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Named Entity Disambiguation Using HMMs
2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2013In this paper we present a novel approach to disambiguate textual mentions of named entities against the Wikipedia knowledge base. The conditional dependencies between different named entities across Wikipedia are represented as a Markov network. In our approach, named entities are treated as hidden variables and textual mentions as observations.
Ayman Alhelbawy, Robert J. Gaizauskas
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IdentityRank: Named entity disambiguation in the news domain
Expert Systems With Applications, 2012Abstract News companies produce news items that describe events that happen in the world. These news items usually contain mentions to persons, organizations, locations and other types of named entities that are involved in the events being described.
Jesus Arias Fisteus, Norberto Fernández
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Named Entity Disambiguation for Resource-Poor Languages
Proceedings of the Eighth Workshop on Exploiting Semantic Annotations in Information Retrieval, 2015Named entity disambiguation (NED) is the task of linking ambiguous names in natural language text to canonical entities like people, organizations or places, registered in a knowledge base. The problem is well-studied for English text, but few systems have considered resource-poor languages that lack comprehensive name-entity dictionaries, entity ...
Gad-Elrab, M., Yosef, M., Weikum, G.
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Context Aware Named Entity Disambiguation
2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 2012Ivo Lasek, Peter Vojtás
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A Survey of Named Entity Disambiguation in Entity Linking
2023 3rd International Conference on Intelligent Communications and Computing (ICC), 2023Shuang Duan +3 more
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Named entity disambiguation on an ontology enriched by Wikipedia
2008 IEEE International Conference on Research, Innovation and Vision for the Future in Computing and Communication Technologies, 2008Currently, for named entity disambiguation, the short-age of training data is a problem. This paper presents a novel method that overcomes this problem by automatically generating an annotated corpus based on a specific ontology. Then the corpus was enriched with new and informative features extracted from Wikipedia data. Moreover, rather than pursuing
Hien T Nguyen, Tru H Cao
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Robust named entity disambiguation with random walks
Semantic Web, 2018Named Entity Disambiguation is the task of assigning entities from a Knowledge Graph (KG) to mentions of such entities in a textual document. The state-of-the-art for this task balances two disparate sources of similarity: lexical, defined as the pairwise similarity between mentions in the text and names of entities in the KG; and semantic, defined ...
Zhaochen Guo, Denilson Barbosa 0001
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Exploiting Wikipedia for Entity Name Disambiguation in Tweets
2014Social media repositories serve as a significant source of evidence when extracting information related to the reputation of a particular entity (e.g., a particular politician, singer or company). Reputation management experts are in need of automated methods for mining the social media repositories (in particular Twitter) to monitor the reputation of ...
Muhammad Atif Qureshi 0001 +2 more
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Semantic Relatedness Approach for Named Entity Disambiguation
2010Natural Language is a mean to express and discuss about concepts, objects, events, i.e., it carries semantic contents. One of the ultimate aims of Natural Language Processing techniques is to identify the meaning of the text, providing effective ways to make a proper linkage between textual references and their referents, that is, real world objects ...
Anna Lisa Gentile +3 more
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Personalized Page Rank for Named Entity Disambiguation
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2015The task of Named Entity Disambiguation is to map entity mentions in the document to their correct entries in some knowledge base. We present a novel graph-based disambiguation approach based on Personalized PageRank (PPR) that combines local and global evidence for disambiguation and effectively filters out noise introduced by incorrect candidates ...
Maria Pershina +2 more
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