BibSonomy publications for /concept/tag/tagoraWed Jul 30 10:52:43 CEST 2008Proceedings of the WWW 2008 Poster SessionPersonalized Search and Exploration with MyTag2008koblenz personalized search braun tagorapub 2008 exploration saathoff metzler rostilov MyTag hagen franz tagora www dellschaft jungen hering Wed Jul 30 10:50:32 CEST 2008HYPERTEXT 2008, Proceedings of the 19th ACM Conference on Hypertext and HypermediaAn Epistemic Dynamic Model for Tagging Systems2008systems hypertext dynamic koblenz 2008 tagorapub staab epistemic tagging model tagora dellschaft In recent literature, several models were proposed for reproducing
and understanding the tagging behavior of users.
They all assume that the tagging behavior is influenced by
the previous tag assignments of other users. But they are
only partially successful in reproducing characteristic properties
found in tag streams. We argue that this inadequacy
of existing models results from their inability to include
user’s background knowledge into their model of tagging
behavior. This paper presents a generative tagging model
that integrates both components, the background knowledge
and the influence of previous tag assignments. Our
model successfully reproduces characteristic properties of
tag streams. It even explains effects of the user interface
on the tag stream.Tue Jun 10 22:32:17 CEST 2008Baden-BadenSocial Software in der WertschöpfungDas Entstehen von Semantik in BibSonomy2006tagorapub schmitz semantics jaeschke nepomuk tagging hotho folksonomies stumme BibSonomy bibsonomy pagerank tags rules folkrank tagora UniK semantik 2006 association folksonomy Immer mehr Soziale-Lesezeichen-Systeme entstehen im heutigen Web. In solchen Systemen erstellen die Nutzer leichtgewichtige begriffliche Strukturen, so genannte Folksonomies. Ihren Erfolg verdanken sie der Tatsache, dass man keine speziellen Fähigkeiten benötigt, um an der Gestaltung mitzuwirken. In diesem Artikel beschreiben wir unser System BibSonomy. Es erlaubt das Speichern, Verwalten und Austauschen sowohl von Lesezeichen (Bookmarks) als auch von Literaturreferenzen in Form von BibTeX-Einträgen. Die Entwicklung des verwendeten Vokabulars und der damit einhergehenden Entstehung einer gemeinsamen Semantik wird detailliert diskutiert.Tue Jun 10 14:05:05 CEST 2008Tag Recommendations in Folksonomies2007tagora folksonomy paper recommendation read:2008 tagging kassel nepomuk bibsonomy folkrank last.fm uni del.icio.us Sun Jun 08 12:59:40 CEST 20084th European Semantic Web Conference, Bridging the Gap between Semantic Web and Web 2.0Folksonomies, the Semantic Web, and Movie Recommendation 2007filtering kind-of-tags read:2008 tags semantic folksonomies tagora web recommendation paper web2.0 netflix imdb collaborative movies While the Semantic Web has evolved to support the meaningful exchange of heterogeneous data through shared and controlled conceptualisations, Web 2.0 has demonstrated that large-scale community tagging sites can enrich the semantic web with readily accessible and valuable knowledge. In this paper, we investigate the integration of a movies folksonomy with a semantic knowledge base about user-movie rentals. The folksonomy is used to enrich the knowledge base with descriptions and categorisations of movie titles, and user interests and opinions. Using tags harvested from the Internet Movie Database, and movie rating data gathered by Netflix, we perform experiments to investigate the question that folksonomy-generated movie tag-clouds can be used to construct better user profiles that reflect a user’s level of interest in different kinds of movies, and therefore, provide a basis for prediction of their rating for a previously unseen movie.Fri Jun 06 11:48:57 CEST 2008ACM Confrence on Hypertext and HypermediaJuneCorrelating User Profiles from Multiple Folksonomies2008folksonomies tagora user-profiles tagorapub Fri Jun 06 11:48:35 CEST 20081st International Workshop on Collective Semantics: Collective Intelligence \& the Semantic Web (CISWeb 2008) JuneEnriching Ontological User Profiles with Tagging History for Multi-Domain Recommendations
2008tagora tag-filtering user-profiles tagorapub recommendation-systems Fri Jun 06 11:45:26 CEST 20084th European Semantic Web Conference, Bridging the Gap between Semantic Web and Web 2.0Folksonomies, the Semantic Web, and Movie Recommendation 2007tagorapub recommendations folksonomies netflix imdb tagora Thu May 08 11:32:59 CEST 2008Proceedings of ECIR'08 Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR 2008)3Introducing Triple Play for Improved Resource Retrieval in Collaborative Tagging Systems20082008 collaborative system folksonomy tripleplay search staab tagorapub retrieval folksonomies esair information abbasi ecir tagora tagging Collaborative tagging systems (like Flickr, del.icio.us, citeulike, etc.) are becoming more popular with passage of time. Users share their resources on tagging systems, and add keywords (called tags) to these resources. Users can search resources using these tags. But as the user gives more tags for search, he might not get sufficient search results, because the resources might not be tagged with all the related tags.
We introduce the method Triple Play, which smoothes the tag space by user space for improved retrieval of resources. As a part of Triple Play, we also propose two new vector space models for collaborative tagging systems, SmoothVSM Dense and SmoothVSM Sparse. These vector space models exploit the user-tag co-occurrence relationship to overcome the problem of missing information in tagging systems. Finally we apply Latent Semantic Analysis to different vector space models and analyze the results. Initial experimentation show that using additional information available in tagging systems helps in improving search in tagging systems.Wed Mar 12 16:41:13 CET 2008OctStatistical physics of social dynamics2007statistical loreto tagora social review physics Statistical physics has proven to be a very fruitful framework to describe
phenomena outside the realm of traditional physics. The last years have
witnessed the attempt by physicists to study collective phenomena emerging from
the interactions of individuals as elementary units in social structures. Here
we review the state of the art by focusing on three major research lines i.e.,
opinion, cultural and language dynamics. In addition we discuss other social
phenomena, such as crowd behavior, hierarchy formation, human dynamics, social
spreading. We highlight the connections between these problems and other, more
traditional, topics of statistical physics. We also emphasize the comparison of
model results with empirical data from social systems.Fri Feb 15 14:44:26 CET 2008Tampa Bay, USAProceedings of the Seventh International Workshop on Peer-to-Peer Systems, IPTPS08February{PINTS}: Peer-to-Peer Infrastructure for Tagging Systems2008staab tagging görlitz sizov pints tagorapub tagora p2p Sun Feb 10 02:19:38 CET 2008NovemberFolksonomy Definition and Wikipedia2005text-mining folksonomy tagging wikipedia WW-MUST tagora semantic d41, Fri Jan 04 16:59:10 CET 2008Graz, AustriaI-KNOW '07. 7th International Conference on Knowledge Management@PROCEEDINGS{ToMa07,
title = {Proceedings of I-KNOW 2007},
year = {2007},
editor = {Tochtermann, Klaus and Maurer, Herrmann},
keywords = {knowledgemanagement iknow DISS ownstuff},
timestamp = {2007.11.06}
}SeptemberConceptual Clustering of Social Bookmarking Sites2007social tagorapub l3s tagging_efficiency DISS folksonomy 2007 semantics iknow ontologies tagging_semantics clustering tagora toread tagging_clustering tagging bookmarking folkrank myown Currently, social bookmarking systems provide intuitive support for
browsing locally their content. A global view is usually presented
by the tag cloud of the system, but it does not allow a conceptual
drill-down, e. g., along a conceptual hierarchy. In this paper, we
present a clustering approach for computing such a conceptual hierarchy
for a given folksonomy. The hierarchy is complemented with ranked
lists of users and resources most related to each cluster. The rankings
are computed using our FolkRank algorithm. We have evaluated our
approach on large scale data from the del.icio.us bookmarking system.Sat Oct 13 14:11:57 CEST 20074th International Workshop on Text-Based Information RetrievalAspects of Broad Folksonomies2007Tagora collaborative_tagging Folksonomies, collaboratively created sets of metadata,
are becoming more and more important for organising in-
formation and knowledge of communites in the Web. While
for a single user the difference to keyword assignment is
marginal, the power of folksonomies emerges from the col-
laborative aspects. Folksonomies are already issue of re-
search. Within this publication we analyse underlying sta-
tistical properties of broad folksonomies aiming to iden-
tify laws and characteristics, which allow inferring prop-
erties for folksonomy based retrieval. The actual bene-
fit of folksonomies for retrieval and the derived methods
are concluded from experiments with aggregated data from
del.icio.us.Mon Aug 06 11:39:48 CEST 20074th International Workshop on Text-Based Information RetrievalAspects of Broad Folksonomies2007broad retrieval paper ciro tagora folksonomies Folksonomies, collaboratively created sets of metadata,
are becoming more and more important for organising in-
formation and knowledge of communites in the Web. While
for a single user the difference to keyword assignment is
marginal, the power of folksonomies emerges from the col-
laborative aspects. Folksonomies are already issue of re-
search. Within this publication we analyse underlying sta-
tistical properties of broad folksonomies aiming to iden-
tify laws and characteristics, which allow inferring prop-
erties for folksonomy based retrieval. The actual bene-
fit of folksonomies for retrieval and the derived methods
are concluded from experiments with aggregated data from
del.icio.us.Tue Jun 26 10:39:47 CEST 2007Innsbruck, AustriaBridging the Gap between Semantic Web and Web 2.0, workshop at ESWC 20076Organizing Resources on Tagging Systems using T-ORG2007torg abbasi staab unikold classification 2007 folksonomies tagora tagging eswc tagorapub cimiano Fri Jun 08 12:52:09 CEST 2007New York5th editionCognitive Psychology and Its Implications2000cognitive psychology tagora Fri May 25 23:45:57 CEST 2007New York, NY, USAProceedings of the 16th nternational World Wide Web Conference (WWW'07)The Complex Dynamics of Collaborative Tagging2007tagging attachment frequency zipf complexity tagora distribution complex preferential network model co-occurence The debate within the Web community over the optimal means
by which to organize information often pits formalized classications
against distributed collaborative tagging systems. A number
of questions remain unanswered, however, regarding the nature of
collaborative tagging systems including whether coherent categorization
schemes can emerge from unsupervised tagging by users.
This paper uses data from the social bookmarking site del.icio.us to
examine the dynamics of collaborative tagging systems. In particular,
we examine whether the distribution of the frequency of use
of tags for popular sites with a long history (many tags and many
users) can be described by a power law distribution, often characteristic
of what are considered complex systems. We produce a
generative model of collaborative tagging in order to understand
the basic dynamics behind tagging, including how a power law distribution
of tags could arise. We empirically examine the tagging
history of sites in order to determine how this distribution arises
over time and to determine the patterns prior to a stable distribution.
Lastly, by focusing on the high-frequency tags of a site where
the distribution of tags is a stabilized power law, we show how tag
co-occurrence networks for a sample domain of tags can be used
to analyze the meaning of particular tags given their relationship to
other tags.Thu May 17 01:53:43 CEST 2007Journal of Memory and Language March55534--552High-dimensional semantic space accounts of priming2006priming memory semantic tagora cognitive space A broad range of priming data has been used to explore the structure of semantic memory and to test between models of word representation. In this paper, we examine the computational mechanisms required to learn distributed
semantic representations for words directly from unsupervised experience with language. To best account for the variety
of priming data, we introduce a holographic model of the lexicon that learns word meaning and order information from
experience with a large text corpus. Both context and order information are learned into the same composite representation by simple summation and convolution mechanisms (cf. Murdock, B.B. (1982). A theory for the storage and
retrieval of item and associative information. Psychological Review, 89, 609626). We compare the similarity structure
of representations learned by the holographic model, Latent Semantic Analysis (LSA; Landauer, T.K., & Dumais, S.T.
(1997). A solution to Plato's problem: The latent semantic analysis theory of acquisition, induction and representation
of knowledge. Psychological Review, 104, 211240), and the Hyperspace Analogue to Language (HAL; Lund, K., &
Burgess, C., (1996). Producing high-dimensional semantic spaces from lexical co-occurrence. Behavior Research Methods, Instrumentation, and Computers, 28, 203208) at predicting human data in a variety of semantic, associated, and
mediated priming experiments. We found that both word context and word order information are necessary to account
for trends in the human data. The representations learned from the holographic system incorporate both types of structure, and are shown to account for priming phenomena across several tasks.Thu May 10 19:01:25 CEST 2007MoscowSelected WorksExtension of the law of large numbers to dependent variables1951original polya paper 1907 markov tagora d4.1 urn