12Explaining and Scrubbing Context-Aware Query Results

Abstract: A context-aware query engine works with huge amounts of uncertain data, coming from sensor networks, subjective preferences, statistical data analysis, machine learning and data mining, information extraction and integration, etc. As a consequence, the answers to a context-aware query may be incorrect, possibly making the query system questionable and unacceptable by its end-users. In order to help users to assess the given answers, it is desirable for context-aware systems to give an explanation on how it arrives at an answer and on which probabilistic assumptions the derived answer is based. In this way, the user based on his/ her knowledge about uncertain information can not ...

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