Cited By
View all- Theocharopoulou GGiannakis K(2012)Web Mining to Create Semantic Content: A Case Study for the EnvironmentArtificial Intelligence Applications and Innovations10.1007/978-3-642-33412-2_42(411-420)Online publication date: 2012
Supervised identification and linking of concept mentions to a domain-specific ontology
Authors: 
Gabor Melli, 
Martin EsterAuthors Info & Claims
Gabor Melli, Martin EsterAuthors Info & ClaimsPages 1717 - 1720
Abstract
We propose a pipelined supervised learning approach named SDOI to the task of interlinking the concepts mentioned within a document to the concepts within an ontology. Concept mention identification is performed by training a sequential tagging model. Each identified concept mention is then associated with a set of candidate ontology concepts along with a feature vector based on features proposed in the literature and novel ones based on new data sources, such as from the training corpus itself. An iterative algorithm is defined for handling collective features. We show a lift in performance over applicable baselines against the ability to identify the concept mentions within the 139 KDD-2009 conference paper abstracts, and to link these concept mentions to a domain-specific ontology for the field of data mining. Additional experiments of 22 ICDM-2009 abstracts suggest that the trained models are portable both in terms of accuracy and in their ability to reduce annotation time.
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- Supervised identification and linking of concept mentions to a domain-specific ontology
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Published In
October 2010
2036 pages
ISBN:9781450300995
DOI:10.1145/1871437
- General Chair:
- Jimmy Huang,
- Program Chairs:
- Nick Koudas,
- Gareth Jones,
- Xindong Wu,
- Kevyn Collins-Thompson,
- Aijun An
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Published: 26 October 2010
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CIKM '10: International Conference on Information and Knowledge Management
October 26 - 30, 2010
ON, Toronto, Canada
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View all- Theocharopoulou GGiannakis K(2012)Web Mining to Create Semantic Content: A Case Study for the EnvironmentArtificial Intelligence Applications and Innovations10.1007/978-3-642-33412-2_42(411-420)Online publication date: 2012
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