The basic idea behind a Cross Language Information Retrieval (CLIR) system is to retrieve documents in a language different from the query. Therefore translation is needed before matching of query and document terms can take place. This translation process tends to cause a reduction in the retrieval effectiveness of CUR as compared to monolingual Information Retrieval systems. The research introduces a new CUR approach, by producing a unique CUR system based on multilingual Arabic/English ontologies; the ontology is used for query expansion and translation. Both Arabic and English ontologies are mapped using unique automatic ontology mapping tools that will be introduced in this study as well. This research addresses lexical ambiguity problems caused by erroneous translations. To prevent this, the study proposed developing a CUR system based on a multilingual ontology to create a mapping that will solve the lexical ambiguity problem. Also this study uses ontology semantic relations to expand the query to produce a better formulated query and gain better results. Finally a weighting algorithm is applied to the result set ofthe proposed system and results are compared to a state ofthe art baseline CUR system that uses a dictionary as a translation base. The CUR system was implemented in the travel domain and two ontologies were developed. A unique ontology mapping tool was also developed to map the two ontologies. The experimental work described consists of the design, development, and evaluation of the proposed CUR system. The evaluation of the proposed system demonstrates that the retrieval effectiveness outperformed the baseline system after running two human centered experiments. Relevancy judgments were measured and the results produced indicated that the proposed system is more effective than the baseline system.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:505050 |
| Date | January 2008 |
| Creators | Abusalah, Mustafa A. |
| Publisher | University of Sunderland |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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