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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 2 of 2 1 Entity linking for Tweets Basile, Pierpaolo; Caputo, Annalina In: Basile, Pierpaolo orcid:0000-0002-0545-1105 and Caputo, Annalina orcid:0000-0002-7144-8545 (2017) Entity linking for Tweets. Encyclopedia with Semantic Computing and Robotic Intelligence, 1 (1). pp. 1-9. ISSN 2529-7376 (2017) Abstract: Named Entity Linking (NEL) is the task of semantically annotating entity mentions in a portion of text with links to a knowledge base. The automatic annotation, which requires the recognition and disambiguation of the entity mention, usually exploits contextual clues like the context of usage and the coherence with respect to other entities. In Twitter, the limits of 140 characters originates very short and noisy text messages that pose new challenges to the entity linking task. We propose an overview of NEL methods focusing on approaches specifically developed to deal with short messages, like tweets. NEL is a fundamental task for the extraction and annotation of concepts in tweets, which is necessary for making the Twitter’s huge amount of interconnected user-generated contents machine readable and enable the intelligent information access. Keyword: Artificial intelligence; Computational linguistics; Entity linking; Twitter URL: http://doras.dcu.ie/25690/ BASE Hide details 2 EVALITA Goes Social: Tasks, Data, and Community at the 2016 Edition Cutugno, Francesco; Sprugnoli, Rachele (orcid:0000-0001-6861-5595); Nissim, Malvina. - 2017 BASE Show details

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