Abstract
Named entity recognition (NER) has been a well-studied problem in the area of text mining for locating atomic element into predefined categories, where "name of people" is one of the most commonly studied categories. Numerous new NER techniques have been unfolded to accommodate the needs of the application developed. However, most research works carried out focused on non-fiction domain. Fiction domain exhibits complexity and uncertainty in locating protagonist as it represents name of person in a diverse spectrums, ranging from living things (animals, plants, person) to non-living things (vehicle, furniture). This paper proposes automated protagonist identification in fiction domain, particularly in fairy tales. Verb has been used as a determinant in substantiating the existence of protagonist with the assistance of WordNet. The experimental results show that it is viable to use verb in identifying named entity, particularly "people" category and it can be applied in a small text size environment.
Original language | English |
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Title of host publication | Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Proceedings |
Pages | 395-406 |
Number of pages | 12 |
Edition | PART 2 |
DOIs | |
Publication status | Published - 2012 |
Externally published | Yes |
Event | Pacific-Asia Conference on Knowledge Discovery and Data Mining 2012 - Kuala Lumpur, Malaysia Duration: 29 May 2012 → 1 Jun 2012 Conference number: 16th https://link.springer.com/book/10.1007/978-3-642-30217-6 (Proceedings) |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Number | PART 2 |
Volume | 7301 LNAI |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | Pacific-Asia Conference on Knowledge Discovery and Data Mining 2012 |
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Abbreviated title | PAKDD 2012 |
Country/Territory | Malaysia |
City | Kuala Lumpur |
Period | 29/05/12 → 1/06/12 |
Internet address |
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Keywords
- characters
- fairy tales
- Named entity recognition
- text mining