Efficient Searching Top-k Semantic Similar Words
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 2373-2377.
Abstract
Measuring the semantic meaning between words is an important issue because it is the basis for many applications, such as word sense disambiguation, document summarization, and so forth. Although it has been explored for several decades, most of the studies focus on improving the effectiveness of the problem, i.e., precision and recall. In this paper, we propose to address the efficiency issue, that given a collection of words, how to efficiently discover the top-k most semantic similar words to the query. This issue is very important for real applications yet the existing state-of-the-art strategies cannot satisfy users with reasonable performance. Efficient strategies on searching top-k semantic similar words are proposed. We provide an extensive comparative experimental evaluation demonstrating the advantages of the introduced strategies over the state-of-the-art approaches.
@inproceedings{ijcai2011p395,
title = {Efficient Searching Top-k Semantic Similar Words},
author = {Yang, Zhenglu and Kitsuregawa, Masaru},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {2373--2377},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-395},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-395},
}
TY - CPAPER TI - Efficient Searching Top-k Semantic Similar Words AU - Yang, Zhenglu AU - Kitsuregawa, Masaru T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 2373 EP - 2377 DO - 10.5591/978-1-57735-516-8/IJCAI11-395 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-395 ER -Copied
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