R
Roi Reichart
Researcher at Technion – Israel Institute of Technology
Publications - 165
Citations - 6599
Roi Reichart is an academic researcher from Technion – Israel Institute of Technology. The author has contributed to research in topics: Computer science & Parsing. The author has an hindex of 34, co-authored 148 publications receiving 5302 citations. Previous affiliations of Roi Reichart include University of Cambridge & Hebrew University of Jerusalem.
Papers
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Journal ArticleDOI
Simlex-999: Evaluating semantic models with genuine similarity estimation
TL;DR: SimLex-999 is presented, a gold standard resource for evaluating distributional semantic models that improves on existing resources in several important ways, and explicitly quantifies similarity rather than association or relatedness so that pairs of entities that are associated but not actually similar have a low rating.
Posted Content
SimLex-999: Evaluating Semantic Models with (Genuine) Similarity Estimation
TL;DR: SimLex-999 as mentioned in this paper is a gold standard resource for evaluating distributional semantic models that improves on existing resources in several important ways, such as quantifying similarity rather than association or relatedness, so that pairs of entities that are associated but not actually similar have a low rating.
Proceedings Article
Modeling the Detection of Textual Cyberbullying
TL;DR: This work decomposes the overall detection problem into detection of sensitive topics, lending itself into text classification sub-problems and shows that the detection of textual cyberbullying can be tackled by building individual topic-sensitive classifiers.
Proceedings ArticleDOI
The Hitchhiker’s Guide to Testing Statistical Significance in Natural Language Processing
TL;DR: This opinion/ theoretical paper proposes a simple practical protocol for statistical significance test selection in NLP setups and accompanies this protocol with a brief survey of the most relevant tests.
Journal ArticleDOI
Semantic Specialization of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints
Nikola Mrksic,Nikola Mrksic,Ivan Vulić,Diarmuid Ó Séaghdha,Ira Leviant,Roi Reichart,Milica Gasic,Anna Korhonen,Steve Young,Steve Young +9 more
TL;DR: This paper proposed an algorithm for improving the semantic quality of word vectors by injecting constraints extracted from lexical resources. But the method can make use of existing cross-lingual lexicons to construct high-quality vector spaces for a plethora of different languages, facilitating semantic transfer from high-to lower-resource ones.