@inproceedings{0a33fa6f30e54c3e94b598d2cda1c388,
title = "Combining POS tagging, Lucene search and similarity metrics for entity linking",
abstract = "Entity linking is to detect proper nouns or concrete concepts (a.k.a mentions) from documents, and to map them to the corresponding entries in a given knowledge base. In this paper, we propose an entity linking framework POSLS consisting of three components: mention detection, candidate selection and entity disambiguation. First, we use part of speech tagging and English syntactic rules to detect mentions. We then choose candidates with Lucene search. Finally, we identify the best matchings with a similarity based disambiguation method. Experimental results show that our approach has an acceptable accuracy.",
keywords = "Entity Linking, Lucene Search, Mention Detection, POS Tagging, Similarity Metrics",
author = "Shujuan Zhao and Chune Li and Shuai Ma and Tiejun Ma and Dianfu Ma",
year = "2013",
doi = "10.1007/978-3-642-41230-1\_44",
language = "英语",
isbn = "9783642412295",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 1",
pages = "503--509",
booktitle = "Web Information Systems Engineering, WISE 2013 - 14th International Conference, Proceedings",
edition = "PART 1",
note = "14th International Conference on Web Information Systems Engineering, WISE 2013 ; Conference date: 13-10-2013 Through 15-10-2013",
}