From senses to texts: an all-in-one graph-based approach for measuring semantic similarity
From MaRDI portal
Publication:896432
DOI10.1016/j.artint.2015.07.005zbMath1346.68227OpenAlexW2192710297MaRDI QIDQ896432
Roberto Navigli, Mohammad Taher Pilehvar
Publication date: 9 December 2015
Published in: Artificial Intelligence (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.artint.2015.07.005
lexical semanticssemantic similaritycoarsening WordNet sense inventorypersonalized PageRanksemantic networksSemantic Textual Similarityword similaritywordnet graph
Related Items (2)
\textsc{Nasari}: integrating explicit knowledge and corpus statistics for a multilingual representation of concepts and entities ⋮ Semantic Similarity Between Adjectives and Adverbs—The Introduction of a New Measure
Uses Software
Cites Work
- BabelNet: the automatic construction, evaluation and application of a wide-coverage multilingual semantic network
- Collaboratively built semi-structured content and artificial intelligence: the story so far
- Computing text semantic relatedness using the contents and links of a hypertext encyclopedia
- A bit-string longest-common-subsequence algorithm
- Co-occurrence Retrieval: A Flexible Framework for Lexical Distributional Similarity
- Evaluating WordNet-based Measures of Lexical Semantic Relatedness
- Dependency-Based Construction of Semantic Space Models
- A Survey of Paraphrasing and Textual Entailment Methods
- A vector space model for automatic indexing
- 10.1162/153244303322533223
- 10.1162/jmlr.2003.3.4-5.993
- Text Relatedness Based on a Word Thesaurus
- From Frequency to Meaning: Vector Space Models of Semantics
- Unsupervised learning by probabilistic latent semantic analysis
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: From senses to texts: an all-in-one graph-based approach for measuring semantic similarity