Data Mining
Atzmueller, M.
McCarthy, P. M. & Boonthum, C., ed., 'Applied Natural Language Processing and Content Analysis: Advances in Identification, Investigation and Resolution.', IGI Global (2011)
Proceedings of the LWA 2010 - Lernen, Wissen, Adaptivität
2010, Atzmueller, M.; Benz, D.; Hotho, A. & Stumme, G., ed., Technical report (KIS), 2010-10, Department of Electrical Engineering/Computer Science, Kassel University
Ready for the MACE? The Mining and Analysis Continuum of Explaining Uncovered
Atzmueller, M. & Roth-Berghofer, T.
2010, Technical report, Deutsches Forschungszentrum für Künstliche Intelligenz
The Mining and Analysis Continuum of Explaining Uncovered
Atzmueller, M. & Roth-Berghofer, T.
, 'Proc. 30th SGAI International Conference on Artificial Intelligence (AI-2010)' (2010)
Towards Explanation-Aware Social Software: Applying the Mining and Analysis Continuum of Explaining
Atzmueller, M. & Roth-Berghofer, T.
, 'Proc. Workshop on Explanation-aware Computing ExaCt 2010 @ ECAI 2010' (2010)
Validation of Mixed-Structured Data Using Pattern Mining and Information Extraction
Atzmueller, M. & Beer, S.
, 'Proc. 55th IWK, International Workshop on Design, Evaluation and Refinement of Intelligent Systems (DERIS)', University of Ilmenau (2010)
Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0
Berendt, B.; Hotho, A. & Stumme, G.
Web Semantics: Science, Services and Agents on the World Wide Web, 8(2-3) 95 - 96 (2010) [pdf]
Decision-Maker-Aware Design of Descriptive Data Mining
Kaempgen, B.; Lemmerich, F. & Atzmueller, M.
, 'Proc. 55th IWK, International Workshop on Design, Evaluation and Refinement of Intelligent Systems (DERIS)' (2010)
Fast Discovery of Relevant Subgroup Patterns
Lemmerich, F. & Atzmueller, M.
, 'Proc. 23rd FLAIRS Conference' (2010)
EWMA Control Charts for Monitoring Binary Processes with Applications to Medical Diagnosis Data
Weiss, C. & Atzmueller, M.
Quality and Reliability Engineering (2010)
Mining the World Wide Web -- Methods, Ap-
ications, and Perspectives
Hotho, A. & Stumme, G.
K√ľnstliche Intelligenz 5-8 (2007) [pdf]
Themenheft Web Mining, K√ľnstliche Intelligenz
2007, Hotho, A. & Stumme, G., ed. [pdf]
Semantics, Web and Mining
2006, Ackermann, M.; Berendt, B.; Grobelnik, M.; Hotho, A.; Mladenic, D.; Semeraro, G.; Spiliopoulou, M.; Stumme, G.; Svatek, V. & van Someren, M., ed., Springer, Heidelberg [pdf]
Proc. of the European Web Mining Forum 2005
2005, Berendt, B.; Hotho, A.; Mladenic, D.; Semerano, G.; Spiliopoulou, M.; Stumme, G. & van Someren, M., ed. [pdf]
Semantic Web Mining and the Representation, Analysis, and Evolution of Web Space
Berendt, B.; Hotho, A. & Stumme, G.
Svatek, V. & Snasel, V., ed., 'Proc. of the 1st Intl. Workshop on Representation and Analysis of Web Space', Technical University of Ostrava, 1-16 (2005) [pdf]
Efficient Mining of Association Rules Based on Formal Concept Analysis
Lakhal, L. & Stumme, G.
'Formal Concept Analysis: Foundations and Applications', 3626(), Springer, Heidelberg, 180-195 (2005) [pdf]
Association rules are a popular knowledge discovery technique for
rehouse basket analysis. They indicate which items of the
rehouse are frequently bought together. The problem of association
le mining has first been stated in 1993. Five years later, several
search groups discovered that this problem has a strong connection
Formal Concept Analysis (FCA). In this survey, we will first
troduce some basic ideas of this connection along a specific
gorithm, and show how FCA helps in reducing the number
resulting rules without loss of information, before giving a
neral overview over the history and state of the art of applying
A for association rule mining.
Generating a Condensed Representation for Association Rules
Pasquier, N.; Taouil, R.; Bastide, Y.; Stumme, G. & Lakhal, L.
Journal Intelligent Information Systems (JIIS), 24(1) 29-60 (2005) [pdf]
A Roadmap for Web Mining: From Web to Semantic Web.
Berendt, B.; Hotho, A.; Mladenic, D.; van Someren, M.; Spiliopoulou, M. & Stumme, G.
Berendt, B.; Hotho, A.; Mladenic, D.; van Someren, M.; Spiliopoulou, M. & Stumme, G., ed., 'Web Mining: From Web to Semantic Web', 3209(), Springer, Heidelberg, 1-22 (2004) [pdf]
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
Berendt, B.; Hotho, A. & Stumme, G.
Kargupta, H.; Joshi, A.; Sivakumar, K. & Yesha, Y., ed., 'Data Mining Next Generation Challenges and Future Directions', AAAI Press, Boston, 461-481 (2004) [pdf]
Semantic Web Mining aims at combining the two fast-developing
search areas Semantic Web and Web Mining.
b Mining aims at discovering insights about the meaning of Web
sources and their usage. Given the primarily syntactical nature
data Web mining operates on, the discovery of meaning is
possible based on these data only. Therefore, formalizations of
e semantics of Web resources and navigation behavior are
creasingly being used. This fits exactly with the aims of the
mantic Web: the Semantic Web enriches the WWW by
chine-processable information which supports the user in his
sks. In this paper, we discuss the interplay of the Semantic Web
th 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
2004, Berendt, B.; Hotho, A.; Mladenic, D.; van Someren, M.; Spiliopoulou, M. & Stumme, G., ed., 3209(), Springer, Heidelberg [pdf]