RUFINO Semantic Word Similarity System
A RUFINO Semantic Word Similarity System is a Multilingual and Cross-lingual Semantic Word Similarity System that is based on pointwise mutual information approach, on Jaccard distance, and on Polyglot's word embeddings.
- Context:
- It was the 4rd best performing semantic word similarity system in the global ranking of SemEval-2017 Task 2 with a score of 0.555.
- It was built by Jimenez et al. (2017) inspired by the Swadesh's list.
- Example(s):
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- Counter-Example(s):
- See: SemEval, SemEval-2017 Task, Semantic Word Similarity Benchmark Task, Semantic Textual Similarity Benchmark Task, Semantic Similarity Modelling System, Semantic Similarity Measure, Semantic Relatedness Measure.
References
2017a
- (Camacho-Collados et al., 2017) ⇒ Jose Camacho-Collados, Mohammad Taher Pilehvar, Nigel Collier, and Roberto Navigli. (2017). “SemEval-2017 Task 2: Multilingual and Cross-lingual Semantic Word Similarity.” In: Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval@ACL 2017).
- QUOTE: RUFINO, which also made use of the Wikipedia corpus only, attained the third overall position. The system exploits PMI and an association measure to capture second-order relations between words based on the Jaccard distance (...).
2017b
- (Jimenez et al., 2017) ⇒ Sergio Jimenez, George Duenas, Lorena Gaitan, and Jorge Segura. (2017). “RUFINO at SemEval-2017 Task 2: Cross-lingual Lexical Similarity by Extending PMI and Word Embeddings Systems with a Swadesh's-like List.” In: Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval@ACL 2017).
- QUOTE: Our goal, is to build cross-lingual systems starting from monolingual systems connected across languages by the proposed list of concepts. Figure 1 provides a general overview of the general architecture of the proposed system.
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