Results 171 to 180 of about 20,627 (210)

Entity disambiguation using semantic networks

Journal of the American Society for Information Science and Technology, 2012
A major stumbling block preventing machines from understanding text is the problem of entity disambiguation. While humans find it easy to determine that a person named in one story is the same person referenced in a second story, machines rely heavily on crude heuristics such as string matching and stemming to make guesses as to whether nouns are ...
Jorge H. Román, Kevin J. Hulin, Linn M. Collins, James E. Powell   +3 more
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Topological Features Based Entity Disambiguation

Journal of Computer Science and Technology, 2016
This work proposes an unsupervised topological features based entity disambiguation solution. Most existing studies leverage semantic information to resolve ambiguous references. However, the semantic information is not always accessible because of privacy or is too expensive to access.
Chen-Chen Sun, De-Rong Shen, Yue Kou, Tie-Zheng Nie, Ge Yu   +4 more
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System for collective entity disambiguation

Proceedings of the first international workshop on Entity recognition & disambiguation - ERD '14, 2014
We present an approach and a system for collective disambiguation of entity mentions occurring in natural language text. Given an input text, the system spots mentions and their candidate entities. Candidate entities across all mentions are jointly modeled as binary nodes in a Markov Random Field.
Ashish Kulkarni, Kanika Agarwal, Pararth Shah, Sunny Raj Rathod, Ganesh Ramakrishnan   +4 more
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Towards Vietnamese Entity Disambiguation

2014
Entity Disambiguation (ED) is a fundamental task in Natural Language Processing (NLP). The term Entity is used to mean either a Named Entity or an Abstract Concept. Although there have been many works on the ED task for English and some for Vietnamese, this is the first time this paper tackles the general ED task for Vietnamese that deal with both ...
Long M. Truong, Tru H. Cao, Dien Dinh
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Learning Entity Representation for Named Entity Disambiguation

2015
In this paper we present a novel disambiguation model, based on neural networks. Most existing studies focus on designing effective man-made features and complicated similarity measures to obtain better disambiguation performance. Instead, our method learns distributed representation of entity to measure similarity without man-made features.
Rui Cai, Houfeng Wang, Junhao Zhang
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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), 2013
In 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 Gaizauskas
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Entity Type Disambiguation in User Queries [PDF]

Journal of Information & Knowledge Management, 2011
Searching for information about individual entities such as persons, locations, events, is an important activity in Internet search today, and is in its core a very semantic-oriented task. Several ways for accessing such information exist, but for locating entity-specific information, search engines are the most commonly used approach. In this context,
Bazzanella, Barbara, Stoermer, Heiko, Bouquet, Paolo   +2 more
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Named Entity Disambiguation for Resource-Poor Languages

Proceedings of the Eighth Workshop on Exploiting Semantic Annotations in Information Retrieval, 2015
Named 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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Do We Need Entity-Centric Knowledge Bases for Entity Disambiguation?

Proceedings of the 13th International Conference on Knowledge Management and Knowledge Technologies, 2013
Entity Disambiguation has been studied extensively in the last 10 years with authors reporting increasingly well performing systems. However, most studies focused on general purpose knowledge bases like Wikipedia or DBPedia and left out the question how those results generalize to more specialized domains. This is especially important in the context of
Zwicklbauer, Stefan, Seifert, Christin, Granitzer, Michael   +2 more
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Generative Event Schema Induction with Entity Disambiguation

Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2015
This paper presents a generative model to event schema induction. Previous methods in the literature only use head words to represent entities. However, elements other than head words contain useful information. For instance, an armed man is more discriminative than man.
Nguyen, K.-H., Tannier, X., Ferret, Olivier, Besancon, R.   +3 more
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