Serelex: search and visualization of semantically related words

Authors:
Alexander Panchenko;Pavel Romanov;Olga Morozova;Hubert Naets;Andrey Philippovich;Alexey Romanov;Cédrick Fairon
Affiliations:
Université catholique de Louvain, Louvain-la-Neuve, Belgium,Bauman Moscow State Technical University, Moscow, Russia;Bauman Moscow State Technical University, Moscow, Russia;Université catholique de Louvain, Louvain-la-Neuve, Belgium;Université catholique de Louvain, Louvain-la-Neuve, Belgium;Bauman Moscow State Technical University, Moscow, Russia;Bauman Moscow State Technical University, Moscow, Russia;Université catholique de Louvain, Louvain-la-Neuve, Belgium
Venue:
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Year:
2013

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Abstract

We present Serelex, a system that provides, given a query in English, a list of semantically related words. The terms are ranked according to an original semantic similarity measure learnt from a huge corpus. The system performs comparably to dictionary-based baselines, but does not require any semantic resource such as WordNet. Our study shows that users are completely satisfied with 70% of the query results.