Hend Suliman Al-Khalifa

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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)
Metadata attempts to describe the content, format, purpose and structure of data. Over the past few years, the IEEE-LOM standard has dominated the metadata world in e-learning applications. However, with the advent of the Semantic Web, e-learning applications are beginning to evolve their metadata representation from these standards by adding semantic(More)
In this paper a barcode-based system to help the visually impaired and blind people identify objects in the environment is introduced. The system is based on the idea of utilizing QR codes (two-dimensional barcode) affixed to an object and scanned using a camera phone equipped with QR reader software. The reader decodes the barcode to a URL and directs the(More)
Sentiment analysis is the process of identifying the polarity of sentiments held in opinions found in pieces of text and classifying them as positive, negative or neutral. In this paper, we propose the implementation of a sentiment analysis tool that is conducted over text found in Arabic new media including web forums, comments on newspaper articles and(More)