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One of the major challenges in the Information Retrieval field is handling the massive amount of information available to Internet users. Existing ranking techniques and strategies that govern the retrieval process fall short of expected accuracy. Often relevant documents are buried deep in the list of documents returned by the search engine. In order to improve retrieval accuracy the authors examine the issue of language effect on the retrieval process. Then, they propose a solution for a more biased, user-centric relevance for retrieved data. The results demonstrate that using indices based on variations of the same language enhances the accuracy of search engines for individual users.
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