NDLI: A Framework for Effective Annotation of Information from Closed Captions Using Ontologies

Content Provider	Springer Nature Link
Author	Khan, Latifur McLeod, Dennis Hovy, Eduard
Copyright Year	2005
Abstract	To improve the accuracy in terms of precision and recall of an audio information retrieval system we have created a domain-specific ontology (a collection of key concepts and their interrelationships), as well as a novel, pruning algorithm. Given the shortcomings of keyword-based techniques, we have opted to employ a concept-based technique utilizing this ontology. Achieving high precision and high recall is the key problem in the retrieval of audio information. In traditional approaches, high recall is typically achieved at the expense of low precision, and vice versa. Through the use of a domain-specific ontology appropriate concepts can be identified during metadata generation (description of audio) or query generation, thus improving precision.When irrelevant concepts are associated with queries or documents there is a loss of precision. On the other side of the coin, if relevant concepts are discarded, a loss of recall will ensue. In conjunction with the use of a domain specific ontology we have thus proposed a novel, automatic pruning algorithm which prunes as many irrelevant concepts as possible during any case of description and identification of documents, and query generation. To improve recall, A controlled and correct query expansion mechanism is proposed for the improvement of recall, thus guaranteeing that precision will not be lost.We have constructed a demonstration prototype, and experimentally and analytically we have shown that our model, compared to keyword search, achieves a significantly higher degree of precision and recall.
Starting Page	181
Ending Page	205
Page Count	25
File Format	PDF
ISSN	09259902
Journal	Journal of Intelligent Information Systems
Volume Number	25
Issue Number	2
e-ISSN	15737675
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2005-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	metadata ontology audio SQL Data Structures, Cryptology and Information Theory Artificial Intelligence (incl. Robotics) Document Preparation and Text Processing Business Information Systems
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Networks and Communications Information Systems Software Hardware and Architecture

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