Shay Hummel


2017

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Unsupervised corpus–wide claim detection
Ran Levy | Shai Gretz | Benjamin Sznajder | Shay Hummel | Ranit Aharonov | Noam Slonim
Proceedings of the 4th Workshop on Argument Mining

Automatic claim detection is a fundamental argument mining task that aims to automatically mine claims regarding a topic of consideration. Previous works on mining argumentative content have assumed that a set of relevant documents is given in advance. Here, we present a first corpus– wide claim detection framework, that can be directly applied to massive corpora. Using simple and intuitive empirical observations, we derive a claim sentence query by which we are able to directly retrieve sentences in which the prior probability to include topic-relevant claims is greatly enhanced. Next, we employ simple heuristics to rank the sentences, leading to an unsupervised corpus–wide claim detection system, with precision that outperforms previously reported results on the task of claim detection given relevant documents and labeled data.

2015

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TR9856: A Multi-word Term Relatedness Benchmark
Ran Levy | Liat Ein-Dor | Shay Hummel | Ruty Rinott | Noam Slonim
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

2014

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Claims on demand – an initial demonstration of a system for automatic detection and polarity identification of context dependent claims in massive corpora
Noam Slonim | Ehud Aharoni | Carlos Alzate | Roy Bar-Haim | Yonatan Bilu | Lena Dankin | Iris Eiron | Daniel Hershcovich | Shay Hummel | Mitesh Khapra | Tamar Lavee | Ran Levy | Paul Matchen | Anatoly Polnarov | Vikas Raykar | Ruty Rinott | Amrita Saha | Naama Zwerdling | David Konopnicki | Dan Gutfreund
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: System Demonstrations