Analyzing Tag Semantics Across Collaborative Tagging Systems.
In: H. Alani, S. Staab and G. Stumme, editors,
Proceedings of the Dagstuhl Seminar on Social Web Communities.
2008.
Dominik Benz, Marko Grobelnik, Andreas Hotho, Robert Jäschke, Dunja Mladenic, Vito D. P. Servedio, Sergej Sizov and Martin Szomszor.
[doi]
[abstract]
[BibTeX]
The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance.
Analyzing Tag Semantics Across Collaborative Tagging Systems.
In: H. Alani, S. Staab and G. Stumme, editors,
Proceedings of the Dagstuhl Seminar on Social Web Communities.
2008.
Dominik Benz, Marko Grobelnik, Andreas Hotho, Robert Jäschke, Dunja Mladenic, Vito D. P. Servedio, Sergej Sizov and Martin Szomszor.
[doi]
[abstract]
[BibTeX]
The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance.
Analyzing Tag Semantics Across Collaborative Tagging Systems.
In: H. Alani, S. Staab and G. Stumme, editors,
Social Web Communities, series Dagstuhl Seminar Proceedings.
Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, 2008.
Dominik Benz, Marko Grobelnik, Andreas Hotho, Robert Jäschke, Dunja Mladenic, Vito D. P. Servedio, Sergej Sizov and Martin Szomszor.
[doi]
[abstract]
[BibTeX]
The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance.
Discovering Shared Conceptualizations in Folksonomies.
Journal of Web Semantics, 6(1):38-53, 2008.
Robert Jäschke, Andreas Hotho, Christoph Schmitz, Bernhard Ganter and Gerd Stumme.
[doi]
[BibTeX]
Discovering Shared Conceptualizations in Folksonomies.
Web Semantics: Science, Services and Agents on the World Wide Web, 6(1):38-53, 2008.
Robert Jäschke, Andreas Hotho, Christoph Schmitz, Bernhard Ganter and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.
Discovering Shared Conceptualizations in Folksonomies.
Web Semantics: Science, Services and Agents on the World Wide Web, 6(1):38-53, 2008.
Robert Jäschke, Andreas Hotho, Christoph Schmitz, Bernhard Ganter and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.
Discovering Shared Conceptualizations in Folksonomies.
Journal of Web Semantics, 6(1):38-53, 2008.
Robert Jäschke, Andreas Hotho, Christoph Schmitz, Bernhard Ganter and Gerd Stumme.
[doi]
[BibTeX]
Logsonomy - A Search Engine Folksonomy.
In:
Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008).
AAAI Press, 2008.
Robert Jäschke, Beate Krause, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Logsonomy - A Search Engine Folksonomy.
In:
Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008).
AAAI Press, 2008.
Robert Jäschke, Beate Krause, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Logsonomy - A Search Engine Folksonomy.
In:
Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008).
AAAI Press, 2008.
Robert Jäschke, Beate Krause, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Logsonomy - A Search Engine Folksonomy.
In:
Proceedings of the Second International Conference on Weblogs and Social Media (ICWSM 2008), pages 192-193.
AAAI Press, Menlo Park, CA, USA, 2008.
Robert Jäschke, Beate Krause, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Logsonomy — A Search Engine Folksonomy.
In:
Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008).
AAAI Press, 2008.
Robert Jäschke, Beate Krause, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Tag Recommendations in Social Bookmarking Systems.
AI Communications, 21(4):231-247, 2008.
Robert Jäschke, Leandro Marinho, Andreas Hotho, Lars Schmidt-Thieme and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Collaborative tagging systems allow users to assign keywords - so called "tags" - to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied.
In this paper we evaluate and compare several recommendation algorithms on large-scale real life datasets: an adaptation of
user-based collaborative filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag occurences. We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We show, how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender.
Tag Recommendations in Social Bookmarking Systems.
AI Communications, 21(4):231-247, 2008.
Robert Jäschke, Leandro Marinho, Andreas Hotho, Lars Schmidt-Thieme and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Collaborative tagging systems allow users to assign keywords - so called "tags" - to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied. In this paper we evaluate and compare several recommendation algorithms on large-scale real life datasets: an adaptation of user-based collaborative filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag occurences. We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We show, how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender.
Tag Recommendations in Social Bookmarking Systems.
AI Communications, 21(4):231-247, 2008.
Robert Jäschke, Leandro Marinho, Andreas Hotho, Lars Schmidt-Thieme and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Collaborative tagging systems allow users to assign keywords - so called "tags" - to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied. In this paper we evaluate and compare several recommendation algorithms on large-scale real life datasets: an adaptation of user-based collaborative filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag occurences. We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We show, how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender.
Logsonomy - Social Information Retrieval with Logdata.
In:
HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia, pages 157-166.
ACM, New York, NY, USA, 2008.
Beate Krause, Robert Jäschke, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Logsonomy - Social Information Retrieval with Logdata.
In:
HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia, pages 157-166.
ACM, New York, NY, USA, 2008.
Beate Krause, Robert Jäschke, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Logsonomy - Social Information Retrieval with Logdata.
In:
HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia, pages 157-166.
ACM, New York, NY, USA, 2008.
Beate Krause, Robert Jäschke, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Logsonomy - Social Information Retrieval with Logdata.
In:
HT '08: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia, pages 157-166.
ACM, New York, NY, USA, 2008.
Beate Krause, Robert Jäschke, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Logsonomy - social information retrieval with logdata.
In:
HT '08: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia, pages 157-166.
ACM, New York, NY, USA, 2008.
Beate Krause, Robert Jäschke, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.