| 书目名称 | Semantic Similarity from Natural Language and Ontology Analysis | | 编辑 | Sébastien Harispe,Sylvie Ranwez,Jacky Montmain | | 视频video | | | 丛书名称 | Synthesis Lectures on Human Language Technologies | | 图书封面 |  | | 描述 | Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning or decision processes). Central to this quest is to give machines the ability to estimate the likeness or similarity between things in the way human beings estimate the similarity between stimuli. In this context, this book focuses on semantic measures: approaches designed for comparing semantic entities such as units of language, e.g. words, sentences, or concepts and instances defined into knowledge bases. The aim of these measures is to assess the similarity or relatedness of such semantic entities by taking into account their semantics, i.e. their meaning---intuitively, the words tea and coffee, which both refer to stimulating beverage, will be estimated to be more semantically similar than the words toffee (confection) and coffee, despite that the last pair has a higher syntactic similarity. The two state-of-the-art approaches for estimating and quantifying semantic similarities/relatedness of semantic entities are presented in detail: the first one relies on corpo | | 出版日期 | Book 2015 | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-02156-5 | | isbn_softcover | 978-3-031-01028-6 | | isbn_ebook | 978-3-031-02156-5Series ISSN 1947-4040 Series E-ISSN 1947-4059 | | issn_series | 1947-4040 | | copyright | Springer Nature Switzerland AG 2015 |
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发表于 2025-3-21 18:05:47
