@inproceedings{krause2008logsonomy, title = {Logsonomy - Social Information Retrieval with Logdata}, address = {New York, NY, USA}, author = {Beate Krause and Robert Jäschke and Andreas Hotho and Gerd Stumme}, booktitle = {HT '08: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia}, pages = {157--166}, publisher = {ACM}, year = 2008, url = {http://portal.acm.org/citation.cfm?id=1379092.1379123&coll=ACM&dl=ACM&type=series&idx=SERIES399&part=series&WantType=Journals&title=Proceedings%20of%20the%20nineteenth%20ACM%20conference%20on%20Hypertext%20and%20hypermedia}, location = {Pittsburgh, PA, USA}, isbn = {978-1-59593-985-2}, doi = {http://doi.acm.org/10.1145/1379092.1379123}, abstract = {Social bookmarking systems constitute an established part of the Web 2.0. In such systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Today’s search engines represent the gateway to retrieve information from the World Wide Web. Short queries typically consisting of two to three words describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. This clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonomies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a large snapshot of del.icio.us and on query logs of two large search engines. All of the three datasets show small world properties. The tagging behavior of users, which is explained by preferential attachment of the tags in social bookmark systems, is reflected in the distribution of single query words in search engines. We can conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of social bookmarking users is driven by similar dynamics.}, biburl = {http://www.bibsonomy.org/bibtex/276d81124951ae39060a8bc98f4883435/jaeschke}, keywords = {social logsonomy retrieval information network for:nepomuk wp5 analysis search l3s engine} } @inproceedings{krause2008logsonomy, title = {Logsonomy - Social Information Retrieval with Logdata}, address = {New York, NY, USA}, author = {Beate Krause and Robert Jäschke and Andreas Hotho and Gerd Stumme}, booktitle = {HT '08: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia}, pages = {157--166}, publisher = {ACM}, year = 2008, url = {http://portal.acm.org/citation.cfm?id=1379092.1379123&coll=ACM&dl=ACM&type=series&idx=SERIES399&part=series&WantType=Journals&title=Proceedings%20of%20the%20nineteenth%20ACM%20conference%20on%20Hypertext%20and%20hypermedia}, location = {Pittsburgh, PA, USA}, isbn = {978-1-59593-985-2}, doi = {http://doi.acm.org/10.1145/1379092.1379123}, abstract = {Social bookmarking systems constitute an established part of the Web 2.0. In such systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Today’s search engines represent the gateway to retrieve information from the World Wide Web. Short queries typically consisting of two to three words describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. This clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonomies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a large snapshot of del.icio.us and on query logs of two large search engines. All of the three datasets show small world properties. The tagging behavior of users, which is explained by preferential attachment of the tags in social bookmark systems, is reflected in the distribution of single query words in search engines. We can conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of social bookmarking users is driven by similar dynamics.}, biburl = {http://www.bibsonomy.org/bibtex/276d81124951ae39060a8bc98f4883435/nepomuk}, keywords = {analysis search l3s from:jaeschke social wp5 information network retrieval logsonomy engine} } @inproceedings{Jaeschke2008logsonomy, title = {Logsonomy — A Search Engine Folksonomy}, author = {Robert Jäschke and Beate Krause and Andreas Hotho and Gerd Stumme}, booktitle = {Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)}, publisher = {AAAI Press}, year = 2008, url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf}, abstract = {In social bookmarking systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Search engines filter the vast information of the web. Queries describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. The clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. This poster analyzes the topological characteristics of the resulting tripartite hypergraph of queries, users and bookmarks of two query logs and compares it two a snapshot of the folksonomy del.icio.us.}, biburl = {http://www.bibsonomy.org/bibtex/2359e1eccdc524334d4a2ad51330f76ae/jaeschke}, keywords = {search logsonomy engine folksonomy l3s for:nepomuk wp5 myown 2008} } @inproceedings{Jaeschke2008logsonomy, title = {Logsonomy — A Search Engine Folksonomy}, author = {Robert Jäschke and Beate Krause and Andreas Hotho and Gerd Stumme}, booktitle = {Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)}, publisher = {AAAI Press}, year = 2008, url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf}, abstract = {In social bookmarking systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Search engines filter the vast information of the web. Queries describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. The clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. This poster analyzes the topological characteristics of the resulting tripartite hypergraph of queries, users and bookmarks of two query logs and compares it two a snapshot of the folksonomy del.icio.us.}, biburl = {http://www.bibsonomy.org/bibtex/2359e1eccdc524334d4a2ad51330f76ae/nepomuk}, keywords = {wp5 myown logsonomy 2008 folksonomy engine l3s from:jaeschke search} } @inproceedings{Jaeschke2008logsonomy, title = {Logsonomy — A Search Engine Folksonomy}, author = {Robert Jäschke and Beate Krause and Andreas Hotho and Gerd Stumme}, booktitle = {Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)}, publisher = {AAAI Press}, year = 2008, url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf}, abstract = {In social bookmarking systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Search engines filter the vast information of the web. Queries describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. The clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. This poster analyzes the topological characteristics of the resulting tripartite hypergraph of queries, users and bookmarks of two query logs and compares it two a snapshot of the folksonomy del.icio.us.}, biburl = {http://www.bibsonomy.org/bibtex/2359e1eccdc524334d4a2ad51330f76ae/beate}, keywords = {myown 2008 search logsonomy folksonomy analysis} } @inproceedings{Jaeschke2008logsonomy, title = {Logsonomy — A Search Engine Folksonomy}, author = {Robert Jäschke and Beate Krause and Andreas Hotho and Gerd Stumme}, booktitle = {Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)}, publisher = {AAAI Press}, year = 2008, url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf}, abstract = {In social bookmarking systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Search engines filter the vast information of the web. Queries describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. The clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. This poster analyzes the topological characteristics of the resulting tripartite hypergraph of queries, users and bookmarks of two query logs and compares it two a snapshot of the folksonomy del.icio.us.}, biburl = {http://www.bibsonomy.org/bibtex/2359e1eccdc524334d4a2ad51330f76ae/stumme}, keywords = {2008 search folksonomy folksonomies tagorapub logsonomies myown logsonomy engine} } @inproceedings{Jaeschke2008logsonomy, title = {Logsonomy — A Search Engine Folksonomy}, author = {Robert Jäschke and Beate Krause and Andreas Hotho and Gerd Stumme}, booktitle = {Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)}, publisher = {AAAI Press}, year = 2008, url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf}, abstract = {In social bookmarking systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Search engines filter the vast information of the web. Queries describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. The clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. This poster analyzes the topological characteristics of the resulting tripartite hypergraph of queries, users and bookmarks of two query logs and compares it two a snapshot of the folksonomy del.icio.us.}, biburl = {http://www.bibsonomy.org/bibtex/2359e1eccdc524334d4a2ad51330f76ae/hotho}, keywords = {query log logsonomy folksonomy 2008 network search myown icwsm analysis} } @article{zhang2002web, title = {A novel Web usage mining approach for search engines}, author = {Dell Zhang and Yisheng Dong}, journal = {Computer Networks}, month = {june}, number = 3, pages = {303--310}, volume = 39, year = 2002, url = {http://www.sciencedirect.com/science/article/B6VRG-45H0GV7-5/2/16726cebdcde67ba7aeb95cc91e797bf}, description = {ScienceDirect - Computer Networks : A novel Web usage mining approach for search engines}, biburl = {http://www.bibsonomy.org/bibtex/20b9b9522a5863d74796f54877c5fbe04/beate}, keywords = {clickdata logsonomy link-analysis hits folkrank} } @inproceedings{yates2007log, title = {Extracting semantic relations from query logs}, address = {New York, NY, USA}, author = {Ricardo Baeza-Yates and Alessandro Tiberi}, booktitle = {KDD '07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining}, pages = {76--85}, publisher = {ACM}, year = 2007, url = {http://portal.acm.org/citation.cfm?id=1281204}, id = {2229158}, priority = {0}, isbn = {9781595936097}, doi = {10.1145/1281192.1281204}, biburl = {http://www.bibsonomy.org/bibtex/26e45b65feffd1545c6dca62bf4b8f53d/beate}, keywords = {clustering queries link-analysis logsonomy} }