Publications

Contribution to book anthology

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., 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

Bouros, P., Assent, I., Jeppesen, J. H. & Toftegaard, T. S. (2019). Processing satellite imagery for decision-making in precision agriculture. In P. Papotti (Ed.), Proceedings of the Workshops of the EDBT/ICDT 2019 Joint Conference (EDBT/ICDT 2019) Sun Site Central Europe. https://bigvis.imsi.athenarc.gr/bigvis2019/papers/BigVis_2019_paper_4.pdf

Bøgh, K. S., Assent, I. & Magnani, M. (2013). Efficient GPU-based skyline computation. In R. Johnson & A. Kemper (Eds.), Proceedings of the Ninth International Workshop on Data Management on New Hardware , DaMoN '13 [5] Association for Computing Machinery. https://doi.org/10.1145/2485278.2485283

Bøgh, K. S., Chester, S., Sidlauskas, D. & Assent, I. (2014). Hashcube: A Data Structure for Space- and Query-Efficient Skycube Compression. In J. Li & X. S. Wang (Eds.), Proceedings of The 23rd ACM International Conference on Information and Knowledge Management (CIKM 2014) (pp. 1767-1770). Association for Computing Machinery. https://doi.org/10.1145/2661829.2661891

Bøgh, K. S., Chester, S., Sidlauskas, D. & Assent, I. (2017). Template Skycube Algorithms for Heterogeneous Parallelism on Multicore and GPU Architectures. In Proceedings of the 2017 International Conference on Management of Data, (ACM SIGMOD) (pp. 447-462). Association for Computing Machinery. https://doi.org/10.1145/3035918.3035962

Campos, G. O., Zimek, A., Sander, J., Campello, R. J. G. B., Micenkova, B., Schubert, E., Assent, I. & Houle, M. E. (2016). On the Evaluation of Outlier Detection: Measures, Datasets, and an Empirical Study Continued. In R. Krestel, D. Mottin & E. Müller (Eds.), Proceedings of the Conference "Lernen, Wissen, Daten, Analysen" (Vol. 1670, pp. 1). ceur workshop proceedings. CEUR Workshop Proceedings Vol. 1670 http://ceur-ws.org/Vol-1670/paper-55.pdf

Chester, S. & Assent, I. (2015). Explanations for Skyline Query Results. In International Conference on Extending Database Technology (EDBT 2015) (pp. 349-360). openproceedings.org. https://doi.org/10.5441/002/edbt.2015.31

Chester, S., Mortensen, M. L. & Assent, I. (2014). On the Suitability of Skyline Queries for Data Exploration. In K. S. Candan et al. (Ed.), Proceedings of the Workshops of the EDBT/ICDT 2014 Joint Conference: 1st International Workshop on Exploratory Search in Databases and the Web (ExploreDB 2014) (pp. 161-166). CEUR-WS.org. CEUR Workshop Proceedings http://ceur-ws.org/Vol-1133/paper-27.pdf

Chester, S., Sidlauskas, D., Assent, I. & Bøgh, K. S. (2015). Scalable Parallelization of Skyline Computation for Multi-core Processors. In 31st IEEE International Conference on Data Engineering (ICDE 2015) (pp. 1083 - 1094). IEEE Computer Society Press. https://doi.org/10.1109/ICDE.2015.7113358

Ciosici, M. R. & Assent, I. (2019). Abbreviation Explorer - an interactive system for pre-evaluation of Unsupervised Abbreviation Disambiguation. In W. Ammar, A. Louis & N. Mostafazadeh (Eds.), Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations) Association for Computational Linguistics. https://aclweb.org/anthology/papers/N/N19/N19-4001/

Ciosici, M. R., Assent, I. & Derczynski, L. (2020). Accelerated High-Quality Mutual-Information Based Word Clustering. In Proceedings of The 12th Language Resources and Evaluation Conference (pp. 2491-2496). European Language Resources Association. https://www.aclweb.org/anthology/2020.lrec-1.303

Ciosici, M. R., Derczynski, L. & Assent, I. (2019). Quantifying the morphosyntactic content of Brown Clusters. In J. Burstein, C. Doran & T. Solorio (Eds.), Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Vol. 1, pp. 1541-1550). Association for Computational Linguistics. https://aclweb.org/anthology/papers/N/N19/N19-1157/

Dang, X-H., Assent, I., Ng, R. T., Zimek, A. & Schubert, E. (2014). Discriminative features for identifying and interpreting outliers. In Proceedings, 2014 IEEE 30th International Conference on Data Engineering (ICDE) (pp. 88-99). [6816642] IEEE Computer Society Press. https://doi.org/10.1109/ICDE.2014.6816642

Dang, X-H., Micenková, B., Assent, I. & Ng, R. T. (2013). Local Outlier Detection with Interpretation. In H. Blockeel, K. Kersting , S. Nijssen & F. Železný (Eds.), Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part III (pp. 304-320 ). Springer VS. Lecture Notes in Computer Science Vol. 8190 https://doi.org/10.1007/978-3-642-40994-3_20

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

Dang, X-H., Micenková, B., Assent, I. & Ng, R. T. (2013). Outlier Detection with Space Transformation and Spectral Analysis. In C. Kamath, J. Dy, Z. Obradovic, J. Ghosh, S. Parthasarathy & Z-H. Zhou (Eds.), Proceedings of the 2013 SIAM International Conference on Data Mining, SDM (pp. 225-233). Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611972832.25

Enni, S. & Assent, I. (2018). Using Balancing Terms to Avoid Discrimination in Classification. In 2018 IEEE International Conference on Data Mining (ICDM) (pp. 947-952). IEEE Press. https://doi.org/10.1109/ICDM.2018.00116

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

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

Kristensen, J., Mai, S. T., Assent, I., Jacobsen, J., Vo, B. & Le, A. (2017). Interactive exploration of subspace clusters for high dimensional data. In D. Benslimane, E. Damiani, W. I. Grosky, A. Hameurlain, A. Sheth & R. R. Wagner (Eds.), Database and Expert Systems Applications - 28th International Conference, DEXA 2017, Proceedings (Vol. 10438 LNCS, pp. 327-342). Springer VS. Lecture Notes in Computer Science Vol. 10438 https://doi.org/10.1007/978-3-319-64468-4_25

Ma, M., Yang, B. & Jensen, C. S. (2014). Enabling Time-Dependent Uncertain Eco-Weights For Road Networks. In M. A. Nascimento & M. Renz (Eds.), Proceedings of the 1st International ACM Workshop on Managing and Mining Enriched Geo-spatial Data: GeoRich 2014 [1] Association for Computing Machinery. https://doi.org/10.1145/2619112.2619113

Magnani, M. & Assent, I. (2013). From stars to galaxies: skyline queries on aggregate data. In G. Guerrini & N. W. . Paton (Eds.), International Conference on Extending Database Technology (pp. 477-488 ). Association for Computing Machinery. https://doi.org/10.1145/2452376.2452432

Mai, S. T., Dieu, M. S., Assent, I., Jacobsen, J., Kristensen, J. & Birk, M. (2017). Scalable and interactive graph clustering algorithm on multicore CPUs. In 2017 IEEE 33rd International Conference on Data Engineering (ICDE) (pp. 349-360). IEEE Computer Society Press. Proceedings of the International Conference on Data Engineering https://doi.org/10.1109/ICDE.2017.94

Micenková, B., Ng, R. T., Dang, X-H. & Assent, I. (2013). Explaining outliers by subspace separability. In H. Xiong, G. Karypis, B. Thuraisingham, D. Cook & X. Wu (Eds.), Proceedings, IEEE 13th International Conference on Data Mining (ICDM 2013) (pp. 518 - 527 ). IEEE Press. IEEE International Conference on Data Mining (ICDM'13) http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6724379

Mortensen, M. L., Chester, S., Assent, I. & Magnani, M. (2015). Efficient caching for constrained skyline queries. In International Conference on Extending Database Technology (EDBT 2015) (pp. 337-348). openproceedings.org. https://doi.org/10.5441/002/edbt.2015.30

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

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..

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

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

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., 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

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

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

Neerbek, J., Eskildsen, M., Dolog, P. & Assent, I. (2020). A real-world data resource of complex sensitive sentences based on documents from the Monsanto trial. In N. Calzolari, F. Bechet, P. Blache, K. Choukri, C. Cieri, T. Declerck, S. Goggi, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk & S. Piperidis (Eds.), LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings (pp. 1258-1267). European Language Resources Association.

Neerbek, J., Assent, I. & Dolog, P. (2018). Detecting Complex Sensitive Information via Phrase Structure in Recursive Neural Networks. In D. Phung, V. S. Tseng, G. I. Webb, B. Ho, M. Ganji & L. Rashidi (Eds.), Advances in Knowledge Discovery and Data Mining: PAKDD '18 (Vol. 10939, pp. 373-385). Springer VS. Lecture Notes in Computer Science (LNCS) No. 10939 https://doi.org/10.1007/978-3-319-93040-4_30

Neerbek, J., Dolog, P. & Assent, I. (2019). Selective Training: A Strategy for Fast Backpropagation on Sentence Embeddings. In Q. Yang, M-L. Zhang, Z. Gong, S-J. Huang & Z-H. Zhou (Eds.), Advances in Knowledge Discovery and Data Mining - 23rd Pacific-Asia Conference, PAKDD 2019, Proceedings: PAKDD '19 (pp. 40-53). Springer. https://doi.org/10.1007/978-3-030-16142-2_4

Neerbek, J., Assent, I. & Dolog, P. (2017). TABOO: Detecting unstructured sensitive information using recursive neural networks. In Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017 (pp. 1399-1400). [7930091] IEEE Computer Society Press. Proceedings of the International Conference on Data Engineering Vol. 33 https://doi.org/10.1109/ICDE.2017.195

Skovsgaard, A., Sidlauskas, D. & Jensen, C. S. (2014). A Clustering Approach to the Discovery of Points of Interest from Geo-Tagged Microblog Posts. In J. E. Guerrero (Ed.), 15th IEEE International Conference on Mobile Data Management (MDM), 2014 : Proceedings (pp. 178-189 (vol. 1)). IEEE Computer Society Press. https://doi.org/10.1109/MDM.2014.28

Skovsgaard, A. & Jensen, C. S. (2014). Top-k point of interest retrieval using standard indexes. In Y. Huang & M. Schneider (Eds.), Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL '14 (pp. 173-182 ). Association for Computing Machinery. https://doi.org/10.1145/2666310.2666399

Thai Son, M., Assent, I., Birk, M. S., Dieu, M. S., Jacobsen, J., Kristensen, J., Rahman, H., Thirumuruganathan, S., Das, G., Omidvar-Tehrani, B., Borromeo, R. M., Chen, L., Miller, R., Benouaret, I., Amer-Yahia, S. & Roy, S. B. (2019). An Efficient Greedy Algorithm for Sequence Recommendation. In DEXA 2019: International Conference on Database and Expert Systems Applications, Aug 2019, Linz, Austria (pp. 314-326) https://doi.org/10.1007/978-3-030-27615-7_24

Thai Son, M., Assent, I. & Storgaard, M. (2016). AnyDBC: An efficient anytime density-based clustering algorithm for very large complex datasets. In KDD 2016 - Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 1025-1034). Association for Computing Machinery. https://doi.org/10.1145/2939672.2939750

Thai Son, M., Assent, I. & Le, A. T. (2016). Anytime OPTICS: An efficient approach for hierarchical density-based clustering. In S. B. Navathe, W. Wu, S. Shekhar, X. Du, X. Sean Wang & H. Xiong (Eds.), Database Systems for Advanced Applications - 21st International Conference, DASFAA 2016, Proceedings (Vol. 9642, pp. 164-179). Springer VS. Lecture Notes in Computer Science (LNCS) Vol. 9642 https://doi.org/10.1007/978-3-319-32025-0_11

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

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