Abstract
Recognizing, identifying and extracting entities, like Person, Location and Organization are useful for information mining from unstructured texts. Currently, it is a typical way of establishing the content for future use such as filtering, indexing or search. This paper presents the results obtained for the benchmark test on our Text Annotation Engine (T-ANNE) that we have developed against several similar systems. Precision, Recall and F-Measure will be used to measure the results for this evaluation.
Original language | English |
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Title of host publication | Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies, i-KNOW 2012 |
DOIs | |
Publication status | Published - 2012 |
Externally published | Yes |
Event | International Conference on Knowledge Management and Knowledge Technologies 2012 - Graz, Austria Duration: 5 Sept 2012 → 7 Sept 2012 Conference number: 12th https://dl.acm.org/doi/proceedings/10.1145/2362456 |
Conference
Conference | International Conference on Knowledge Management and Knowledge Technologies 2012 |
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Abbreviated title | i-KNOW 2012 |
Country/Territory | Austria |
City | Graz |
Period | 5/09/12 → 7/09/12 |
Internet address |
Keywords
- Named entity recognition
- Natural language processing
- Text Annotation Engine