Abstract
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Article Information:
An Intelligent Technique for Extracting Subjects from User Profile Using ODP Ontology-Driven Reasoning
Mina Minazadeh, Kambiz Badie and Mir Mohsen Pedram
Corresponding Author: Mina Minazadeh
Submitted: January 08, 2012
Accepted: March 15, 2012
Published: August 01, 2012 |
Abstract:
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Nowadays, the amount of available information, especially on the Web, is increasing. In this field,
the role of user modeling and personalized information access is obviously vital. The traditional techniques like
BOW (Bags of words) limit recommendations to the words which have been stored in the profile. In other
words, the news items, which semantically relate to the users interests, can’t be recognized and recommended
to the users. Besides, BOW technique suffers from the curse of dimensionality, thus computational burden
reduction is an essential task to efficiently handle a large number of terms in practical applications. This study
focuses on the problem of choosing a representation of documents that can be suitable to induce concept-based
user profiles as well as to support a content-based retrieval process. In this study, a new approach has been
proposed to construct a ranked semantic user profile through extracting the related subjects. The new items can
be recommended through collecting information from the user’s selections, based on existing domain ontology
ODP. The efficiency of the proposed technique has been shown by embedding it into an intelligent aggregator,
RSS (RSS is acronym of “ Really Simple Syndication) feed reader, which has been trained and evaluated by
different and heterogeneous users. The results in experimental session show that the incoming news item which
semantically relates to the profile gets highly recommended to the user despite its excluding of common words
in the profile.
Key words: Component, ontology, ranking, semantic profile, user interest, ,
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Cite this Reference:
Mina Minazadeh, Kambiz Badie and Mir Mohsen Pedram, . An Intelligent Technique for Extracting Subjects from User Profile Using ODP Ontology-Driven Reasoning. Research Journal of Applied Sciences, Engineering and Technology, (15): 2334-2342.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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Sales & Services |
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