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There are a lot of valuable data on the web that users may need to improve their decision making process. The answer of user query often exists in multiple Web data sources. The extraction and combination of answers of user queries from different Web data sources often fails because of syntax and semantic heterogeneity between user queries and web data sources. The retrieval and extraction of these answers from the different web data sources impose a need for queries to be syntactically and semantically mapped to Web sources query languages. In this paper, we focus on semantic heterogeneity among user query terms and web data sources terms. We propose an approach for the semantic mapping of user query terms to web data sources terms.