The ongoing transition from the current Web of unstructured data to the Web of Data yet requires scalable and accurate approaches for the extraction of structured data in RDF from these websites. One of the key steps towards extracting RDF from text is the disambiguation of named entities. While several approaches aim to tackle this problem, they still achieve poor accuracy. We address this drawback by presenting AGDIS-TIS, a novel knowledge-base-agnostic approach for named entity disambiguation.

URL: http://videolectures.net/iswc2014_ngonga_ngomo_agdistis/
Keywords: Named entity extraction, Data Mining, Scalability, Web of Data
Author: Ngomo, Axel-Cyrille
Date created: 2014-12-19 05:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P15M
Educational use: instruction
Educational audience: professional
Interactivity type: expositive

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