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"paper_id": "U07-1001",
"header": {
"generated_with": "S2ORC 1.0.0",
"date_generated": "2023-01-19T03:08:58.382999Z"
},
"title": "Text Mining Techniques for Building a Biolexicon",
"authors": [
{
"first": "Sophia",
"middle": [],
"last": "Ananiadou",
"suffix": "",
"affiliation": {
"laboratory": "",
"institution": "The University of Manchester",
"location": {}
},
"email": "sophia.ananiadou@manchester.ac.uk"
}
],
"year": "",
"venue": null,
"identifiers": {},
"abstract": "My talk will focus on building a biolexicon by leveraging existing bio-resources, combining them within a common, standardized lexical, terminological, conceptual representation framework and employing advanced NL technologies to discover new terms, concepts, relations and linguistic lexical information from text. In particular I will discuss term normalisation techniques, named entity recognition and a smart dictionary look up. This research forms part of the National Centre for Text Mining (www.nactem.ac.uk) and the project BOOTStrep.",
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"paper_id": "U07-1001",
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"abstract": [
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"text": "My talk will focus on building a biolexicon by leveraging existing bio-resources, combining them within a common, standardized lexical, terminological, conceptual representation framework and employing advanced NL technologies to discover new terms, concepts, relations and linguistic lexical information from text. In particular I will discuss term normalisation techniques, named entity recognition and a smart dictionary look up. This research forms part of the National Centre for Text Mining (www.nactem.ac.uk) and the project BOOTStrep.",
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"section": "Abstract",
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} |