Balázs Hidasi

Data Mining Researcher

Publications

Last update: 19.09.2016

Journal papers

2015

Balázs Hidasi, Domonkos Tikk: Speeding up ALS learning via approximate methods for context-aware recommendations
Knowledge and Information Systems (KAIS). July 2015.
[WWW] [PDF - Full Text]

Balázs Hidasi, Domonkos Tikk: General Factorization Framework for Context-aware Recommendations
Data Mining and Knowledge Discovery (DMKD). May 2015.
[WWW] [PDF - Full Text]

2014

Balázs Hidasi: Factorization models for context-aware recommendations
Infocommunications Journal. Volume VI. Issue 4. Pages 27-34. December 2014.
[PDF - Full Text]

2013

Balázs Hidasi, Domonkos Tikk: Initializing Matrix Factorization Methods on Implicit Feedback Databases
Journal of Universal Computer Science (J.UCS). Volume 19. Issue 12. Pages 1834-1853. October 2013.
[WWW - Full Text]

Conference papers

2016

Balázs Hidasi, Massimo Quadrana, Alexandros Karatzoglou, Domonkos Tikk: Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations
10th ACM Conference on Recommender Systems, RecSys 2016. Boston, USA, 15-19 September, 2016.
[WWW] [Full text] [Slides] [Slides - SlideShare]

Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, Domonkos Tikk: Session-based recommendations with recurrent neural networks
International Conference on Learning Representations (ICLR). San Juan, Puerto Rico, 2-4 May, 2016.
[WWW - Full Text] [Poster] [Algorithm]

2015

Balázs Hidasi: Context-aware preference modeling with factorization
Doctoral Symposium at RecSys'15. Vienna, Austria, September 2015.
[WWW] [PDF - Full text] [Slides] [SlideShare] [Poster]

2012

Balázs Hidasi, Domonkos Tikk: Fast ALS-based tensor factorization for context-aware recommendation from implicit feedback
at ECML/PKDD. Bristol, United Kingdom, September 2012.
[WWW] [PDF - Full text] [Slides] [SlideShare] [Poster]

2011

Balázs Hidasi, Csaba Gáspár-Papanek: ShiftTree: An Interpretable Model-Based Approach for Time Series Classification
at ECML/PKDD. Athens, Greece, September 2011.
[WWW] [PDF - Full text] [Slides] [SlideShare] [Poster]
*Huge thanks to Google for covering a significant part of my conference related expenses through their Eastern European Travel Grant program!

Workshop papers

2015

Benjamin Kille, Fabian Abel, Balázs Hidasi, Sahin Albayrak: Using interaction signals for job recommendations
Workshop on Situation Recognition by Mining Temporal Information SIREMTI2015. Berlin, Germany, November 13, 2015.
[WWW] [PDF - Full text] [SlideShare]

2014

Balázs Hidasi, Domonkos Tikk: Approximate modeling of continuous context in factorization algorithms
at 4th Workshop on Context-awareness in Retrieval and Recommendation. Amsterdam, The Netherlands, April 2014.
[WWW] [PDF - Full text] [Slides] [SlideShare]

2013

Balázs Hidasi, Domonkos Tikk: Context-aware item-to-item recommendation within the factorization framework
at 3rd Workshop on Context-awareness in Retrieval and Recommendation. Rome, Italy, February 2013.
[WWW] [PDF - Full text] [Slides] [SlideShare]

2012

Dávid Zibriczky, Balázs Hidasi, Zoltán Petres, Domonkos Tikk: Personalized recommendation of linear content on interactive TV platforms: beating the cold start and noisy implicit user feedback
at Workshop on TV and multimedia personalization (TVMMP). Montreal, Canada, July 2012.
[WWW - Full Text]

Balázs Hidasi, Domonkos Tikk: Enhancing matrix factorization through initialization for implicit feedback databases
at 2nd Workshop on Context-awareness in Retrieval and Recommendation. Lisbon, Portugal, February 2012.
[WWW] [PDF - Full text] [Slides] [SlideShare]

2009

Balázs Hidasi: Újfajta, automatikus, döntési fa alapú adatbányászati módszer idősorok osztályozására
(ENG: Novel, automatic, decision-tree based datamining method for time series classification).

at Conference of Graduating Students. Budapest, Hungary, May 2009.
Awards: Best presentation award
[PDF - Full text - HUN] [Slides - HUN] [SlideShare - HUN]

Dissertations

2016

Balázs Hidasi: Context-aware factorization methods for implicit feedback based recommendation problems
Ph.D. Thesis
[PDF - Full text - ENG] [Slides - HUN] [SlideShare - HUN] [PDF - Booklet - ENG][PDF - Booklet - HUN]

2011

Balázs Hidasi: Modell alapú idősor-osztályozó fejlesztése és kiterjesztése
(ENG: Developement and extension of model-based time series classifier).

M.Sc. Thesis
Grade: Excellent
[PDF - Full text - HUN] [Slides - Hun] [SlideShare - HUN]

2008

Balázs Hidasi: Újfajta, automatikus, döntési fa alapú adatbányászati módszer idősorok osztályozására
(ENG: Novel, automatic, decision-tree based datamining method for time series classification).

B.Sc. Thesis
Grade: Excellent
Awards: 2nd place award by the Scientific Association for Infocommunications Hungary (HTE)

Balázs Hidasi: Az idősor-osztályozás problémájának megoldása új, döntési fa alapú adatbányászati algoritmussal
(ENG: Solving the time series classification task with novel, decision-tree based datamining algorithm).

Dissertation for the Students' Scientific Conference
Awards: 1st place (Faculty), 3rd place (National)