@inproceedings{Abbasi2008ITP, title = {Introducing Triple Play for Improved Resource Retrieval in Collaborative Tagging Systems}, author = {Rabeeh Abbasi and Steffen Staab}, booktitle = {In: Proc. of ECIR'08 Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR 2008)}, month = 3, year = 2008, url = {http://www.uni-koblenz.de/~abbasi/publications/Abbasi2008ITP.pdf}, abstract = {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.}, biburl = {http://www.bibsonomy.org/bibtex/2fc105a9e1be1ac195e7d4d05fe3c7a32/rabeeh}, keywords = {tripleplay system ecir collaborative esair information search tagorapub folksonomy tagging retrieval 2008 folksonomies} } @inproceedings{1102357, title = {Multi-way distributional clustering via pairwise interactions}, address = {New York, NY, USA}, author = {Ron Bekkerman and Ran El-Yaniv and Andrew McCallum}, booktitle = {ICML '05: Proceedings of the 22nd international conference on Machine learning}, pages = {41--48}, publisher = {ACM Press}, year = 2005, location = {Bonn, Germany}, isbn = {1-59593-180-5}, doi = {http://doi.acm.org/10.1145/1102351.1102357}, description = {Multi-way distributional clustering via pairwise interactions}, biburl = {http://www.bibsonomy.org/bibtex/2a5ac489feb7407a07570f6733665a6dd/rabeeh}, keywords = {multiway clustering mdc} } @inproceedings{Abbasi:2007, title = {Organizing Resources on Tagging Systems using T-ORG}, author = {Rabeeh Abbasi and Steffen Staab and Philipp Cimiano}, booktitle = {In proceedings of Workshop on Bridging the Gap between Semantic Web and Web 2.0 at ESWC 2007}, pages = {97-110}, year = 2007, url = {http://www.uni-koblenz.de/~abbasi/publications/Abbasi2007ORO.pdf}, abstract = {Tagging systems (or folksonomies) like Flickr or Delicious are expanding tremendously. More and more resources are being added to them. As the resources present on these system increase in amount, it becomes difficult to explore these resources. For this purpose, we present a system T-ORG, which provides a mechanism to organize these resources by classifying the tags (or keywords) attached to them into predefined categories. Supervised classification in this case seems infeasible; therefore we also propose a new classification algorithm T-KNOW that does not require training data. For our experiments, we have downloaded images and their tags from groups present on Flickr website and then classified these tags into different categories. We have used Cohen’s Kappa and F-measure to evaluate the classification results of T-KNOW. Results are encouraging and show that T-ORG can be used to explore resources in an effective manner.}, biburl = {http://www.bibsonomy.org/bibtex/29c7fe8f5088a6d73dc8326ddcd4d803f/rabeeh}, keywords = {cohen tags folksonomies torg tagorapub tagging 2007 system eswc eswc2007 kappa classification tknow} } @inbook{baldi03modelling, title = {Modeling the Internet and the Web: Probabilistic Methods and Algorithms}, author = {Pierre Baldi and Paolo Frasconi and Padhraic Smyth}, booktitle = {Modeling the Internet and the Web: Probabilistic Methods and Algorithms}, month = {April}, publisher = {Wiley}, year = 2003, url = {http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470849061.html}, id = {822915}, priority = {2}, abstract = {Modeling the Internet and the Web covers the most important aspects of modeling the Web using a modern mathematical and probabilistic treatment. It focuses on the information and application layers, as well as some of the emerging properties of the Internet.  Provides a comprehensive introduction to the modeling of the Internet and the Web at the information level.  Takes a modern approach based on mathematical, probabilistic, and graphical modeling.  Provides an integrated presentation of theory, examples, exercises and applications.  Covers key topics such as text analysis, link analysis, crawling techniques, human behaviour, and commerce on the Web. Interdisciplinary in nature, Modeling the Internet and the Web will be of interest to students and researchers from a variety of disciplines including computer science, machine learning, engineering, statistics, economics, business, and the social sciences.}, biburl = {http://www.bibsonomy.org/bibtex/23e4e2899e7d6988218d02a264bcfe24a/rabeeh}, keywords = {modeling probabilistic web} } @inproceedings{hotho2006information, title = {Information Retrieval in Folksonomies: Search and Ranking}, address = {Budva, Montenegro}, author = {Andreas Hotho and Robert Jäschke and Christoph Schmitz and Gerd Stumme}, booktitle = {Proceedings of the 3rd European Semantic Web Conference }, month = {June}, pages = {411-426}, publisher = {Springer}, series = {LNCS}, year = 2006, url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2006/seach2006hotho_eswc.pdf}, isbn = {3-540-34544-2}, vgwort = {29}, biburl = {http://www.bibsonomy.org/bibtex/2566686f518e43c993dc1854dc2b2b5e4/rabeeh}, keywords = {folksonomy information} } @inproceedings{Hebert2007, title = {{A Unified View of Objective Interestingness Measures}}, address = {{Leipzig, Germany}}, author = {C. Hébert and B. Crémilleux}, booktitle = {{5th International Conference on Machine Learning and Data Mining (MLDM'07)}}, month = {{07}}, pages = {--}, publisher = {Springer-Verlag}, year = {{2007}}, description = {Bingo project}, biburl = {http://www.bibsonomy.org/bibtex/2441a7f7aaddb5a13abb09106d5b44af7/rabeeh}, keywords = {imported} } @inproceedings{CM:ontoImage-06, title = {Automatically Populating an Image Ontology and Semantic Color Filtering}, address = {Genoa, Italy}, annote = {category=inproceedings state=published project=tii group=tii }, author = {C. Millet and G. Grefenstette and I. Bloch and P.-A. Mo\"ellic and P. H\`ede}, booktitle = {Ontoimage 2006, Language Resources for Content-Based Image Retrieval}, month = {may}, pages = {34-39}, year = 2006, biburl = {http://www.bibsonomy.org/bibtex/22b92231ebc9eb041cd0b1122087f8ec6/rabeeh}, keywords = {context clustering ontology} } @inproceedings{conf/rskt/JinQP06, title = {Reduction-Based Approaches Towards Constructing Galois (Concept) Lattices.}, author = {Jingyu Jin and Keyun Qin and Zheng Pei}, booktitle = {RSKT}, crossref = {conf/rskt/2006}, editor = {Guoyin Wang and James F. Peters and Andrzej Skowron and Yiyu Yao}, pages = {107-113}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, volume = 4062, year = 2006, url = {http://dblp.uni-trier.de/db/conf/rskt/rskt2006.html#JinQP06}, ee = {http://dx.doi.org/10.1007/11795131_16}, isbn = {3-540-36297-5}, date = {2006-10-31}, description = {dblp}, biburl = {http://www.bibsonomy.org/bibtex/2aab1fda3152860e72e1238242cccebab/rabeeh}, keywords = {fca reduction attribute} } @article{desmet:efn, title = {{Extraction of Folksonomies from Noisy Texts}}, author = {W. De Smet and M.F. Moens}, year = 2007, biburl = {http://www.bibsonomy.org/bibtex/28d28a9b77ef4284749c2d2a458a1f2c2/rabeeh}, keywords = {co-clustering folksonomy} } @article{passant:uos, title = {{Using Ontologies to Strengthen Folksonomies and Enrich Information Retrieval in Weblogs}}, author = {A. Passant}, year = 2007, biburl = {http://www.bibsonomy.org/bibtex/29676149ef903cc65871a07b5a552f9b8/rabeeh}, keywords = {folksonomy semantic} } @article{cantador:bes, title = {{Building Emergent Social Networks and Group Profiles by Semantic User Preference Clustering}}, author = {I. Cantador and P. Castells}, year = 2006, biburl = {http://www.bibsonomy.org/bibtex/2eeb2ea8c8f39f6057465b38eea991582/rabeeh}, keywords = {network semantic social clustering} } @article{frivolt:cgc, title = {{Comparison of Graph Clustering Approaches}}, author = {G. Frivolt and O. Pok}, year = 2006, biburl = {http://www.bibsonomy.org/bibtex/2e7109528877b4ee8fb17acb837740b74/rabeeh}, keywords = {graph clustering} } @inproceedings{conf/ekaw/CantadorC06, title = {Multilayered Semantic Social Network Modeling by Ontology-Based User Profiles Clustering: Application to Collaborative Filtering.}, author = {Iván Cantador and Pablo Castells}, booktitle = {EKAW}, crossref = {conf/ekaw/2006}, editor = {Steffen Staab and Vojtech Svátek}, pages = {334-349}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, volume = 4248, year = 2006, url = {http://dblp.uni-trier.de/db/conf/ekaw/ekaw2006.html#CantadorC06}, ee = {http://dx.doi.org/10.1007/11891451_30}, isbn = {3-540-46363-1}, date = {2006-10-24}, description = {dblp}, biburl = {http://www.bibsonomy.org/bibtex/21c690a00afc357bd9ced80932507f13b/rabeeh}, keywords = {clustering social network} } @article{cattuto2007network, title = {Network Properties of Folksonomies}, author = {Ciro Cattuto and Christoph Schmitz and Andre Baldassarri and Vito D. P. Servedio and Vittorio Loreto and Andreas Hotho and Miranda Grahl and Gerd Stumme}, journal = {AI Communications Special Issue on "Network Analysis in Natural Sciences and Engineering" (to appear)}, year = 2007, biburl = {http://www.bibsonomy.org/bibtex/2d7a5f75c14ced45ca76bad1e9ef162eb/rabeeh}, keywords = {semantics emergent tagging folksonomy clustering printed} } @article{rui07, title = {Towards Effective Browsing of Large Scale Social Annotations}, author = {Rui Li and Shenghua Bao and Ben Fei and Zhong Su and Yong Yu}, year = 2007, biburl = {http://www.bibsonomy.org/bibtex/29ba1d7cb870265a32f1b8817a8dcd504/rabeeh}, keywords = {printed clustering folksonomy} } @article{priss2005fca, title = {{Formal concept analysis in information science}}, author = {U. Priss}, journal = {Annual Review of Information Science and Technology}, volume = 40, year = 2005, biburl = {http://www.bibsonomy.org/bibtex/2ee02c483061595e5990367b8e1e030da/rabeeh}, keywords = {fca} } @inproceedings{hotho2006emergent, title = {Emergent Semantics in BibSonomy}, address = {Bonn}, author = {Andreas Hotho and Robert Jäschke and Christoph Schmitz and Gerd Stumme}, booktitle = {Informatik 2006 - Informatik für Menschen. Band 2}, editor = {Christian Hochberger and Rüdiger Liskowsky}, month = {oct}, note = {Proc. Workshop on Applications of Semantic Technologies, Informatik 2006}, publisher = {Gesellschaft für Informatik}, series = {Lecture Notes in Informatics}, volume = {P-94}, year = 2006, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006emergent.pdf}, 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. In this paper we specify a formal model for folksonomies, briefly describe our own system BibSonomy, which allows for sharing both bookmarks and publication references, and discuss first steps towards emergent semantics.}, biburl = {http://www.bibsonomy.org/bibtex/205043cc20f1e0f5a612135c970e4f1ac/rabeeh}, keywords = {semantics emergent folksonomy} } @inproceedings{hotho2006trend, title = {Trend Detection in Folksonomies}, address = {Heidelberg}, author = {Andreas Hotho and Robert Jäschke and Christoph Schmitz and Gerd Stumme}, booktitle = {Proc. First International Conference on Semantics And Digital Media Technology (SAMT) }, editor = {Yannis S. Avrithis and Yiannis Kompatsiaris and Steffen Staab and Noel E. O'Connor}, month = {dec}, pages = {56-70}, publisher = {Springer}, series = {LNCS}, volume = 4306, year = 2006, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006trend.pdf}, ee = {http://dx.doi.org/10.1007/11930334_5}, isbn = {3-540-49335-2}, vgwort = {27}, date = {2006-12-13}, abstract = {As the number of resources on the web exceeds by far the number of documents one can track, it becomes increasingly difficult to remain up to date on ones own areas of interest. The problem becomes more severe with the increasing fraction of multimedia data, from which it is difficult to extract some conceptual description of their contents. One way to overcome this problem are social bookmark tools, which are rapidly emerging on the web. In such systems, users are setting up lightweight conceptual structures called folksonomies, and overcome thus the knowledge acquisition bottleneck. As more and more people participate in the effort, the use of a common vocabulary becomes more and more stable. We present an approach for discovering topic-specific trends within folksonomies. It is based on a differential adaptation of the PageRank algorithm to the triadic hypergraph structure of a folksonomy. The approach allows for any kind of data, as it does not rely on the internal structure of the documents. In particular, this allows to consider different data types in the same analysis step. We run experiments on a large-scale real-world snapshot of a social bookmarking system.}, biburl = {http://www.bibsonomy.org/bibtex/242cda5911e901eadd0ac6a106a6aa1dc/rabeeh}, keywords = {trend printed folksonomy} } @inproceedings{ieKey, title = {Concept Lattices in Rough Set Theory}, author = {Y. Y. Yao}, booktitle = {Proceedings of 2004 Annual Meeting of the North American Fuzzy Information Processing Society(NAFIPS 2004),IEEE Catalog Number: 04 TH 8736}, pages = {796-801}, year = 2004, date = {2004}, biburl = {http://www.bibsonomy.org/bibtex/29a707f8479af3266f6f4add86a9fb161/rabeeh}, keywords = {printed fca rought concept set} } @inbook{ma2006, title = {Clustering Techniques}, author = {Tao Li Sheng Ma}, year = 2006, biburl = {http://www.bibsonomy.org/bibtex/276faba3296f01fdbcb3015bbb9da5b55/rabeeh}, keywords = {printed clustering} }