User-Relatedness and Community Structure in Social Interaction Networks.
CoRR/abs, 1309.3888, 2013.
Folke Mitzlaff, Martin Atzmueller, Dominik Benz, Andreas Hotho and Gerd Stumme.
[BibTeX]
On the Semantics of User Interaction in Social Media (Extended Abstract, Resubmission).
In:
Proc. LWA 2013 (KDML Special Track).
University of Bamberg, Bamberg, Germany, 2011.
Folke Mitzlaff, Martin Atzmueller, Gerd Stumme and Andreas Hotho.
[BibTeX]
Bridging the Gap-Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0.
Web Semantics: Science, Services and Agents on the World Wide Web, 8(2-3):95 - 96, 2010.
Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0; The Future of Knowledge Dissemination: The Elsevier Grand Challenge for the Life Sciences
Bettina Berendt, Andreas Hotho and Gerd Stumme.
[doi]
[BibTeX]
Mining the World Wide Web - Methods, Ap-
plications, and Perspectives.
Künstliche Intelligenz(3):5-8, 2007.
Andreas Hotho and Gerd Stumme.
[doi]
[BibTeX]
Mining the World Wide Web -- Methods, Applications, and Perspectives.
Künstliche Intelligenz(3):5-8, 2007.
Andreas Hotho and Gerd Stumme.
[doi]
[BibTeX]
Themenheft Web Mining, Künstliche Intelligenz.
number 3.
2007.
Andreas Hotho and Gerd Stumme.
[doi]
[BibTeX]
Semantic Web Mining - State of the Art and Future Directions.
Journal of Web Semantics, 4(2):124-143, 2006.
Gerd Stumme, Andreas Hotho and Bettina Berendt.
[doi]
[abstract]
[BibTeX]
SemanticWeb Mining aims at combining the two fast-developing research areas SemanticWeb andWeb Mining. This survey analyzes the convergence of trends from both areas: an increasing number of researchers is working on improving the results ofWeb Mining by exploiting semantic structures in theWeb, and they make use ofWeb Mining techniques for building the Semantic Web. Last but not least, these techniques can be used for mining the Semantic Web itself. The Semantic Web is the second-generation WWW, enriched by machine-processable information which supports the user in his tasks. Given the enormous size even of today’s Web, it is impossible to manually enrich all of these resources. Therefore, automated schemes for learning the relevant information are increasingly being used. Web Mining aims at discovering insights about the meaning of Web resources and their usage. Given the primarily syntactical nature of the data being mined, the discovery of meaning is impossible based on these data only. Therefore, formalizations of the semantics of Web sites and navigation behavior are becoming more and more common. Furthermore, mining the Semantic Web itself is another upcoming application. We argue that the two areas Web Mining and Semantic Web need each other to fulfill their goals, but that the full potential of this convergence is not yet realized. This paper gives an overview of where the two areas meet today, and sketches ways of how a closer integration could be profitable.
Proc. of the European Web Mining Forum 2005.
2005.
Bettina Berendt, Andreas Hotho, Dunja Mladenic, Giovanni Semerano, Myra Spiliopoulou, Gerd Stumme and Maarten van Someren.
[doi]
[BibTeX]
Semantic Web Mining and the Representation, Analysis, and Evolution of Web Space.
In: V. Svatek and V. Snasel, editors,
Proc. of the 1st Intl. Workshop on Representation and Analysis of Web Space, pages 1-16.
Technical University of Ostrava, 2005.
Bettina Berendt, Andreas Hotho and Gerd Stumme.
[doi]
[BibTeX]
A Roadmap for Web Mining: From Web to Semantic Web..
In: B. Berendt, A. Hotho, D. Mladenic, M. van Someren, M. Spiliopoulou and G. Stumme, editors,
Web Mining: From Web to Semantic Web, volume 3209, pages 1-22.
Springer, Heidelberg, 2004.
Bettina Berendt, Andreas Hotho, Dunja Mladenic, Maarten van Someren, Myra Spiliopoulou and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
The purpose of Web mining is to develop methods and systems for discovering models of objects and processes on the World Wide Web and for web-based systems that show adaptive performance. Web Mining integrates three parent areas: Data Mining (we use this term here also for the closely related areas of Machine Learning and Knowledge Discovery), Internet technology and World Wide Web, and for the more recent Semantic Web. The World Wide Web has made an enormous amount of information electronically accessible. The use of email, news and markup languages like HTML allow users to publish and read documents at a world-wide scale and to communicate via chat connections, including information in the form of images and voice records. The HTTP protocol that enables access to documents over the network via Web browsers created an immense improvement in communication and access to information. For some years these possibilities were used mostly in the scientific world but recent years have seen an immense growth in popularity, supported by the wide availability of computers and broadband communication. The use of the internet for other tasks than finding information and direct communication is increasing, as can be seen from the interest in ldquoe-activitiesrdquo such as e-commerce, e-learning, e-government, e-science.
Usage Mining for and on the Semantic Web.
In:
H. Kargupta, A. Joshi, K. Sivakumar and Y. Yesha, editors,
Data Mining Next Generation Challenges and Future Directions, pages 461-481.
AAAI Press, Boston, 2004.
Bettina Berendt, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Semantic Web Mining aims at combining the two fast-developing
research areas Semantic Web and Web Mining.
Web Mining aims at discovering insights about the meaning of Web
resources and their usage. Given the primarily syntactical nature
of data Web mining operates on, the discovery of meaning is
impossible based on these data only. Therefore, formalizations of
the semantics of Web resources and navigation behavior are
increasingly being used. This fits exactly with the aims of the
Semantic Web: the Semantic Web enriches the WWW by
machine-processable information which supports the user in his
tasks. In this paper, we discuss the interplay of the Semantic Web
with Web Mining, with a specific focus on usage mining.
Web Mining: From Web to Semantic Web, First European Web
Mining Forum, EMWF 2003, Cavtat-Dubrovnik, Croatia, September
22, 2003, Revised Selected and Invited Papers.
LNAI. volume 3209.
Springer, Heidelberg, 2004.
http://km.aifb.uni-karlsruhe.de/ws/ewmf03/.
Bettina Berendt, Andreas Hotho, Dunja Mladenic, Maarten van Someren, Myra Spiliopoulou and Gerd Stumme.
[doi]
[BibTeX]
Proceedings of the 1st European Web Mining Forum (EWMF 2003).
Cavtat/Dubrovnik, Croatia, 2003.
B. Berendt, A. Hotho, D. Mladenić, M. van Someren, M. Spiliopoulou and G. Stumme.
[doi]
[BibTeX]
Building and Using the Semantic Web.
In:
New Trends in Knowledge Processing - Data Mining, Semantic Web and Computational, pages 31-34.
Osaka, Japan, 2003.
Rudi Studer, Gerd Stumme, Siegfried Handschuh, Andreas Hotho and B. Motik.
[doi]
[BibTeX]
Semantic Web Mining. Proc. of the Semantic Web Mining Workshop of the 13th Europ. Conf. on
Machine Learning (ECML'02) / 6th Europ. Conf. on Principles and
Practice of Knowledge Discovery in Databases (PKDD'02).
Helsinki, Finland, 2002.
B. Berendt, A. Hotho and G. Stumme.
[doi]
[BibTeX]
Towards Semantic Web Mining.
In: I. Horrocks and J. Hendler, editors,
The Semantic Web - ISWC 2002, series LNCS, pages 264-278.
Springer, Heidelberg, 2002.
B. Berendt, A. Hotho and G. Stumme.
[doi]
[BibTeX]
Usage Mining for and on the Semantic Web.
In:
Proc. NSF Workshop on Next Generation Data Mining, pages 77-86.
Baltimore, 2002.
G. Stumme, B. Berendt and A. Hotho.
[doi]
[BibTeX]
Semantic Web Mining. Workshop Proceedings..
Freiburg, 2001.
G. Stumme, A. Hotho and B. Berendt.
[doi]
[BibTeX]