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Full-Text Articles in Computer Engineering
Statistical Pos Tagging Experiments On Persian Text, F. Raja, S. Tasharofi, Farhad Oroumchian
Statistical Pos Tagging Experiments On Persian Text, F. Raja, S. Tasharofi, Farhad Oroumchian
University of Wollongong in Dubai - Papers
Part-Of-Speech (POS) tagging is the process of marking-up the words in a text with their corresponding parts of speech. It is an essential part of text and natural language processing. There are many models and software for POS tagging in English and other European languages. Little work has been done on POS tagging of Persian language which uses Arabic script for writing. In these experiments we want to see how effective would be if we just applied a POS tagger from a language such as English to Persian. Although English and Persian are both Indo-European languages but they have subtle …
Using Owa Fuzzy Operator To Merge Retrieval System Results, H. Amiri, A. Aleahmad, Farhad Oroumchian, C. Lucas, M. Rahgozar
Using Owa Fuzzy Operator To Merge Retrieval System Results, H. Amiri, A. Aleahmad, Farhad Oroumchian, C. Lucas, M. Rahgozar
University of Wollongong in Dubai - Papers
With rapid growth of information sources, it is essential to develop methods that retrieve most relevant information according to the user requirements. One way of improving the quality of retrieval is to use more than one retrieval engine and then merge the retrieved results and show a single ranked list to the user. There are studies that suggest combining the results of multiple search engines will improve ranking when these engine are treated as independent experts. In this study, we investigated performance of Persian retrieval by merging four different language modeling methods and two vector space models with Lnu.ltu and …
A Vector Based Method Of Ontology Matching, Z. Eidoon, N. Yazdani, Farhad Oroumchian
A Vector Based Method Of Ontology Matching, Z. Eidoon, N. Yazdani, Farhad Oroumchian
University of Wollongong in Dubai - Papers
Semantic interoperability is highly influenced by similarities and differences which exist between ontologies. Ontology matching as a solution for finding corresponding concepts among ontologies has emerged to facilitate semantic based negotiations of applications. This paper presents a method of ontology matching which is based on vectorizing ontologies and estimating their similarity degree. A post processing with two heuristic rules also has been employed to improve the results. The proposed method is successfully applied to the test suit of Ontology Alignment Evaluation Initiative 2005 [10] and compared to results obtained by other methods. In general the preliminary results are encouraging and …