Abstract : Text annotation is the procedure of identifying the semantically dominant words of a text segment and attaching them with conceptual content information in their context. In this paper, we propose novel methods for automatic annotation of text fragments with entities of Wikipedia, the largest knowledge base online, a process commonly known as Wikification aiming at resolving the semantics of synonymous and polysemous terms accurately. The cornerstone of our contribution is a novel iterative Wikification approach, converging at optimal annotations while balancing high accuracy with performance. Our first two methods can be fine-tuned through a machine-learning technique over large homogenous data sets. Our experimental evaluation resulted in remarkable improvement over state-of-the-art Wikification approaches.
Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.508-518, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_50〉
https://hal.inria.fr/hal-01391352
Contributeur : Hal Ifip
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Soumis le : jeudi 3 novembre 2016 - 11:05:40
Dernière modification le : mardi 26 décembre 2017 - 16:38:01
Document(s) archivé(s) le : samedi 4 février 2017 - 13:03:53
Christos Makris, Michael Simos. Novel Techniques for Text Annotation with Wikipedia Entities. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.508-518, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_50〉. 〈hal-01391352〉
