Bilyana Taneva

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Gerhard WeikumProfessor of Computer Science, Max Planck Institute for Informatics, Saarland Informatics CampusVerified email at mpi-inf.mpg.de
Hagen FürstenauSenior Manager Machine Learning, AmazonVerified email at amazon.com
Johannes HoffartChief Architect for Natural Language Processing and Knowledge Graphs at SAPVerified email at hoffart.ai
Marc SpaniolUniversité de Caen NormandieVerified email at unicaen.fr
Ilaria BordinoResearch Scientist, Unicredit R&DVerified email at acm.org
Mohamed Amir YosefMax-Planck-Institute for InformaticsVerified email at mpi-inf.mpg.de
Mouna KACIMIFree University of Bozen-BolzanoVerified email at unibz.it
Tao ChengPinterest IncVerified email at pinterest.com
Peter ZollikerEmpaVerified email at empa.ch
Patrick NicholsonShutterstockVerified email at uwaterloo.ca
Preethi LahotiPhD student @ Max Planck Institute for InformaticsVerified email at mpi-inf.mpg.de
Deepak AjwaniUniversity College DublinVerified email at ucd.ie

Bilyana Taneva

Thomson Reuters

Verified email at thomsonreuters.com

Data Mining Information Retrieval NLP


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Robust disambiguation of named entities in text J Hoffart, MA Yosef, I Bordino, H Fürstenau, M Pinkal, M Spaniol, ... Proceedings of the 2011 conference on empirical methods in natural language …, 2011	1132	2011
Gathering and ranking photos of named entities with high precision, high recall, and diversity B Taneva, M Kacimi, G Weikum Proceedings of the third ACM international conference on Web search and data …, 2010	58	2010
Mining acronym expansions and their meanings using query click log B Taneva, T Cheng, K Chakrabarti, Y He Proceedings of the 22nd international conference on World Wide Web, 1261-1272, 2013	22	2013
Gem-based entity-knowledge maintenance B Taneva, G Weikum Proceedings of the 22nd ACM international conference on Information …, 2013	17	2013
Finding images of difficult entities in the long tail B Taneva, M Kacimi, G Weikum Proceedings of the 20th ACM international conference on Information and …, 2011	10	2011
Choice based conjoint analysis: Discrete choice models vs. direct regression B Taneva, J Giesen, P Zolliker, K Mueller 1st ECML/PKDD-Workshop on Preference Learning (PL), 2008	6	2008
Efficient Set Intersection Counting Algorithm for Text Similarity Measures. P Lahoti, PK Nicholson, B Taneva ALENEX, 146-158, 2017	5	2017
Finding images of rare and ambiguous entities B Taneva, M Kacimi El Hassani, G Weikum Max-Planck-Institut für Informatik, 2011	5	2011
Choice-Based Conjoint Analysis: Classification vs. Discrete Choice Models J Giesen, K Mueller, B Taneva, P Zolliker Preference Learning, 297-315, 2011	3	2011
Conjoint Analysis: A Tool for Preference Analysis B Taneva Master's Thesis, Saarland University, 2008	2	2008
ANNOTATE: orgANizing uNstructured cOntenTs viA Topic labEls D Ajwani, B Taneva, S Dutta, PK Nicholson, G Heyrani-Nobari, A Sala 2018 IEEE International Conference on Big Data (Big Data), 1699-1708, 2018	1	2018
On-topic Cover Stories from News Archives C Schulte, B Taneva, G Weikum European Conference on Information Retrieval, 37-42, 2015		2015
Automatic population of knowledge bases with multimodal data about named entities B Taneva PhD Thesis, Saarland University, 2013		2013

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