Conference articles
Attribute Exploration on the Web.
In: P. Cellier, F. Distel and B. Ganter, editors,
Contributions to the 11th International Conference on Formal Concept Analysis, pages 19-34.
2013.
Robert Jäschke and Sebastian Rudolph.
[doi]
[abstract]
[BibTeX]
We propose an approach for supporting attribute exploration by web information retrieval, in particular by posing appropriate queries to search engines, crowd sourcing systems, and the linked open data cloud. We discuss underlying general assumptions for this to work and the degree to which these can be taken for granted.
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.
FCA-based Browsing and Searching of a Collection of Images.
In:
Proc. of the 14 th Int. Conference on Conceptual Structures.
Springer-Verlag, 2006.
J. Ducrou, B. Vormbrock and P. W. Eklund.
[BibTeX]
FCA-based Browsing and Searching of a Collection of Images.
In: J. Ducrou, B. Vormbrock and P. W. Eklund, editors,
Proc. of the 14 th Int. Conference on Conceptual Structures.
Springer-Verlag, 2006.
[BibTeX]
Information Retrieval in Folksonomies: Search and Ranking.
In:
Proceedings of the 3rd European Semantic Web Conference, series Lecture Notes in Computer Science, pages 411-426.
Springer, 2006.
Andreas Hotho, Robert Jäschke, Christoph Schmitz and Gerd Stumme.
[BibTeX]
Information Retrieval in Folksonomies: Search and Ranking.
In: Y. Sure and J. Domingue, editors,
The Semantic Web: Research and Applications, volume 4011, series LNAI, pages 411-426.
Springer, Heidelberg, 2006.
Andreas Hotho, Robert Jäschke, Christoph Schmitz and Gerd Stumme.
[BibTeX]
Information Retrieval in Folksonomies: Search and Ranking.
In: Y. Sure and J. Domingue, editors,
The Semantic Web: Research and Applications, volume 4011, series LNAI, pages 411-426.
Springer, Heidelberg, 2006.
Andreas Hotho, Robert J�schke, Christoph Schmitz and Gerd Stumme.
[BibTeX]
Journal articles
Document Retrieval for Email Search and Discovery using Formal Concept Analysis.
Journal of Applied Artificial Intelligence (AAI), 17(3):257-280, 2003.
Richard J. Cole, Peter W. Eklund and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
This paper discusses an document discovery tool based on
conceptual clustering by formal concept analysis. The program
allows users to navigate email using a visual lattice metaphor
rather than a tree. It implements a virtual file structure over
email where files and entire directories can appear in multiple
positions. The content and shape of the lattice formed by the
conceptual ontology can assist in email discovery. The system
described provides more flexibility in retrieving stored emails
than what is normally available in email clients. The paper
discusses how conceptual ontologies can leverage traditional
document retrieval systems and aid knowledge discovery in document
collections.
Miscellaneous
Information Retrieval: Suchmodelle und Data-Mining-Verfahren für Textsammlungen und das Web.
2003.
Reginald Ferber.
[doi]
[BibTeX]
Conference articles
Wordnet improves text document clustering.
In:
Proc. SIGIR Semantic Web Workshop.
Toronto, 2003.
A Hotho, S. Staab and G. Stumme.
[doi]
[BibTeX]
Item-based collaborative filtering recommendation algorithms..
In:
WWW, pages 285-295.
2001.
Badrul M. Sarwar, George Karypis, Joseph A. Konstan and John Riedl.
[doi]
[BibTeX]
Miscellaneous
Modern Information Retrieval.
1999.
Ricardo A. Baeza-Yates and Berthier A. Ribeiro-Neto.
[doi]
[BibTeX]
Conference articles
Dual Retrieval in Conceptual Information Systems.
In: A. Buchmann, editor,
Datenbanksysteme in Büro, Technik und Wissenschaft. Proc. BTW'99, pages 328-342.
Heidelberg, 1999.
Gerd Stumme.
[doi]
[BibTeX]
Miscellaneous
Readings in Information Retrieval.
1997.
[BibTeX]
Journal articles
A lattice conceptual clustering system and its application to browsing retrieval.
Machine Learning, 24(2):95-122, 1996.
Claudio Carpineto and Giovanni Romano.
[doi]
[abstract]
[BibTeX]
The theory of concept (or Galois) lattices provides a simple and formal approach to conceptual clustering. In this paper we present GALOIS, a system that automates and applies this theory. The algorithm utilized by GALOIS to build a concept lattice is incremental and efficient, each update being done in time at most quadratic in the number of objects in the lattice. Also, the algorithm may incorporate background information into the lattice, and through clustering, extend the scope of the theory. The application we present is concerned with information retrieval via browsing, for which we argue that concept lattices may represent major support structures. We describe a prototype user interface for browsing through the concept lattice of a document-term relation, possibly enriched with a thesaurus of terms. An experimental evaluation of the system performed on a medium-sized bibliographic database shows good retrieval performance and a significant improvement after the introduction of background knowledge.
ER -
Conference articles
NewsWeeder: learning to filter netnews.
In:
Proceedings of the 12th International Conference on Machine Learning, pages 331-339.
Morgan Kaufmann publishers Inc.: San Mateo, CA, USA, 1995.
Ken Lang.
[doi]
[BibTeX]
Query Expansion Using Lexical-Semantic Relations..
In:
SIGIR, pages 61-69.
1994.
Ellen M. Voorhees.
[doi]
[BibTeX]
Miscellaneous
Information retrieval.
1979.
C. J. van Rijsbergen.
[doi]
[BibTeX]