Publikationen

150 Ergebnisse

2014

Zimmer (née Ivanescu) A., Driessen P., Kranen P., Seidl T.:
Inverse Predictions on Continuous Models in Scientific Databases
Proceedings of the 26th International Conference on Scientific and Statistical Database Management (2014)
[SSDBM 2014]
Boden B., Ester M., Seidl T.:
Density-Based Subspace Clustering in Heterogeneous Networks
Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2014), Nancy, France (2014) (to appear)
Boden B.:
Combined Clustering of Graph and Attribute Data
Dissertation, Fakultät für Mathematik, Informatik und Naturwissenschaften, RWTH Aachen University (2014) Tag der mündlichen Prüfung: 16.04.2014
[Apprimus-Verlag] [RWTH-Bibliothek]
Assam R., Hassani M., Brysch M., Seidl T.:
(k, d)-Core Anonymity: Structural Anonymization of Massive Networks
Proc. of the 26th International Conference on Scientific and Statistical Database Management (SSDBM 2014), Aalborg, Denmark. (2014) Article No. 17
[SSDBM 2014]
Fries S., Wels S., Seidl T.:
Projected Clustering for Huge Data Sets in MapReduce
International Conference on Extending Database Technology (EDBT 2014), Athens, Greece S.49-60 (2014)
[EDBT 2014]
Assam R., Seidl T.:
Insights and Knowledge Discovery from Big Geospatial Data using TMC-Pattern
Hassan A. Karimi (Ed.):  Big Data: Techniques and Technologies in Geoinformatics S.233 - 257 (2014)
[CRC Press]
Hassani M., Kranen P., Saini R., Seidl T.:
Subspace Anytime Stream Clustering
Proc. of the 26th International Conference on Scientific and Statistical Database Management (SSDBM 2014), Aalborg, Denmark. (2014) Article No. 37
[SSDBM 2014]
Fries S., Boden B., Stepien G., Seidl T.:
PHiDJ: Parallel Similarity Self-Join for High-Dimensional Vector Data with MapReduce
Proc. IEEE 30th International Conference on Data Engineering (ICDE 2014), Chicago, IL, USA (2014)
[ICDE 2014]

2013

Kremer H.:
Mining and Similarity Search in Temporal Databases
Dissertation, Fakultät für Mathematik, Informatik und Naturwissenschaften, RWTH Aachen University. (2013) Tag der mündlichen Prüfung: 14.10.2013
[PDF] [RWTH Bibliothek] [Apprimus-Verlag]
Günnemann S., Färber I., Raubach S., Seidl T.:
Spectral Subspace Clustering for Graphs with Feature Vectors
Proc. IEEE International Conference on Data Mining (ICDM), Dallas, TX, USA S.231-240 (2013)
[ICDM 2013]
Assam R., Seidl T.:
BodyGuards: A Clairvoyant Location Predictor using Frequent Neighbors and Markov Model
Proc. IEEE  10th International Conference on Ubiquitous Intelligence and Computing (UIC-2013), Vietri sul Mare, Italy S.25-32 (2013)
[UIC 2013]
Zimmer (née Ivanescu) A., Kurze M., Seidl T.:
Adaptive Model Tree for Streaming Data
Proc. IEEE International Conference on Data Mining (ICDM), Dallas, TX, USA S.1319-1324 (2013)
[ICDM 2013]
Kremer H., Günnemann S., Held A., Seidl T.:
An Evaluation Framework for Temporal Subspace Clustering Approaches
Proc. IEEE International Conference on Data Mining Workshops (ICDMW), Dallas, TX, USA  S.1089-1092 (2013) (Demo)
[ICDM 2013]
Assam R., Seidl T.:
Private Map Matching: Realistic Private Route Cognition on Road Networks
Proc. IEEE  10th International Conference on Ubiquitous Intelligence and Computing (UIC-2013), Vietri sul Mare, Italy S.178-185 (2013)
[UIC 2013]
Helmut Vieritz, Tobias Meisen, Tobias Vaegs, Sabina Jeschke, Hassani M., Beecks C., Seidl T., Matthias Priesters, Irene Mittelberg, Paula Niemietz, Tatiana Serbina, Stella Neumann:
e-cosmos: Cluster-Analysen zeitelastischer, multimodaler Daten in der Linguistik
LingUnite RWTH Aachen Tag der Sprachforschung. (Poster) (2013)
[LingUnite]
Boden B., Haag R., Seidl T.:
Detecting and Exploring Clusters in Attributed Graphs
Proceedings of the 22nd ACM Conference on Information and Knowledge Management (CIKM 2013), San Francisco, CA, USA S.2505-2508 (2013) (Demo)
[CIKM 2013]
Müller E., Günnemann S., Färber I., Seidl T.:
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data
Tutorial at the 30th International Conference on Machine Learning (ICML 2013), Atlanta, USA (2013)
[ICML 2013] [Tutorial Website]
Boden B., Günnemann S., Hoffmann H., Seidl T.:
RMiCS: A Robust Approach for Mining Coherent Subgraphs in Edge-Labeled Multi-Layer Graphs
Proc. of the 25th International Conference on Scientific and Statistical Database Management (SSDBM 2013), Baltimore, Maryland, USA S.23 (2013)
[SSDBM 2013]
Christoph Quix, Johannes Barnickel, Sandra Geisler, Hassani M., Saim Kim, Xiang Li, Andreas Lorenz, Till Quadflieg, Thomas Gries, Matthias Jarke, Steffen Leonhardt, Ulrike Meyer, Seidl T.:
HealthNet: A System for Mobile and Wearable Health Information Management
Proc. of the 3rd International Workshop on Information Management in Mobile Applications (IMMoA 2013) in conjunction with VLDB 2013, Riva del Garda, Trento, Italy. S.36-43 (2013)
[IMMoA 2013] [VLDB 2013]
Kremer H., Günnemann S., Wollwage S., Seidl T.:
Nesting the Earth Mover's Distance for Effective Cluster Tracing
Proc. of the 25th International Conference on Scientific and Statistical Database Management (SSDBM), Baltimore, Maryland, USA S.34:1-34:4 (2013)
[SSDBM 2013]
Assam R., Seidl T.:
A Model for Context-Aware Location Identity Preservation using Differential Privacy
Proceedings of the 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom-13), Melbourne, Australia S.346-353 (2013)
[IEEE TrustCom 2013]
Hassani M., Kim Y., Seungjin Choi, Seidl T.:
Effective Evaluation Measures for Subspace Clustering of Data Streams
The third Quality issues, measures of interestingness and evaluation of data mining models workshop (QIMIE'13), held in conjunction with PAKDD'13 conference (17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Gold Coast, Australia) S.342-353 (2013)
[QIMIE13] [PAKDD13]
Hassani M., Kim Y., Seidl T.:
Subspace MOA: Subspace Stream Clustering Evaluation Using the MOA Framework
The 18th International Conference on Database Systems for Advanced Applications (DASFAA 2013), Wuhan, China (Best Demo Award Runner-Up) S.446-449 (2013) (Demo)
[DASFAA 2013]
Günnemann S., Boden B., Färber I., Seidl T.:
Efficient Mining of Combined Subspace and Subgraph Clusters in Graphs with Feature Vectors
Proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2013), Gold Coast, Queensland, Australia S.261-275 (2013)
Seidl T., Fries S., Boden B.:
MR-DSJ: Distance-Based Self-Join for Large-Scale Vector Data Analysis with MapReduce
15. GI-Fachtagung Datenbanksysteme für Business, Technologie und Web (BTW 2013), Magdeburg, Germany S.37-56 (2013)

2012

Hassani M., Seidl T.:
Distributed Weighted Clustering of Evolving Sensor Data Streams with Noise
Journal of Digital Information Management (JDIM) Volume 10, No. 6, December 2012 S.410-420 (2012)
[JDIM ] [Volume 10, Issue 6, December 2012]
Assam R., Hassani M., Seidl T.:
Differential Private Trajectory Obfuscation
Proc. of the 9th International Conference on Mobile and Ubiquitous Systems (MobiQuitous 2012), Beijing, China S.139-151 (2012)
[MOBIQUITOUS 2012]
Tatu A., Maaß F., Färber I., Bertini E., Schreck T., Seidl T., Keim D. A.:
Subspace Search and Visualization to Make Sense of Alternative Clusterings in High-Dimensional Data
Proc. IEEE Symposium on Visual Analytics Science and Technology S.63-72 (2012)
[IEEE-VAST 2012]
Assam R., Seidl T.:
TMC-Pattern: Holistic Trajectory Extraction, Modeling and Mining
Proc. of 1st International Workshop on Analytics for Big Geospatial Data (BigSpatial-2012), held in conjunction with 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2012), Redondo Beach, CA, USA S.71-80 (2012)
[BigSpatial 2012] [ACM SIGSPATIAL GIS 2012]
Zimmer (née Ivanescu) A., Albin T., Abel D., Seidl T.:
Employing the Principal Hessian Direction for Building Hinging Hyperplane Models
Workshop on Optimization Based Techniques for Emerging Data Mining (OEDM 2012) in conjunction with the IEEE International Conference on Data Mining (ICDM 2012), Brussels, Belgium. S.481-485 (2012)
[ICDM 2012]
Günnemann S., Dao P., Jamali M., Ester M.:
Assessing the Significance of Data Mining Results on Graphs with Feature Vectors
Proc. IEEE International Conference on Data Mining (ICDM 2012), Brussels, Belgium S.270-279 (2012)
[ICDM 2012]
Günnemann S., Kremer H., Laufkötter C., Seidl T.:
Tracing Evolving Subspace Clusters in Temporal Climate Data
Data Mining and Knowledge Discovery Journal (DMKD), Vol. 24, Nr. 2 S.387-410 (2012)
[Full Text PDF (Springer Open Access)]
Kremer H., Günnemann S., Held A., Seidl T.:
Effective and Robust Mining of Temporal Subspace Clusters
Proc. IEEE International Conference on Data Mining (ICDM), Brussels, Belgium S.369-378 (2012)
[ICDM 2012]
Kranen P., Wels S., Rohlfs T., Raubach S., Seidl T.:
A Tool for Automated Evaluation of Algorithms
Proceedings of The 21st ACM Conference on Information and Knowledge Management (CIKM 2012), Maui, USA S.2692-2694 (2012) (Demo)
Boden B., Günnemann S., Seidl T.:
Tracing Clusters in Evolving Graphs with Node Attributes
Proceedings of The 21st ACM Conference on Information and Knowledge Management (CIKM 2012), Maui, USA  S.2331-2334 (2012) (poster presentation)
Boden B.:
Efficient Combined Clustering of Graph and Attribute Data
PhD Workshop of the 38th International Conference on Very Large Data Bases (VLDB 2012), Istanbul (2012)
[VLDB 2012]
Günnemann S., Boden B., Seidl T.:
Finding Density-Based Subspace Clusters in Graphs with Feature Vectors
Data Mining and Knowledge Discovery Journal (DMKD), Vol. 25, Nr. 2 S.243-269 (2012)
Günnemann S.:
Subspace Clustering for Complex Data
Dissertation, Fakultät für Mathematik, Informatik und Naturwissenschaften, RWTH Aachen University. (2012) Tag der mündlichen Prüfung: 15.03.2012
[RWTH Bibliothek] [URN]
Günnemann S., Boden B., Seidl T.:
Substructure Clustering: A Novel Mining Paradigm for Arbitrary Data Types
Proc. of the 24th International Conference on Scientific and Statistical Database Management (SSDBM 2012), Chania, Greece S.280-297 (2012)
[SSDBM 2012]
Zimmer (née Ivanescu) A., Kranen P., Seidl T.:
Hinging Hyperplane Models for Multiple Predicted Variables
Proceedings of the 24th International Conference on Scientific and Statistical Database Management (SSDBM 2012), Chania, Greece S.431-448 (2012)
[SSDBM 2012]
Kranen P., Hassani M., Seidl T.:
BT* - An Advanced Algorithm for Anytime Classification
Proc. of the 24th International Conference on Scientific and Statistical Database Management (SSDBM 2012), Chania, Greece S.298-315 (2012)
[SSDBM 2012]
Hassani M., Seidl T.:
Resource-Aware Distributed Clustering of Drifting Sensor Data Streams
The 4th International Conference on Networked Digital Technologies (NDT 2012), Dubai, UAE. S.592-607 (2012)
[NDT 2012]
Kranen P., Assent I., Seidl T.:
An Index-inspired Algorithm for Anytime Classification on Evolving Data Streams
Datenbank-Spektrum (Springer DASP), Volume 12, Issue 1 S.43-50 (2012) DOI: 10.1007/s13222-012-0083-9
[DASP Journal - full text]
Müller E., Günnemann S., Färber I., Seidl T.:
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data
Tutorial at the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2012), Kuala Lumpur, Malaysia (2012)
[PAKDD 2012] [Tutorial Website]
Kremer H., Günnemann S., Held A., Seidl T.:
Mining of Temporal Coherent Subspace Clusters in Multivariate Time Series Databases
Proceedings 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Kuala Lumpur, Malaysia S.444-455 (2012)  
[PAKDD 2012] [full text PDF]
Günnemann S., Kremer H., Musiol R., Haag R., Seidl T.:
A Subspace Clustering Extension for the KNIME Data Mining Framework
Proc. IEEE International Conference on Data Mining Workshops (ICDMW), Brussels, Belgium S.886-889 (2012) (Demo)
[ICDM 2012] [Download Page]
Assent I., Kranen P., Baldauf C., Seidl T.:
AnyOut: Anytime Outlier Detection on Streaming Data
The 17th International Conference on Database Systems for Advanced Applications (DASFAA 2012), Busan, South Korea (2012)
[DASFAA 2012]
Zimmer (née Ivanescu) A., Kranen P., Smieschek M., Driessen P., Seidl T.:
PA-Miner: Process Analysis using Retrieval, Modeling, and Prediction
The 17th International Conference on Database Systems for Advanced Applications (DASFAA 2012), Busan, South Korea (2012) (Demo)
[DASFAA 2012]
Kranen P., Kremer H., Jansen T., Seidl T., Bifet A., Holmes G., Pfahringer B., Read J.:
Stream Data Mining using the MOA Framework
The 17th International Conference on Database Systems for Advanced Applications (DASFAA), Busan, South Korea S.309-313 (2012) (Demo)
[DASFAA 2012]
Müller E., Günnemann S., Färber I., Seidl T.:
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data
Tutorial at IEEE 28th International Conference on Data Engineering (ICDE 2012), Washington, DC, USA (2012)
[ICDE 2012] [Tutorial Website]

2011

Kranen P.:
Anytime Algorithms for Stream Data Mining
Dissertation, Fakultät für Mathematik, Informatik und Naturwissenschaften, RWTH Aachen University (2011) Tag der mündlichen Prüfung: 14.09.2011
[[RWTH Bibliothek]] [urn:nbn:de:hbz:82-opus-38501]
Günnemann S., Müller E., Raubach S., Seidl T.:
Flexible Fault Tolerant Subspace Clustering for Data with Missing Values
Proc. IEEE International Conference on Data Mining (ICDM 2011), Vancouver, Canada (2011)
[ICDM 2011]
Kranen P., Assent I., Baldauf C., Seidl T.:
The ClusTree: Indexing Micro-Clusters for Anytime Stream Mining
Knowledge and Information Systems Journal (Springer KAIS), Volume 29, Issue 2 S.249-272 (2011) DOI 10.1007/s10115-010-0342-8
[KAIS Journal - full text]
Assam R., Seidl T.:
Preserving Privacy of Moving Objects Spatio-Temporal Data Stream Using Temporal Clustering
4th ACM SIGSPATIAL International Workshop on Security and Privacy in GIS and LBS (SPRINGl 2011), held in conjunction with 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2011) November 1-4, 2011 in Chicago, Illinois, USA. S. 9-16 (2011)
[SPRINGL 2011] [ACM SIGSPATIAL GIS 2011]
Günnemann S., Färber I., Müller E., Assent I., Seidl T.:
External Evaluation Measures for Subspace Clustering
Proc. 20th ACM Conference on Information and Knowledge Management (CIKM 2011), Glasgow, UK S.1363-1372 (2011)
[CIKM 2011]
Müller E., Assent I., Günnemann S., Seidl T.:
Scalable Density-Based Subspace Clustering
Proc. 20th ACM Conference on Information and Knowledge Management (CIKM 2011), Glasgow, UK S.1077-1086 (2011)
[CIKM 2011]
Kremer H., Kranen P., Jansen T., Seidl T., Bifet A., Holmes G., Pfahringer B.:
An Effective Evaluation Measure for Clustering on Evolving Data Streams
Proc. of the 17th ACM Conference on Knowledge Discovery and Data Mining (SIGKDD 2011), San Diego, CA, USA S.868-876 (2011)
[KDD 2011] [DOI: 10.1145/2020408.2020555]
Zimmer (née Ivanescu) A., Albin T., Abel D., Seidl T.:
Employing Correlation Clustering for the Identification of Piecewise Affine Models
Workshop on Knowledge Discovery, Modeling and Simulation (KDMS 2011) in conjunction with the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2011), CA, San Diego, USA  S.7-14 (2011) Best Student Paper Award
[KDMS 2011] [KDD 2011]
Günnemann S., Boden B., Seidl T.:
DB-CSC: A density-based approach for subspace clustering in graphs with feature vectors
Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2011), Athens, Greece S.565-580 (2011) ECML PKDD 2011 Best Paper Award in Data Mining
[ECML PKDD 2011] [Full Text PDF]
Hassani M., Seidl T.:
Network Intrusion Detection using a Secure Ranking of Hidden Outliers
Proc. of the seventh International Computing Conference in Arabic (ICCA 2011), Riyadh, Saudi Arabia (to appear) (2011)
[ICCA 2011]
Kranen P., Reidl F., Sanchez Villaamil F., Seidl T.:
Hierarchical Clustering for Real-Time Stream Data with Noise
Proc. of the 23nd International Conference on Scientific and Statistical Database Management (SSDBM 2011), Portland, Oregon, USA S.405-413 (2011)
[SSDBM 2011]
Zimmer (née Ivanescu) A., Wichterich M., Seidl T.:
ClasSi: Measuring Ranking Quality in the Presence of Object Classes with Similarity Information
Workshop on Quality Issues, Measures of Interestingness and Evaluation of Data Mining Models (QIMIE 2011), in conjunction with the International Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2011), Shenzhen, China. S.185-196 (2011)
[PAKDD 2011] [QIMIE 2011] [DOI: 10.1007/978-3-642-28320-8_16]
Günnemann S., Kremer H., Laufkötter C., Seidl T.:
Tracing Evolving Clusters by Subspace and Value Similarity
Proc. 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2011), Shenzhen, China S.444-456 (2011)
[PAKDD 2011]
Müller E., Günnemann S., Färber I., Seidl T.:
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data
Tutorial at SIAM International Conference on Data Mining (SDM 2011), Mesa, Arizona, USA. (2011)
[SDM 2011] [Tutorial Website]
Bifet A., Holmes G., Pfahringer B., Read J., Kranen P., Kremer H., Jansen T., Seidl T.:
MOA: a Real-time Analytics Open Source Framework
Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2011), Athens, Greece S.617-620 (2011) (Demo)
[ECML PKDD 2011]
Müller E., Schiffer M., Seidl T.:
Statistical Selection of Relevant Subspace Projections for Outlier Ranking
Proc. IEEE 27th International Conference on Data Engineering (ICDE 2011), Hannover, Germany S.434-445 (2011) (full paper acceptance rate 19.8%)
[ICDE 2011]
Müller E., Assent I., Günnemann S., Gerwert P., Hannen M., Jansen T., Seidl T.:
A Framework for Evaluation and Exploration of Clustering Algorithms in Subspaces of High Dimensional Databases
Proc. 14th GI Conference on Database Systems for Business, Technology, and the Web (BTW 2011), Kaiserslautern, Germany S.347-366 (2011)
[BTW 2011]
Hassani M., Kranen P., Seidl T.:
Noise-aware Concise Clustering of Streaming Sensor Data in a Logarithmic Time
KDML Workshop on Knowledge Discovery, Data Mining and Machine Learning in conj. with LWA 2011, Magdeburg, Germany (2011)
[LWA 2011]

2010

Müller E.:
Efficient Knowledge Discovery in Subspaces of High Dimensional Databases
Dissertation, Fakultät für Mathematik, Informatik und Naturwissenschaften, RWTH Aachen University. (2010) Tag der mündlichen Prüfung: 09.06.2010
[RWTH Bibliothek]
Müller E., Günnemann S., Färber I., Seidl T.:
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data
Tutorial at IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia S.1220 (2010)
[ICDM 2010] [Tutorial Website]
Kranen P., Müller E., Assent I., Krieger R., Seidl T.:
Incremental Learning of Medical Data for Multi-Step Patient Health Classification
Plant C., Böhm C. (eds.): Database Technology for Life Sciences and Medicine, World Scientific Publishing S.321-344 (2010)
[World Scientific Publishing ]
Bifet A., Holmes G., Pfahringer B., Kranen P., Kremer H., Jansen T., Seidl T.:
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Journal of Machine Learning Research (JMLR) Workshop and Conference Proceedings, Volume 11: Workshop on Applications of Pattern Analysis S.44-50 (2010)
[www.pascal-network.org/wapa2010] [JMLR Proc. Vol. 11] [pdf]
Günnemann S., Färber I., Boden B., Seidl T.:
Subspace Clustering Meets Dense Subgraph Mining: A Synthesis of Two Paradigms
Proc. IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia S.845-850 (2010)
[ICDM 2010] [Supplementary material]
Günnemann S., Kremer H., Seidl T.:
Subspace Clustering for Uncertain Data
Proc.  SIAM International Conference on Data Mining (SDM 2010), Columbus, Ohio, USA. S.385-396 (2010)
[SDM 2010]
Müller E., Schiffer M., Seidl T.:
Adaptive Outlierness for Subspace Outlier Ranking
Proc. 19th ACM Conference on Information and Knowledge Management (CIKM 2010), Toronto, Canada S.1629-1632 (2010)
[CIKM 2010]
Kranen P., Günnemann S., Fries S., Seidl T.:
MC-Tree: Improving Bayesian Anytime Classification
Proc. of the 22nd International Conference on Scientific and Statistical Database Management (SSDBM 2010), Heidelberg, Germany, Springer LNCS S.252-269 (2010)
[SSDBM 2010] [DOI: 10.1007/978-3-642-13818-8_19]
Günnemann S., Seidl T.:
Subgraph Mining on Directed and Weighted Graphs
Proc. 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2010), 21-24 June, 2010 - Hyderabad, India. Springer Lecture Notes in Artificial Intelligence (LNAI) S.133-146 (2010)
[PAKDD 2010]
Kranen P., Krieger R., Denker S., Seidl T.:
Bulk loading Hierarchical Mixture Models for Efficient Stream Classification
Proc. 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2010), Hyderabad, India. Springer LNAI S.325-334 (2010)
[PAKDD 2010] [DOI: 10.1007/978-3-642-13672-6_32]
Hassani M., Müller E., Spaus P., Faqolli A., Palpanas T., Seidl T.:
Self-Organizing Energy Aware Clustering of Nodes in Sensor Networks Using Relevant Attributes
Proc. 4th International Workshop on Knowledge Discovery from Sensor Data (SensorKDD 2010) in conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, USA S.87-96 (2010)
[SensorKDD 2010]
Müller E.:
Mining Subspace Clusters: Enhanced Models, Efficient Algorithms and an Objective Evaluation Study
PhD Workshop of the 36th International Conference on Very Large Data Bases (VLDB 2010), Singapore (2010)
[VLDB 2010] [Full Text PDF]
Färber I., Günnemann S., Kriegel H., Kröger P., Müller E., Schubert E., Seidl T., Zimek A.:
On Using Class-Labels in Evaluation of Clusterings
Proc. 1st International Workshop on Discovering, Summarizing and Using Multiple Clusterings (MultiClust 2010) in conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, USA (2010)
[MultiClust 2010] [Full Text PDF] [Talk Slides]
Günnemann S., Färber I., Müller E., Seidl T.:
ASCLU: Alternative Subspace Clustering
Proc. 1st International Workshop on Discovering, Summarizing and Using Multiple Clusterings (MultiClust 2010) in conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, USA (2010)
[MultiClust 2010] [Full Text PDF] [Talk Slides]
Assent I., Müller E., Günnemann S., Krieger R., Seidl T.:
Less is More: Non-Redundant Subspace Clustering
Proc. 1st International Workshop on Discovering, Summarizing and Using Multiple Clusterings (MultiClust 2010) in conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, USA (2010)
[MultiClust 2010] [Full Text PDF] [Talk Slides]
Assent I., Kranen P., Baldauf C., Seidl T.:
Detecting Outliers on Arbitrary Data Streams using Anytime Approaches
International Workshop on Novel Data Stream Pattern Mining Techniques (StreamKDD 2010) in conjunction with 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, USA S.10-16 (2010)
[StreamKDD 2010] [online proceedings]
Kremer H., Günnemann S., Seidl T.:
Detecting Climate Change in Multivariate Time Series Data by Novel Clustering and Cluster Tracing Techniques
Proc. 2nd IEEE ICDM Workshop on Knowledge Discovery from Climate Data: Prediction, Extremes, and Impacts (CLIMKD 2010) in conjunction with IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia S.96-97 (2010)
[ICDM 2010] [CLIMKD 2010]
Bifet A., Holmes G., Pfahringer B., Kranen P., Kremer H., Jansen T., Seidl T.:
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Invited presentation at the International Workshop on Handling Concept Drift in Adaptive Information Systems in conjunction with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2010). S.3-16 (2010)
Hassani M., Seidl T.:
Network Intrusion Detection using a Secure Ranking of Hidden Outliers
Proceedings of the 15th Syrian Computer Society Meeting on Computer Network Security 27-28 October, Aleppo - Syria. Paper [PDF] (2010)
Günnemann S., Kremer H., Färber I., Seidl T.:
MCExplorer: Interactive Exploration of Multiple (Subspace) Clustering Solutions
Proc. IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia S.1387-1390 (2010) (Demo)
[ICDM 2010]
Kranen P., Kremer H., Jansen T., Seidl T., Bifet A., Holmes G., Pfahringer B.:
Clustering Performance on Evolving Data Streams: Assessing Algorithms and Evaluation Measures within MOA
Proc. IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia S.1400-1403 (2010) (Demo)
[ICDM 2010]
Günnemann S., Färber I., Kremer H., Seidl T.:
CoDA: Interactive Cluster Based Concept Discovery
Proceedings of the VLDB Endowment (PVLDB) 3(2): 1633-1636 (2010) S.1633-1636 (2010) (Demo)
[VLDB 2010]
Kranen P., Kremer H., Jansen T., Seidl T., Bifet A., Holmes G., Pfahringer B.:
Benchmarking Stream Clustering Algorithms within the MOA Framework
16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, USA (2010) 2010 KDD - MOA (demo).pdf(Demo)
[KDD 2010]
Müller E., Schiffer M., Gerwert P., Hannen M., Jansen T., Seidl T.:
SOREX: Subspace Outlier Ranking Exploration Toolkit
Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2010), Barcelona, Spain, Springer, LNAI 6323 S.607-610 (2010) (Demo)
[ECML PKDD 2010]
Hassani M.:
Distributed Processing of Data Streams and Large Data Sets
In: P. G. Kolaitis, M. Lenzerini and N. Schweikardt: Data Exchange, Integration, and Streams (GI-Dagstuhl-Seminar), Dagstuhl Seminar 10452. Slides [PDF]   (2010)
[Dagstuhl seminar homepage]

2009

Mamoulis N., Seidl T., Pedersen T. B., Torp K., Assent I.:
Advances in Spatial and Temporal Databases - Proceedings of SSTD 2009
Proceedings of the 11th International Symposium on Spatial and Temporal Databases (SSTD), Aalborg, Denmark, July 8-10, 2009. Springer Verlag, Lecture Notes in Computer Sciences, Vol. 5644. (2009)
[SSTD 2009] [Springer LNCS 5644]
Seidl T.:
Nearest Neighbor Classification
Liu L., Özsu M. T. (eds.): Encyclopedia of Database Systems. Springer. S.1885-1890 (2009)
[print+eReference] [print only]
Kranen P., Seidl T.:
Harnessing the Strengths of Anytime Algorithms for Constant Data Streams
Data Mining and Knowledge Discovery Journal (Springer DMKD), Special Issue on Selected Papers from ECML PKDD 2009, Vol. 19, No. 2, S.245-260 (2009) [DOI 10.1007/s10618-009-0139-0]
[DMKD Journal - full text]
Müller E., Günnemann S., Assent I., Seidl T.:
Evaluating Clustering in Subspace Projections of High Dimensional Data
Proc. 35th International Conference on Very Large Data Bases (VLDB 2009), Lyon, France, PVLDB Journal, Vol. 2, No. 1, S.1270-1281 (2009) (Experiments and Analyses track, acceptance rate 23.1%)
[VLDB 2009] [Full Text PDF] [Supplementary material]
Kranen P., Assent I., Baldauf C., Seidl T.:
Self-Adaptive Anytime Stream Clustering
Proc. IEEE International Conference on Data Mining (ICDM 2009), Miami, USA S.249-258 (2009) (full paper acceptance rate 8.9%)
[ICDM 2009] [DOI: 10.1109/ICDM.2009.47]
Müller E., Assent I., Günnemann S., Krieger R., Seidl T.:
Relevant Subspace Clustering: Mining the Most Interesting Non-Redundant Concepts in High Dimensional Data
Proc. IEEE International Conference on Data Mining (ICDM 2009), Miami, USA S.377-386 (2009) (full paper acceptance rate 8.9%)
[ICDM 2009] [Supplementary material]
Kranen P., Seidl T.:
Harnessing the Strengths of Anytime Algorithms for Constant Data Streams
Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2009), Bled, Slowenia. S.31 (2009) The Paper has additionally been chosen for publication in the Data Mining and Knowledge Discovery Journal, ECML PKDD Special Issue (acceptance rate 3.3%).
[ECML PKDD 2009]
Müller E., Assent I., Krieger R., Günnemann S., Seidl T.:
DensEst: Density Estimation for Data Mining in High Dimensional Spaces
Proc. SIAM International Conference on Data Mining (SDM 2009), Sparks, Nevada, USA. S.173-184 (2009) (full paper acceptance rate 15.6%)
[SDM 2009] [PDF]
Günnemann S., Müller E., Färber I., Seidl T.:
Detection of Orthogonal Concepts in Subspaces of High Dimensional Data
Proc. 18th ACM Conference on Information and Knowledge Management (CIKM 2009), Hong Kong, China S.1317-1326 (2009) (full paper acceptance rate 14.5%)
[CIKM 2009] [DOI: 10.1145/1645953.1646120]
Seidl T., Assent I., Kranen P., Krieger R., Herrmann J.:
Indexing Density Models for Incremental Learning and Anytime Classification on Data Streams
Proc. 12th International Conference on Extending Database Technology (EDBT/ICDT 2009), Saint-Petersburg, Russia. S.311-322 (2009)
[EDBT/ICDT 2009] [DOI: 10.1145/1516360.1516397]
Ahmadi B., Hadjieleftheriou M., Seidl T., Srivastava D., Venkatasubramanian S.:
Type-Based Categorization of Relational Attributes
Proc. 12th International Conference on Extending Database Technology (EDBT/ICDT 2009), Saint-Petersburg, Russia. S.84-95 (2009)
[EDBT/ICDT 2009]
Müller E., Assent I., Seidl T.:
HSM: Heterogeneous Subspace Mining in High Dimensional Data
Proc. 21st International Conference on Scientific and Statistical Database Management (SSDBM 2009), New Orleans, Louisiana, USA S.497-516 (2009)
[SSDBM 2009]
Hassani M., Müller E., Seidl T.:
EDISKCO: Energy Efficient Distributed In-Sensor-Network K-center Clustering with Outliers
Proc. 3rd International Workshop on Knowledge Discovery from Sensor Data (SensorKDD 2009) in conjunction with 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2009), Paris, France S.39-48 (2009)
[SensorKDD 2009]
Kranen P.:
Using Index Structures for Anytime Stream Mining
PhD Workshop of the International Conference on Very Large Data Bases (VLDB 2009), Lyon, France (2009) 2009 VLDB (PhD Workshop) - Anytime Stream Mining.pdf
[VLDB 2009]
Müller E., Assent I., Günnemann S., Jansen T., Seidl T.:
OpenSubspace: An Open Source Framework for Evaluation and Exploration of Subspace Clustering Algorithms in WEKA
Proc. 1st Open Source in Data Mining Workshop (OSDM 2009) in conjunction with 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2009), Bangkok, Thailand S.2-13 (2009)
[OpenSubspace Project] [OSDM 2009]
Schiffer M., Müller E., Seidl T.:
SubRank: Ranking Local Outliers in Projections of High-Dimensional Spaces
Datenbank-Spektrum Vol. 9 Issue 29 S.53-55 (2009) (BTW-Studierendenprogramm)
[DB Spektrum]
Schiffer M.:
SubRank: Ranking local outliers in projections of high-dimensional spaces
Studierendenprogramm at the 13th GI-conference on Databases, Technology and Web (BTW 2009), Münster, Germany [pdf] (2009)
[BTW 2009 Studierendenprogramm]
Fries S.:
Bestimmung des optimalen Verzweigungsgrades hierarchischer Anytime-Klassifikatoren
Studierendenprogramm at the 13th GI-conference on Databases, Technology and Web (BTW 2009), Münster, Germany (2009) (ausgezeichnet als bester Beitrag im Studierendenprogramm der BTW 2009 )
[BTW 2009 Studierendenprogramm]
Färber I.:
Mining orthogonaler Konzepte in hochdimensionalen Datenbanken
GI Informatiktage 27./28. März 2009 in Bonn S.153-156 (2009)
[Informatiktage]

2008

Krieger R.:
Efficient density-based methods for knowledge discovery in databases
Dissertation, Fakultät für Mathematik, Informatik und Naturwissenschaften, RWTH Aachen University. (2008) Tag der mündlichen Prüfung: 09.07.2008
[RWTH Bibliothek]
Assent I., Krieger R., Glavic B., Seidl T.:
Clustering Multidimensional Sequences in Spatial and Temporal Databases
In: International Journal on Knowledge and Information Systems (KAIS) Vol. 16, Issue 1 S.29-51 (2008)
[KAIS] [DOI: 10.1007/s10115-007-0121-3]
Assent I., Krieger R., Müller E., Seidl T.:
INSCY: Indexing Subspace Clusters with In-Process-Removal of Redundancy
Proc. IEEE International Conference on Data Mining (ICDM 2008), Pisa, Italy S.719-724 (2008) (acceptance rate 20%)
[ICDM 2008]
Assent I., Krieger R., Müller E., Seidl T.:
EDSC: Efficient Density-Based Subspace Clustering
Proc. ACM 17th Conference on Information and Knowledge Management (CIKM 2008), Napa Valley, USA S.1093-1102 (2008) (full paper acceptance rate 17%)
[CIKM 2008]
Assent I., Krieger R., Welter P., Herbers J., Seidl T.:
SubClass: Classification of Multidimensional Noisy Data Using Subspace Clusters
Proc. 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2008), Springer LNCS/LNAI, Osaka, Japan S.40-52 (2008)
[PAKDD 2008] [DOI: 10.1007/978-3-540-68125-0_6]
Müller E., Assent I., Krieger R., Jansen T., Seidl T.:
Morpheus: Interactive Exploration of Subspace Clustering
Proc. 14th ACM SIGKDD International Conference on Knowledge Discovery in Databases (KDD 2008), Las Vegas, USA S.1089-1092 (2008) (Demo)
[KDD 2008]
Müller E., Assent I., Steinhausen U., Seidl T.:
OutRank: ranking outliers in high dimensional data
Proc. 2nd International Workshop on Ranking in Databases (DBRank 2008) in conjunction with IEEE 24th International Conference on Data Engineering (ICDE 2008), Cancun, Mexico S.600-603 (2008)
[ICDE 2008 Workshops] [DOI: 10.1109/ICDEW.2008.4498387]
Assent I., Müller E., Krieger R., Jansen T., Seidl T.:
Pleiades: Subspace Clustering and Evaluation
Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2008), Antwerp, Belgium, Springer LNCS 5212. S.666-671 (2008) (Demo)
[ECML PKKD 2008] [Springer LNCS 5212]
Kranen P., Kensche D., Kim S., Zimmermann N., Müller E., Quix C., Li X., Gries T., Seidl T., Jarke M., Leonhardt S.:
Mobile Mining and Information Management in HealthNet Scenarios
Proceedings of the 9th IEEE MDM International Conference on Mobile Data Management (MDM 2008), Beijing, China S.215-216 (2008) (Demo)
[MDM 2008]
Ruau D., Kolarik C., Mevissen H.-T., Müller E., Assent I., Krieger R., Seidl T., Hofmann-Apitius M., Zenke M.:
Public microarray repository semantic annotation with ontologies employing text mining and expression profile correlation
BMC Bioinformatics 2008, 9(Suppl 10):O5 doi:10.1186/1471-2105-9-S10-O54th ISCB Student Council Symposium in conjunction with International Conference Intelligent Systems for Molecular Biology (ISMB 2008), Toronto, Canada (2008) (poster and oral presentation)
[ISCB 2008] [ISMB 2008]
Kim S., Leonhardt S., Zimmermann N., Kranen P., Kensche D., Müller E., Quix C.:
Influence of contact pressure and moisture on the signal quality of a newly developed textile ECG sensor shirt
5th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2008), Hong Kong, China (2008)
[BSN 2008]
Seidl T., Müller E., Assent I., Steinhausen U.:
Outlier detection and ranking based on subspace clustering
Dagstuhl Seminar 08421 on Uncertainty Management in Information Systems. (2008)
[Dagstuhl seminar 08421] [paper at DROPS]

2007

Assent I., Krieger R., Müller E., Seidl T.:
VISA: Visual Subspace Clustering Analysis
ACM SIGKDD Explorations Special Issue on Visual Analytics, Vol. 9, Issue 2 S.5-12 (2007)
[SIGKDD Explorations] [Full Text PDF]
Zaki M. J., Peters M., Assent I., Seidl T.:
Clicks: An effective algorithm for mining subspace clusters in categorical datasets
Data & Knowledge Engineering (DKE) 60 (1) S.51-70 (2007)
[DKE] [Abstract]
Assent I., Krieger R., Müller E., Seidl T.:
DUSC: Dimensionality Unbiased Subspace Clustering
Proc. IEEE International Conference on Data Mining (ICDM 2007), Omaha, Nebraska, USA S.409-414 (2007) (acceptance rate 19%)
[ICDM 2007]
Krieger R.:
Nature inspired local pattern detection: new approaches to open data mining questions
Proc. Workshop on Nature-inspired Methods for Local Pattern Detection (NiLOP 2007) in conjunction with NiSIS 2007, St. Julians, Malta (2007)
Müller E.:
Density-based clustering in arbitrary subspaces
Proc. Workshop on Nature-inspired Methods for Local Pattern Detection (NiLOP 2007) in conjunction with NiSIS 2007, St. Julians, Malta (2007)
Assent I.:
Population dynamic coverage for subspace search
Proc. Workshop on Nature-inspired Methods for Local Pattern Detection (NiLOP 2007) in conjunction with NiSIS 2007, St. Julians, Malta (2007)
Assent I., Krieger R., Müller E., Steffens A., Seidl T.:
Evolutionary Subspace Search in biologically-inspired Optimal Niches
Proc. Annual Symposium on Nature inspired Smart Information Systems (NiSIS 2007), St Julians, Malta (2007)
[http://www.nisis.risk-technologies.com/]
Assent I., Krieger R., Müller E., Seidl T.:
Removing Dimensionality Bias in Density-based Subspace Clustering
Abstract in Dutch-Belgian Data Base Day (DBDBD 2007), Eindhoven, NL (2007)
[DBDBD 2007]
Aleksandrowicz A., Kensche D., Kim S., Kranen P., Müller E., Quix C.:
Mobile and Wearable P2P Information Management in HEALTHNET Applications
IEEE Benelux Chapter on Engineering in Medicine and Biology (EMB) (2007)
Assent I., Krieger R., Müller E., Seidl T.:
Subspace outlier mining in large multimedia databases
In: M. Berthold, K. Morik, A. Siebes(eds.): Parallel Universes and Local Patterns, Dagstuhl Seminar 07181 (2007)
[Dagstuhl seminar homepage] [Dagstuhl DROPS Document]
Müller E.:
Subspace Clustering für die Analyse von CGH Daten
Studierendenprogramm at the 12th GI-conference on Databases, Technology and Web (BTW 2007), Aachen, Germany: 31-33 (2007)
[BTW 2007] [BTW Studierendenprogramm]

2006

Assent I., Krieger R., Glavic B., Seidl T.:
Spatial Multidimensional Sequence Clustering
Proc. 1st International Workshop on Spatial and Spatio-temporal Data Mining (SSTDM 2006)In conjunction with ICDM 2006, Hong Kong S.343-348 (2006)
[SSTDM 2006]
Assent I., Krieger R., Steffens A., Seidl T.:
A Novel Biology inspired Model for Evolutionary Subspace Clustering
Proc. Annual Symposium on Nature inspired Smart Information Systems (NiSIS 2006), Puerto de la Cruz, Tenerife (2006)
[NiSIS Project]
Kriegel H., Kröger P., Pfeifle M., Brecheisen S., Pötke M., Schubert M., Seidl T.:
Similarity Search for Voxelized CAD Objects
In: Zongmin Ma (ed.): Database Modeling for Industrial Data Management: Emerging Technologies and Applications. Idea Group Inc. S.115-147 (2006) ISBN: 1-59140-684-6 (Hard Cover), 1-59140-685-4 (Soft Cover)
[publisher]
Assent I., Bartusseck S., Glavic B., Krieger R., Nacken H., Seidl T., Sewilam H.:
Clustering für Fließgewässer - Data Mining zur Entscheidungsunterstützung in der Hydrologie
In RWTH Aachen: Informatik und Informationstechnik, RWTH Themen 2/2006. S.66-69 (2006)
[RWTH Themen]
Seidl T., Schönauer S., Kailing K.:
Data Mining and Efficient Similarity Retrieval of Hierarchical Structures from Large Databases
J.-R. Sack, M. Sester, M. Worboys, P. van Oosterom (eds.): Spatial Data - mining, processing and communicating. Dagstuhl Seminar 06101 (2006)
[seminar homepage]

2005

Zaki M., Peters M., Assent I., Seidl T.:
CLICKS: An Effective Algorithm for Mining Subspace Clusters in Categorical Datasets
Proc. ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD 2005), Chicago, IL, USA S.736 - 742 (2005) (acceptance rate 22%)
[KDD 2005]
Seidl T., Krieger R., Assent I., Glavic B., Nacken H.:
Data Mining zur Entscheidungsunterstützung in der Hydrologie
In: Nacken H., Bartusseck S., Sewilam H. (Eds.): Entscheidungsunterstützung in der Wasserwirtschaft - Von der Theorie zum Anwendungsfall - Beiträge zum Tag der Hydrologie 2005, Aachen. Forum für Hydrologie und Wasserbewirtschaftung, Heft 10.05 S.137-145 (2005)
[Hydrology]

1999

Ankerst M., Kastenmüller G., Kriegel H.-P., Seidl T.:
Nearest Neighbor Classification in 3D Protein Databases
Proc. 7th Int. Conf. on Intelligent Systems for Molecular Biology (ISMB 1999), Heidelberg, Germany. AAAI Press S.34-43 (1999)
Seidl T., Kriegel H.-P.:
Mining Protein Databases
Proc. Tag der Informatik Bioinformatik (TdI), Institute for Computer Science, University of Munich (1999)