Оценка Сходства

This paper presents a technique for discover- ing translationally equivalent texts. It is com- prised of the application of a matching algo- rithm at two different levels of analysis and …...

Probabilistic models have been effective in re- solving prepositional phrase attachment am- biguity, but sparse data remains a significant problem. We propose a solution based on similarity-based smoothing, where the …...

We propose an automatic machine translation (MT) evaluation metric that calculates a sim- ilarity score (based on precision and recall) of a pair of sentences. Unlike most metrics, we compute …...

This paper presents a novel approach for building adaptive similarity functions based on cardinality us- ing machine learning. Unlike current approaches that build feature sets using similarity scores, we have …...

This paper deals with knowledge-based text processing which aims at an intuitive notion of textual similarity. Entities and relations rel- evant for a particular domain are identified and disambiguated by …...

We present extensive evaluations compar- ing the performance of taxonomy-based and corpus-based approaches on SimLex- 999. The results confirm our hypothesis that taxonomy-based approaches are more suitable to identify similarity. …...

We present a description of the system submit- ted to the Semantic Textual Similarity (STS) shared task at SemEval 2016. The task is to assess the degree to which two …...

AbstractMost conventional sentence similarity methods only focus on similar parts of two input sentences, and simply ignore the dissimilar parts, which usually give us some clues and semantic meanings about …...

AbstractIn this paper we present the Tren-toTeam system which participated to thetask 3 at SemEval-2017 (Nakov et al.,2017).We concentrated our work onapplying Grice Maxims(used in manystate-of-the-art Machine learning applica-tions(Vogel et …...

Human perception on the singing voice differs with the factors of the singing voice and the subjects. On one hand, the background knowledge influences the understanding of voice for each …...