Abstract | ||
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Recognition of named entities (people, companies, locations, etc) is an essential task of text analytics. We address the subproblem of this task, namely, named entity classification. We propose a novel approach that constructs an effective fine-grained named entity classifier. Its key highlights are semi-automatic training set construction from Wikipedia articles and additional feature selection. We justify our solution by creating 18-class classifier and demonstrating its effectiveness and efficiency. |
Year | DOI | Venue |
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2011 | 10.1109/ICDEW.2011.5767662 | Data Engineering Workshops |
Keywords | DocType | ISBN |
fine-grained class,novel approach,key highlight,entity classifier,semi-automatic training set construction,entity classification,18-class classifier,wikipedia article,text analytics,essential task,classifying wikipedia entity,additional feature selection,support vector machine,electronic publishing,feature selection,accuracy,internet,support vector machines,text analysis,encyclopedias | Conference | 978-1-4244-9194-0 |
Citations | PageRank | References |
6 | 0.50 | 19 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Maksim Tkatchenko | 1 | 6 | 0.50 |
Alexander Ulanov | 2 | 65 | 9.64 |
Andrey Simanovsky | 3 | 45 | 3.98 |