibsonomy.org/author/III">III</a> und Eric <a href="http://www.bibsonomy.org/author/Brill">Brill</a> </span><em>North American Association for Computational Linguistics, </em><em>Seite49--52. </em>(<em>2004</em>)Wed Sep 10 12:31:23 CEST 2008North American Association for Computational Linguistics49--52Web search intent induction via automatic query reformulation2004intention search query WebSearch toread WWW09 Semantic similarity between search engine queries using temporal correlationhttp://www.bibsonomy.org/bibtex/25d62240773c5850568c85cd1462027dd/mkroellmkroell2008-09-09T16:11:38+02:00search query temporal similarity WebSearch toread ReadingGroup WWW09 <span style="color:#555555;">Steve <a href="http://www.bibsonomy.org/author/Chien">Chien</a> und Nicole <a href="http://www.bibsonomy.org/author/Immorlica">Immorlica</a> </span><em>WWW '05: Proceedings of the 14th international conference on World Wide Web, </em><em>Seite2--11. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2005</em>)Tue Sep 09 16:11:38 CEST 2008New York, NY, USAWWW '05: Proceedings of the 14th international conference on World Wide Web2--11Semantic similarity between search engine queries using temporal correlation2005search query temporal similarity WebSearch toread ReadingGroup WWW09 We investigate the idea of finding semantically related search engine queries based on their temporal correlation; in other words, we infer that two queries are related if their popularities behave similarly over time. To this end, we first define a new measure of the temporal correlation of two queries based on the correlation coefficient of their frequency functions. We then conduct extensive experiments using our measure on two massive query streams from the MSN search engine, revealing that this technique can discover a wide range of semantically similar queries. Finally, we develop a method of efficiently finding the highest correlated queries for a given input query using far less space and time than the naive approach, making real-time implementation possible.Personalized web search by mapping user queries to categorieshttp://www.bibsonomy.org/bibtex/2d5197251b456325659aceb68eb2032bc/mkroellmkroell2008-09-09T11:16:21+02:00personalization search query classification WebSearch toread WWW09 <span style="color:#555555;">Fang <a href="http://www.bibsonomy.org/author/Liu">Liu</a> und Clement <a href="http://www.bibsonomy.org/author/Yu">Yu</a> und Weiyi <a href="http://www.bibsonomy.org/author/Meng">Meng</a> </span><em>CIKM '02: Proceedings of the eleventh international conference on Information and knowledge management, </em><em>Seite558--565. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2002</em>)Tue Sep 09 11:16:21 CEST 2008New York, NY, USACIKM '02: Proceedings of the eleventh international conference on Information and knowledge management558--565Personalized web search by mapping user queries to categories2002personalization search query classification WebSearch toread WWW09 Current web search engines are built to serve all users, independent of the needs of any individual user. Personalization of web search is to carry out retrieval for each user incorporating his/her interests. We propose a novel technique to map a user query to a set of categories, which represent the user's search intention. This set of categories can serve as a context to disambiguate the words in the user's query. A user profile and a general profile are learned from the user's search history and a category hierarchy respectively. These two profiles are combined to map a user query into a set of categories. Several learning and combining algorithms are evaluated and found to be effective. Among the algorithms to learn a user profile, we choose the Rocchio-based method for its simplicity, efficiency and its ability to be adaptive. Experimental results indicate that our technique to personalize web search is both effective and efficient.