192 research outputs found
Social Web Communities
Blogs, Wikis, and Social Bookmark Tools have rapidly emerged onthe Web. The reasons for their immediate success are that people are happy to share information, and that these tools provide an infrastructure for doing so without requiring any specific skills. At the moment, there exists no foundational research for these systems, and they provide only very simple structures for organising knowledge. Individual users create their own structures, but these can currently not be exploited for knowledge sharing. The objective of the seminar was to provide theoretical foundations for upcoming Web 2.0 applications and to investigate further applications that go beyond bookmark- and file-sharing.
The main research question can be summarized as follows: How will current and emerging resource sharing systems support users to leverage more knowledge and power from the information they share on Web 2.0 applications? Research areas like Semantic Web, Machine Learning, Information Retrieval, Information Extraction, Social Network Analysis, Natural Language Processing, Library and Information Sciences, and Hypermedia Systems have been working for a while on these questions. In the workshop, researchers from these areas came together to assess the state of the art and to set up a road map describing the next steps
towards the next generation of social software
Social Web Communities
Blogs, Wikis, and Social Bookmark Tools have rapidly emerged on the Web. The reasons for their immediate success are that people are happy to share information, and that these tools provide an infrastructure for doing so without requiring any specific skills. At the moment, there exists no foundational research for these systems, and they provide only very simple structures for organising knowledge. Individual users create their own structures, but these can currently not be exploited for knowledge sharing. The objective of the seminar was to provide theoretical foundations for upcoming Web 2.0 applications and to investigate further applications that go beyond bookmark- and file-sharing. The main research question can be summarized as follows: How will current and emerging resource sharing systems support users to leverage more knowledge and power from the information they share on Web 2.0 applications? Research areas like Semantic Web, Machine Learning, Information Retrieval, Information Extraction, Social Network Analysis, Natural Language Processing, Library and Information Sciences, and Hypermedia Systems have been working for a while on these questions. In the workshop, researchers from these areas came together to assess the state of the art and to set up a road map describing the next steps towards the next generation of social software
FolkRank: A Ranking Algorithm for Folksonomies
In social bookmark tools users are setting up lightweight conceptual structures called folksonomies. Currently, 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. A long version of this paper has been published at the European Semantic Web Conference 2006
Maximal Ordinal Two-Factorizations
Given a formal context, an ordinal factor is a subset of its incidence
relation that forms a chain in the concept lattice, i.e., a part of the dataset
that corresponds to a linear order. To visualize the data in a formal context,
Ganter and Glodeanu proposed a biplot based on two ordinal factors. For the
biplot to be useful, it is important that these factors comprise as much data
points as possible, i.e., that they cover a large part of the incidence
relation. In this work, we investigate such ordinal two-factorizations. First,
we investigate for formal contexts that omit ordinal two-factorizations the
disjointness of the two factors. Then, we show that deciding on the existence
of two-factorizations of a given size is an NP-complete problem which makes
computing maximal factorizations computationally expensive. Finally, we provide
the algorithm Ord2Factor that allows us to compute large ordinal
two-factorizations.Comment: 15 pages, 6 figures, 2 algorithms, 28th International Conference on
Conceptual Structure
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