| Author | Title | Year | Journal/Proceedings | Reftype | DOI/URL |
|---|---|---|---|---|---|
| Jäschke, R., Krause, B., Hotho, A. & Stumme, G. | Logsonomy -- A Search Engine Folksonomy | 2008 | Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008) | inproceedings | URL |
| Abstract: In social bookmarking systems users describe bookmarksby keywords called tags. The structure behindthese social systems, called folksonomies, can beviewed as a tripartite hypergraph of user, tag and resourcenodes. This underlying network shows specificstructural properties that explain its growth and the possibilityof serendipitous exploration.Search engines filter the vast information of the web.Queries describe a user’s information need. In responseto the displayed results of the search engine, users clickon the links of the result page as they expect the answerto be of relevance. The clickdata can be represented as afolksonomy in which queries are descriptions of clickedURLs. This poster analyzes the topological characteristicsof the resulting tripartite hypergraph of queries,users and bookmarks of two query logs and compares ittwo a snapshot of the folksonomy del.icio.us. | |||||
BibTeX:
@inproceedings{jaeschke2008logsonomy,
author = {Jäschke, Robert and Krause, Beate and Hotho, Andreas and Stumme, Gerd},
title = {Logsonomy -- A Search Engine Folksonomy},
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}
}
|
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| Gwizdka, J. & Cole, M. | Finding It on Google, Finding It on del.icio.us. [BibTeX] |
2007 | ECDL | inproceedings | URL |
BibTeX:
@inproceedings{gwizdka2007finding,
author = {Gwizdka, Jacek and Cole, Michael},
title = {Finding It on Google, Finding It on del.icio.us.},
booktitle = {ECDL},
publisher = {Springer},
year = {2007},
volume = {4675},
pages = {559-562},
url = {http://dblp.uni-trier.de/db/conf/ercimdl/ecdl2007.html#GwizdkaC07}
}
|
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| Yanbe, Y., Jatowt, A., Nakamura, S. & Tanaka, K. | Can social bookmarking enhance search in the web? [BibTeX] |
2007 | JCDL '07: Proceedings of the 2007 conference on Digital libraries | inproceedings | DOIURL |
BibTeX:
@inproceedings{yanbe2007can,
author = {Yanbe, Yusuke and Jatowt, Adam and Nakamura, Satoshi and Tanaka, Katsumi},
title = {Can social bookmarking enhance search in the web?},
booktitle = {JCDL '07: Proceedings of the 2007 conference on Digital libraries},
publisher = {ACM Press},
year = {2007},
pages = {107--116},
url = {http://portal.acm.org/citation.cfm?id=1255175.1255198},
doi = {http://doi.acm.org/10.1145/1255175.1255198}
}
|
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| Baeza-Yates, R., Calderón-Benavides, L. & González-Caro, C. | The Intention Behind Web Queries | 2006 | String Processing and Information Retrieval | incollection | URL |
| Abstract: The identification of the user’s intention or interest through queries that they submit to a search engine can be very usefulto offer them more adequate results. In this work we present a framework for the identification of user’s interest in an automaticway, based on the analysis of query logs. This identification is made from two perspectives, the objectives or goals of auser and the categories in which these aims are situated. A manual classification of the queries was made in order to havea reference point and then we applied supervised and unsupervised learning techniques. The results obtained show that fora considerable amount of cases supervised learning is a good option, however through unsupervised learning we found relationshipsbetween users and behaviors that are not easy to detect just taking the query words. Also, through unsupervised learning weestablished that there are categories that we are not able to determine in contrast with other classes that were not consideredbut naturally appear after the clustering process. This allowed us to establish that the combination of supervised and unsupervisedlearning is a good alternative to find user’s goals. From supervised learning we can identify the user interest given certainestablished goals and categories; on the other hand, with unsupervised learning we can validate the goals and categories used,refine them and select the most appropriate to the user’s needs. | |||||
BibTeX:
@incollection{baezayates2006intention,
author = {Baeza-Yates, Ricardo and Calderón-Benavides, Liliana and González-Caro, Cristina},
title = {The Intention Behind Web Queries},
booktitle = {String Processing and Information Retrieval},
publisher = {Springer Berlin / Heidelberg},
year = {2006},
pages = {98--109},
url = {http://dx.doi.org/10.1007/11880561_9}
}
|
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| Hotho, A., J�schke, R., Schmitz, C. & Stumme, G. | Information Retrieval in Folksonomies: Search and Ranking | 2006 | The Semantic Web: Research and Applications | inproceedings | URL |
| Abstract: 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. | |||||
BibTeX:
@inproceedings{hotho06-information,
author = {Hotho, Andreas and J�schke, Robert and Schmitz, Christoph and Stumme, Gerd},
title = {Information Retrieval in Folksonomies: Search and Ranking},
booktitle = {The Semantic Web: Research and Applications},
publisher = {Springer},
year = {2006},
volume = {4011},
pages = {411-426},
url = {http://.kde.cs.uni-kassel.de/hotho}
}
|
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| Hotho, A., Jäschke, R., Schmitz, C. & Stumme, G. | Information Retrieval in Folksonomies: Search and Ranking | 2006 | The Semantic Web: Research and Applications | inproceedings | |
| Abstract: 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 findcommunities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset. | |||||
BibTeX:
@inproceedings{hotho2006information,
author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
title = {Information Retrieval in Folksonomies: Search and Ranking},
booktitle = {The Semantic Web: Research and Applications},
publisher = {Springer},
year = {2006},
volume = {4011},
pages = {411-426}
}
|
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