Semantic Relatedness Using Salient Semantic Analysis
Abstract
This paper introduces a novel method for measuring semantic relatedness using semantic profiles constructed from salient encyclopedic features. The model is built on the notion that the meaning of a word can be characterized by the salient concepts found in its immediate context. In addition to being computationally efficient, the new model has superior performance and remarkable consistency when compared to both knowledge-based and corpus-based state-of-the-art semantic relatedness models.
Cite
Text
Hassan and Mihalcea. "Semantic Relatedness Using Salient Semantic Analysis." AAAI Conference on Artificial Intelligence, 2011. doi:10.1609/AAAI.V25I1.7971Markdown
[Hassan and Mihalcea. "Semantic Relatedness Using Salient Semantic Analysis." AAAI Conference on Artificial Intelligence, 2011.](https://mlanthology.org/aaai/2011/hassan2011aaai-semantic/) doi:10.1609/AAAI.V25I1.7971BibTeX
@inproceedings{hassan2011aaai-semantic,
title = {{Semantic Relatedness Using Salient Semantic Analysis}},
author = {Hassan, Samer and Mihalcea, Rada},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2011},
pages = {884-889},
doi = {10.1609/AAAI.V25I1.7971},
url = {https://mlanthology.org/aaai/2011/hassan2011aaai-semantic/}
}