Data Mining.
In:
P. M. McCarthy and C. Boonthum, editors,
Applied Natural Language Processing and Content Analysis: Advances in Identification, Investigation and Resolution..
IGI Global, 2011.
Martin Atzmueller.
[BibTeX]
Proceedings of the LWA 2010 - Lernen, Wissen, Adaptivität.
2010.
[BibTeX]
Ready for the MACE? The Mining and Analysis Continuum of Explaining Uncovered.
Deutsches Forschungszentrum für Künstliche Intelligenz, 2010. Number RR-10-02.
Martin Atzmueller and Thomas Roth-Berghofer.
[BibTeX]
The Mining and Analysis Continuum of Explaining Uncovered.
In:
Proc. 30th SGAI International Conference on Artificial Intelligence (AI-2010).
2010.
Martin Atzmueller and Thomas Roth-Berghofer.
[BibTeX]
Towards Explanation-Aware Social Software: Applying the Mining and Analysis Continuum of Explaining.
In:
Proc. Workshop on Explanation-aware Computing ExaCt 2010 @ ECAI 2010.
2010.
Martin Atzmueller and Thomas Roth-Berghofer.
[BibTeX]
Validation of Mixed-Structured Data Using Pattern Mining and Information Extraction.
In:
Proc. 55th IWK, International Workshop on Design, Evaluation and Refinement of Intelligent Systems (DERIS).
University of Ilmenau, 2010.
Martin Atzmueller and Stephanie Beer.
[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]
Decision-Maker-Aware Design of Descriptive Data Mining.
In:
Proc. 55th IWK, International Workshop on Design, Evaluation and Refinement of Intelligent Systems (DERIS).
2010.
Benedikt Kaempgen, Florian Lemmerich and Martin Atzmueller.
[BibTeX]
Fast Discovery of Relevant Subgroup Patterns.
In:
Proc. 23rd FLAIRS Conference.
2010.
Florian Lemmerich and Martin Atzmueller.
[BibTeX]
EWMA Control Charts for Monitoring Binary Processes with Applications to Medical Diagnosis Data.
Quality and Reliability Engineering, 2010.
Christian Weiss and Martin Atzmueller.
[BibTeX]
Mining the World Wide Web - Methods, Ap-
plications, 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]
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]
Efficient Mining of Association Rules Based on Formal Concept Analysis.
2005.
Lotfi Lakhal and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Association rules are a popular knowledge discovery technique for
warehouse basket analysis. They indicate which items of the
warehouse are frequently bought together. The problem of association
rule mining has first been stated in 1993. Five years later, several
research groups discovered that this problem has a strong connection
to Formal Concept Analysis (FCA). In this survey, we will first
introduce some basic ideas of this connection along a specific
algorithm, and show how FCA helps in reducing the number
of resulting rules without loss of information, before giving a
general overview over the history and state of the art of applying
FCA for association rule mining.
Generating a Condensed Representation for Association Rules.
Journal Intelligent Information Systems (JIIS), 24(1):29-60, 2005.
Nicolas Pasquier, Rafik Taouil, Yves Bastide, Gerd Stumme and Lotfi Lakhal.
[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]