Hend Suliman Al-Khalifa

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Finding good keywords to describe resources is an ongoing problem: typically we select such words manually from a thesaurus of terms, or they are created using automatic keyword extraction techniques. Folksonomies are an increasingly well populated source of unstructured tags describing web resources. This paper explores the value of the folksonomy tags as(More)
Semantic Metadata, which describes the meaning of documents, can be produced either manually or else semi-automatically using information extraction techniques. Manual techniques are expensive if they rely on skilled cataloguers, but a possible alternative is to make use of community produced annotations such as those collected in folksonomies. This paper(More)
Since the advent of the Semantic Web in the late 90's, many Web applications were created to benefit from the capabilities provided by Semantic Web technologies. These capabilities include intelligent reasoning over data, semantic search and data interoperability. However, most Semantic Web technologies are dedicated to processing Latin family scripts,(More)
Information availability is a key factor in the acquisition of knowledge. Access to information either in the general area or even in more specific ones like sciences, languages, and religion become wider since the use of semantics in World Wide Web. Semantic Web technologies assist in the acquiring of information by creating processes that link information(More)
Folksonomies provide a free source of keywords describing web resources, however, these keywords are free form and unstructured. In this paper, we describe a novel tool that converts folksonomy tags into semantic metadata, and present a case study consisting of a framework for evaluating the usefulness of this metadata within the context of a particular(More)
This paper presents two approaches for building ontologies to represent Quranic words based on the field of componential analysis. The first approach is a class-based ontology and the second is an instance-based ontology. Both approaches are described in details along with the result of the comparison.
In this paper we present the Arib system for Arabic spelling error detection and correction as part of the second Shared Task on Automatic Arabic Error Correction. Our system contains many components that address various types of spelling error and applies a combination of approaches including rule based, statistical based, and lexicon based in a cascade(More)