A New Sentence Similarity Method Based on a Three-Layer Sentence Representation
Rafael Ferreira, Rafael Dueire Lins, Fred Freitas, Bruno Tenório Ávila, Steven J. Simske, Marcelo Riss · 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) · 2014
Sentence similarity methods are used to assess the degree of likelihood between phrases. Many natural language applications such as text summarization, information retrieval, text categorization, and machine translation employ measures of sentence similarity. The existing approaches for this problem represent sentences as vectors of bag of words or the syntactic information of the words in the phrase. The likelihood between phrases is calculated by composing the similarity between the words in the sentences. Such schemes do not address two important concerns in the area, however: the semantic problem and the word order. This paper proposes a new sentence similarity measure that attempts to address such problems by taking into account the lexical, syntactic, and semantic analysis of sentences. The new similarity measure proposed outperforms the state of the art systems in around 6%, when tested using a standard and publically available dataset.