http://www.bibsonomy.org/rss/user/mstrohm/searchBibSonomy RSS Feed for /user/mstrohm/searchThe real, last, big Whole Earth Catalog.http://www.wholeearth.com/issue-electronic-edition.php?iss=1330mstrohm2012-01-23T04:23:35+01:00historical knowledge-management search web-science The real, last, big Whole Earth Catalog.http://iiix2010.org/hcir.phpmstrohm2010-02-08T12:08:02+01:00commonsense goals search workshop http://www.wsdm-conference.org/2010/accepted-papers.htmlmstrohm2009-12-26T17:35:15+01:00conference mining search on &#039;googlewhacking&#039;http://www.timemachinego.com/linkmachinego/2009/11/16/me-and-belle-de-jour-could-it-be-brooke/mstrohm2009-12-17T13:36:20+01:00hacking motivation search on &#039;googlewhacking&#039;including LSA / LSIhttp://www.miislita.com/mstrohm2009-12-14T14:17:33+01:00knowledge-acquisition mining search tutorial including LSA / LSIhttp://lemurstudy.cs.umass.edu/mstrohm2009-12-06T11:12:17+01:00datasets query-log-analysis search &#034;buying a prius&#034; Google vs Binghttp://searchengineland.com/search-where-does-it-go-from-here-30630mstrohm2009-11-29T10:59:48+01:00goals search &#034;buying a prius&#034; Google vs BingMarti Hearsthttp://www.youtube.com/watch?v=BpBAg4Ndi9w&amp;feature=player_embeddedmstrohm2009-11-26T09:51:47+01:00information-retrieval lecture search Marti Hearsthttp://workshops.fxpal.com/cscw2010cis/Overview.aspxmstrohm2009-11-04T21:30:10+01:00search social-search workshop http://www.yorku.ca/wiiat10/index.phpmstrohm2009-11-03T14:09:01+01:00conference knowledge-management search web-science on the origin of hash tags in twitter (2007!)http://factoryjoe.com/blog/2007/08/25/groups-for-twitter-or-a-proposal-for-twitter-tag-channels/mstrohm2009-09-25T18:32:55+02:00historical search social-search twitter on the origin of hash tags in twitter (2007!)http://clubs.ya.ru/company/replies.xml?item_no=19430&amp;ncrnd=6871mstrohm2009-09-18T18:20:56+02:00intentional lecture search http://technology.timesonline.co.uk/tol/news/tech_and_web/article4213681.ecemstrohm2009-08-31T19:12:49+02:00goals motivation search social-factors social-search why we can&#039;t quit searchinghttp://www.slate.com/id/2224932/mstrohm2009-08-19T02:23:22+02:00cognition search why we can&#039;t quit searchingPaper: http://appsrv.cse.cuhk.edu.hk/~hma/Poster_SigIR09_Hao.pdfhttp://pagehunt.msrlivelabs.com/AboutPageHunt.htmmstrohm2009-07-28T16:41:50+02:00games knowledge-acquisition search tools web-science Paper: http://appsrv.cse.cuhk.edu.hk/~hma/Poster_SigIR09_Hao.pdfCategory system structure in search interfaces is usually one of flat, hierarchical, or faceted. A flat list of categories works well for presenting a list of choices with which to narrow the contents of a collection, but needs to be limited to a small set in order to be scannable. Hierarchical (or tree-structured) category systems are useful and can be easy to understand for relatively simple information structures. However, a problem with assigning documents to single categories within a hierarchy is that many information items are best described by multiple different categories simultaneously. This use of hierarchical faceted metadata provides a usable method for allowing users to browse information collections according to multiple categories simultaneously (Hearst, 2000, Hearst et al., 2002). The main idea is to build a set of category hierarchies, each of which corresponds to a different facet (dimension or feature type) that is relevant to the collection to be navigated. Each facet has a set of labels associated with it, and if this set is large, it may be organized into a hierarchy. After the facet hierarchies are designed, each item in the collection can be assigned any number of labels from any number of facets. In a properly designed faceted navigation interface, the user can browse the information collection from any of the different facets as a starting point, and after starting with one facet, can then navigate using any other facet. Usability results suggest that this kind of interface is highly usable for navigation of information collections with somewhat homogeneous content (English et al., 2001, Hearst et al., 2002, Yee et al., 2003). http://searchuserinterfaces.com/book/sui_ch1_design.htmlmstrohm2009-07-23T13:26:28+02:00search Category system structure in search interfaces is usually one of flat, hierarchical, or faceted. A flat list of categories works well for presenting a list<span class="info">...<div>Category system structure in search interfaces is usually one of flat, hierarchical, or faceted. A flat list of categories works well for presenting a list of choices with which to narrow the contents of a collection, but needs to be limited to a small set in order to be scannable. Hierarchical (or tree-structured) category systems are useful and can be easy to understand for relatively simple information structures. However, a problem with assigning documents to single categories within a hierarchy is that many information items are best described by multiple different categories simultaneously. This use of hierarchical faceted metadata provides a usable method for allowing users to browse information collections according to multiple categories simultaneously (Hearst, 2000, Hearst et al., 2002). The main idea is to build a set of category hierarchies, each of which corresponds to a different facet (dimension or feature type) that is relevant to the collection to be navigated. Each facet has a set of labels associated with it, and if this set is large, it may be organized into a hierarchy. After the facet hierarchies are designed, each item in the collection can be assigned any number of labels from any number of facets. In a properly designed faceted navigation interface, the user can browse the information collection from any of the different facets as a starting point, and after starting with one facet, can then navigate using any other facet. Usability results suggest that this kind of interface is highly usable for navigation of information collections with somewhat homogeneous content (English et al., 2001, Hearst et al., 2002, Yee et al., 2003). </div></span>http://www.readwriteweb.com/archives/future_of_search_social_relevancy_rank.phpmstrohm2009-07-18T11:51:45+02:00search social-factors social-search http://palblog.fxpal.com/?p=1220mstrohm2009-07-16T10:20:56+02:00information-retrieval search textbooks http://anyall.org/blog/2009/04/1-billion-web-page-dataset-from-cmu/mstrohm2009-06-30T10:26:22+02:00datasets mining search Third International Conference on Web Search and Data Mininghttp://www.wsdm-conference.org/2010/mstrohm2009-06-23T11:54:03+02:00conference mining search Third International Conference on Web Search and Data Mining