Indexing and Weighting of Multilingual and Mixed Documents
Ali, Mohammed Mustafa, Izzedin Osman and Hussein Suleman (2011) Indexing and Weighting of Multilingual and Mixed Documents. In Brown, Irwin, Kosheek Sewchurran and Hussein Suleman, Eds. Proceedings SAICSIT 2011, pages 161-170, Cape Town, South Africa.
Non-English-speaking users, such as Arabic speakers, are not always able to express terminology in their native languages, especially in scientific domains. Such difficulty forces many Arabic authors and scholars to use English terms in order to explain precise concepts, particularly when they address technical topics, resulting in mixed/multilingual queries with both English and Arabic terms. Cross Language Information Retrieval (CLIR) allows users to search documents that are written in a language different from the query. However, current algorithms are optimized for monolingual queries, even if they are translated. This paper attempts to address the problem of multilingual querying in CLIR. New techniques that are better suited to the unique characteristics of this problem, in terms of indexing and weighting, are proposed. A new multilingual and mixed test collection containing mixed-language (Arabic and English) computer science documents and mixed-language queries has been created. Experimental results show that current CLIR techniques were not designed for these types of multilingual queries and documents and are found to perform poorly whereas the proposed techniques are found to be promising.
|EPrint Type:||Conference Paper|
|Subjects:||H Information Systems: H.1 MODELS AND PRINCIPLES|
H Information Systems: H.3 INFORMATION STORAGE AND RETRIEVAL
|Deposited By:||Suleman, Hussein|
|Deposited On:||12 December 2011|