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- W1041536176 abstract "This paper introduces a method for assessing the semantic similarity between sentences, which relies on the assumption that the meaning of a sentence is captured by its syntactic constituents and the dependencies between them. We obtain both the constituents and their dependencies from a syntactic parser. Our algorithm considers that two sentences have the same meaning if it can find a good mapping between their chunks and also if the chunk dependencies in one text are preserved in the other. Moreover, the algorithm takes into account that every chunk has a different importance with respect to the overall meaning of a sentence, which is computed based on the information content of the words in the chunk. The experiments conducted on a well-known paraphrase data set show that the performance of our method is comparable to state of the art." @default.
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- W1041536176 date "2014-01-01" @default.
- W1041536176 modified "2023-10-17" @default.
- W1041536176 title "A Sentence Similarity Method Based on Chunking and Information Content" @default.
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- W1041536176 doi "https://doi.org/10.1007/978-3-642-54906-9_36" @default.
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