Publications

Guo, C., Ma, M., Yang, B., Jensen, C. S. & Kaul, M. (2012). EcoMark: Evaluating Models of Vehicular Environmental Impact. In I. Cruz & C. Knoblock (Eds.), Proceedings of the 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems: ACM SIGSPATIAL GIS 2012 (pp. 269-278). Association for Computing Machinery. https://doi.org/10.1145/2424321.2424356

Dang, X.-H., Assent, I. & Bailey, J. (2012). Multiple Clustering Views via Constrained Projections. In E. Müller, T. Seidl & A. Zimek (Eds.), 2012 SIAM International Conference on Data Mining: 3rd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings (pp. 23-30). Society for Industrial and Applied Mathematics. http://siam.omnibooksonline.com/2012datamining/data/papers/WS06.pdf

Muller, E., Assent, I., Iglesias, P., Mülle, Y. & Böhm, K. B. (2012). Outlier Ranking via Subspace Analysis in Multiple Views of the Data. In Proceedings of the 12th IEEE International Conference on Data Mining, ICDM (pp. 529 - 538 ). IEEE Communications Society. https://doi.org/10.1109/ICDM.2012.112

Yiu, M. L., Assent, I. & Jensen, C. S. (2012). Outsourced Similarity Search on Metric Data Assets. I E E E Transactions on Knowledge & Data Engineering, 24(2), 338-352. https://doi.org/10.1109/TKDE.2010.222

Müller, E., Assent, I., Günnemann, S., Gerwert, P., Hannen, M., Jansen, T. & Seidl, T. (2011). A Framework for Evaluation and Exploration of Clustering Algorithms in Subspaces of High Dimensional Databases. In T. Härder, W. Lehner, B. Mitschang, H. Schöning & H. Schwarz (Eds.), Proceedings of the 14th GI Conference on Database Systems for Business, Technology, and the Web (BTW 2011) (pp. 347-366). Gesellschaft für Informatik e.V..

Nguyen, H. V., Gopalkrishnan, V. & Assent, I. (2011). An Unbiased Distance-based Outlier Detection Approach for High-dimensional Data. Lecture Notes in Computer Science, 6587, 138-152. https://doi.org/10.1007/978-3-642-20149-3_12

Beecks, C., Assent, I. & Seidl, T. (2011). Content-Based Multimedia Retrieval in the Presence of Unknown User Preferences. Lecture Notes in Computer Science, 6523, 140-150. https://doi.org/10.1007/978-3-642-17832-0_14

Vicente, C. R., Assent, I. & Jensen, C. S. (2011). Effective Privacy-Preserving Online Route Planning. In 2011 12th IEEE International Conference on Mobile Data Management (MDM) (pp. 119-128). IEEE Computer Society Press. https://doi.org/10.1109/MDM.2011.20

Assent, I. (2011). Efficient algorithms for collaborative decision making for large scale settings. In Proceedings of the 3rd international workshop on Collaborative information retrieval (pp. 15-18). Association for Computing Machinery. https://doi.org/10.1145/2064075.2064081

Kremer, H., Günnemann, S., Ivanescu, A.-M., Assent, I. & Seidl, T. (2011). Efficient Processing of Multiple DTW Queries in Time Series Databases. Lecture Notes in Computer Science, 6809, 150-167. https://doi.org/10.1007/978-3-642-22351-8_9

Günnemann, S., Färber, I., Müller, E., Assent, I. & Seidl, T. (2011). External Evaluation Measures for Subspace Clustering. In Proceedings of the 20th ACM international conference on Information and knowledge management (pp. 1363-1372). Association for Computing Machinery. https://doi.org/10.1145/2063576.2063774

Müller, E., Assent, I., Günnemann, S. & Seidl, T. (2011). Scalable Density-Based Subspace Clustering. In Proceedings of the 20th ACM international conference on Information and knowledge management (pp. 1077-1086). Association for Computing Machinery. https://doi.org/10.1145/2063576.2063733

Kranen, P., Assent, I., Baldauf, C. & Seidl, T. (2011). The ClusTree : indexing micro-clusters for anytime stream mining. Knowledge and Information Systems, 29(2), 249-272. https://doi.org/10.1007/s10115-010-0342-8

Assent, I., Kranen, P., Baldauf, C. & Seidl, T. (2010). Detecting Outliers on Arbitrary Data Streams using Anytime Approaches. In 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, Washington, DC, USA (2010) https://doi.org/10.1145/1833280.1833282

Wichterich, M., Kranen, P., Assent, I. & Seidl, T. (2010). Efficient EMD-based Similarity Search in Medical Image Databases. In C. Plant & C. Böhm (Eds.), Database Technology for Life Sciences and Medicine (pp. 175-202). World Scientific.

Assent, I. (2010). Effiziente ähnlichkeitssuche und Data Mining in großen Multimediadatenbanken. IT - Information Technology, 52(1), 45-47. https://doi.org/10.1524/itit.2010.0570

Kranen, P., Müller, E., Assent, I., Krieger, R. & Seidl, T. (2010). Incremental Learning of Medical Data for Multi-Step Patient Health Classification. In C. Plant & C. Böhm (Eds.), Database Technology for Life Sciences and Medicine (pp. 321-344). World Scientific.

Assent, I., Müller, E., Günnemann, S., Krieger, R. & Seidl, T. (2010). Less is More: Non-Redundant Subspace Clustering. In 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, Washington, DC, USA (2010)

Assent, I. (2010). Mining and representing recommendations in actively evolving recommender systems. In International Workshop on Modeling, Managing and Mining of Evolving Social Networks (M3SN), in conjunction with IEEE International Conference on Data Engineering (ICDE 2010), Long Beach, CA, USA (pp. 282-285) https://doi.org/10.1109/ICDEW.2010.5452714

Assent, I., Kremer, H., Günnemann, S. & Seidl, T. (2010). Pattern Detector: Fast Detection of Suspicious Stream Patterns for Immediate Reaction. In Proc. International Conference on Extending Database Technology (EDBT/ICDT 2010), Lausanne, Switzerland http://www.edbt.org/Proceedings/2010-Lausanne/

Assent, I. (2009). Actively building private recommender networks for evolving reliable relationships. In Proc. International Workshop on Modeling, Managing and Mining of Evolving Social Networks (M3SN), in conjunction with IEEE International Conference on Data Engineering (ICDE 2009) (pp. 1611-1614) https://doi.org/10.1109/ICDE.2009.145

Assent, I., Wichterich, M., Krieger, R., Kremer, H. & Seidl, T. (2009). Anticipatory DTW for Efficient Similarity Search in Time Series Databases. International Conference on Very Large Data Bases. Proceedings, 826-837. http://www.informatik.uni-trier.de/~ley/db/journals/pvldb/pvldb2.html

Assent, I., Krieger, R., Welter, P., Herbers, J. & Seidl, T. (2009). Data Mining For Robust Flight Scheduling. In Data Mining for Business Applications (pp. 267-282) http://www.springer.com/computer/database+management+&+information+retrieval/book/978-0-387-79419-8

Müller, E., Assent, I., Krieger, R., Günnemann, S. & Seidl, T. (2009). DensEst: Density Estimation for Data Mining in High Dimensional Spaces. In Proceedings of the Ninth SIAM International Conference on Data Mining (pp. 175-186) http://www.siam.org/proceedings/datamining/2009/dm09.php

Assent, I. (2009). Efficient adaptive retrieval and mining in large multimedia databases. Datenbank-Spektrum, 9(29), 57.

Assent, I. (2009). Efficient adaptive retrieval and mining in large multimedia databases. Lecture Notes in Informatics, 144. http://btw2009.uni-muenster.de/oe20/cms/website.php?id=/de/index/programm.htm

Müller, E., Günnemann, S., Assent, I. & Seidl, T. (2009). Evaluating Clustering in Subspace Projections of High Dimensional Data. V L D B Journal, (1), 1270-1281. http://www.informatik.uni-trier.de/~ley/db/journals/pvldb/pvldb2.html

Assent, I., Günnemann, S., Kremer, H. & Seidl, T. (2009). High-dimensional Indexing for Multimedia Features. Lecture Notes in Informatics, 187-206. http://btw2009.uni-muenster.de/oe20/cms/website.php?id=/de/index/programm.htm

Müller, E., Assent, I., Günnemann, S. & Seidl, T. (2009). OpenSubspace: An Open Source Framework for Evaluation and Exploration of Subspace Clustering Algorithms in WEKA. In Proceedings of OSDM 2009 (pp. 1-12) http://osdm09.togaware.com/

Müller, E., Assent, I., Günnemann, S., Krieger, R. & Seidl, T. (2009). Relevant Subspace Clustering: Mining the Most Interesting Non-Redundant Concepts in High-Dimensional Data. In Proc. IEEE International Conference on Data Mining (ICDM 2009) (pp. 377-386) https://doi.org/10.1109/ICDM.2009.10

Assent, I. & Seidl, T. (2008). Advanced Data Mining Algorithms. http://www-i9.informatik.rwth-aachen.de/lehre/hauptstudium/datamining/ss2008#73

Assent, I., Krieger, R., Glavic, B. & Seidl, T. (2008). Clustering Multidimensional Sequences in Spatial and Temporal Databases. Knowledge and Information Systems, 16(1), 29-51. https://doi.org/10.1007/s10115-007-0121-3

Assent, I., Krieger, R., Müller, E. & Seidl, T. (2008). EDSC: Efficient Density-Based Subspace Clustering. In Proceeding of the 17th ACM conference on Information and knowledge management 2008, Napa Valley, California, USA (pp. 1093-1102) https://doi.org/10.1145/1458082.1458227

Assent, I. (2008). Efficient adaptive retrieval and mining in large multimedia databases.

Wichterich, M., Assent, I., Philipp, K. & Seidl, T. (2008). Efficient EMD-based Similarity Search in Multimedia Databases via Flexible Dimensionality Reduction. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data (pp. 199-212) https://doi.org/10.1145/1376616.1376639

Assent, I., Wichterich, M., Meisen, T. & Seidl, T. (2008). Efficient Similarity Search Using the Earth Mover's Distance for Large Multimedia Databases. In IEEE 24th International Conference on Data Engineering, 2008. ICDE 2008. (pp. 307-316) https://doi.org/10.1109/ICDE.2008.4497439

Assent, I., Krieger, R. & Seidl, T. (2008). Evolutionäre Clustering-Algorithmen: Bionik-Methoden für Knowledge Discovery in Datenbanken. R W T H - Themen, (1). http://www.rwth-aachen.de/global/show_document.asp?id=aaaaaaaaaabfhbu

Assent, I., Krieger, R., Müller, E., ller, E. & Seidl, T. (2008). INSCY: indexing subspace clusters with in-process-removal of redundancy. In Eighth IEEE International Conference on Data Mining, 2008. ICDM '08. (pp. 719-724) https://doi.org/10.1109/ICDM.2008.46

Müller, E., Assent, I., Krieger, R., Jansen, T. & Seidl, T. (2008). Morpheus: Interactive Exploration of Subspace Clustering. In Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 1089-1092) https://doi.org/10.1145/1401890.1402026

Seidl, T., Müller, E., Assent, I. & Steinhausen, U. (2008). Outlier detection and ranking based on subspace clustering. Dagstuhl Seminar Proceedings. http://www.dagstuhl.de/Materials/index.en.phtml?08421

Müller, E., Assent, I., Steinhausen, U. & Seidl, T. (2008). OutRank: ranking outliers in high dimensional data. In IEEE 24th International Conference on Data Engineering Workshop, 2008. ICDEW 2008 (pp. 600-603) https://doi.org/10.1109/ICDEW.2008.4498387

Assent, I., Krieger, R., Afschari, F. & Seidl, T. (2008). The TS-Tree: Efficient Time Series Search and Retrieval. In Proceedings of the 11th international conference on Extending database technology: Advances in database technology (Vol. 261, pp. 252-263) https://doi.org/10.1145/1353343.1353376

Displaying results 201 to 242 out of 242

Revised 01.09.2025

Sofia Hedegaard Rasmussen