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Named Entity Recognition Using Web Document Corpus

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Author :  Wahiba Ben Abdessalem Karaa

Affiliation :  Institut Superieur de Gestion de Tunis

Country :  Tunisia

Category :  Information Technology Management

Volume, Issue, Month, Year :  3, 1, February, 2011

Abstract :


This paper introduces a named entity recognition approach in textual corpus. This Named Entity (NE) can be a named: location, person, organization, date, time, etc., characterized by instances. A NE is found in texts accompanied by contexts: words that are left or right of the NE. The work mainly aims at identifying contexts inducing the NE’s nature. As such, The occurrence of the word "President" in a text, means that this word or context may be followed by the name of a president as President "Obama". Likewise, a word preceded by the string "footballer" induces that this is the name of a footballer. NE recognition may be viewed as a classification method, where every word is assigned to a NE class, regarding the context. The aim of this study is then to identify and classify the contexts that are most relevant to recognize a NE, those which are frequently found with the NE. A learning approach using training corpus: web documents, constructed from learning examples is then suggested. Frequency representations and modified tf-idf representations are used to calculate the context weights associated to context frequency, learning example frequency, and document frequency in the corpus.

Keyword :  Named entity; Learning; Information extraction; tf-idf; Web document.

Journal/ Proceedings Name :  International Journal of Managing Information Technology (IJMIT) WJCI Indexed

URL :  https://airccse.org/journal/ijmit/papers/3111ijmit04.pdf

User Name : Adriano
Posted 16-10-2021 on 18:32:15 AEDT



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