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Journal ArticleDOI

Designing a novel cross ontology measure to extract resources from knowledge base for an adaptive e-learning system

TLDR
An adaptive e- learning system is proposed, which generates use r-specific e-learning contents based on their knowledge level and by comparing the similarity of concepts between ontologies, to enhance the integration and retrieval of resources in a more meaningful way.
Abstract
E-Learning deals with the interaction between the teacher and learner on the basis of knowledge possessed by the learner. Ontology is a key concept that helps in providing more relevant and accurate information to the users for a particular domain or from multiple domains. Finding semantic similarity between the concepts of different ontologies will enhance the integration and retrieval of resources in a more meaningful way. In this paper, an adaptive e-learning system is proposed, which generates use r-specific e-learning contents based on their knowledge level and by comparing the similarity of concepts between ontologies. Based on this a new approach is designed to retrieve more relevant and accurate documents by embedding a new Concept Similarity measure ConSim, after evaluating the user's knowledge based on the search query. The experimental results prove that after embedding the ConSim measure the retrieval results have been improved.

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References
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Journal ArticleDOI

WordNet : an electronic lexical database

Christiane Fellbaum
- 01 Sep 2000 - 
TL;DR: The lexical database: nouns in WordNet, Katherine J. Miller a semantic network of English verbs, and applications of WordNet: building semantic concordances are presented.
Journal ArticleDOI

Features of Similarity

Amos Tversky
- 01 Jul 1977 - 
TL;DR: The metric and dimensional assumptions that underlie the geometric representation of similarity are questioned on both theoretical and empirical grounds and a set of qualitative assumptions are shown to imply the contrast model, which expresses the similarity between objects as a linear combination of the measures of their common and distinctive features.
Proceedings Article

An Information-Theoretic Definition of Similarity

Dekang Lin
TL;DR: This work presents an informationtheoretic definition of similarity that is applicable as long as there is a probabilistic model and demonstrates how this definition can be used to measure the similarity in a number of different domains.
Posted Content

Using Information Content to Evaluate Semantic Similarity in a Taxonomy

TL;DR: In this article, a new measure of semantic similarity in an IS-A taxonomy based on the notion of information content is presented, and experimental evaluation suggests that the measure performs encouragingly well (a correlation of r = 0.79 with a benchmark set of human similarity judgments, with an upper bound of r < 0.90 for human subjects performing the same task).
Proceedings ArticleDOI

Verb semantics and lexical selection

Abstract: This paper will focus on the semantic representation of verbs in computer systems and its impact on lexical selection problems in machine translation (MT). Two groups of English and Chinese verbs are examined to show that lexical selection must be based on interpretation of the sentences as well as selection restrictions placed on the verb arguments. A novel representation scheme is suggested, and is compared to representations with selection restrictions used in transfer-based MT. We see our approach as closely aligned with knowledge-based MT approaches (KBMT), and as a separate component that could be incorporated into existing systems. Examples and experimental results will show that, using this scheme, inexact matches can achieve correct lexical selection.
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