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In recent years, market has seen a growth in the amount of semi-structured data users access and store in personal information management systems. This has necessitated the need to develop complex search tools that are capable of retrieving very heterogeneous data in a simple and efficient way. This paper attempts to undertake a multi-dimensional search for personal information management systems. This paper presents a new multi-dimensional approach to semi-structured data searches in personal information management systems. This is done by allowing users to provide fuzzy structure and metadata conditions in addition to keyword conditions. The techniques presented in this paper consider three query dimensions- content, structure, metadata- in the search. This makes them a comprehensive complex query interface than content-only searches. These techniques can be used to individually score each dimension as well as a framework to integrate the three dimension scores into a meaningful unified score. To show the effects of this on the overall scores and ranks of files, as well as on query performance, the paper also presents a thorough experimental evaluation of the techniques. The paper concludes that the scoring strategy presented in the paper is able to adequately take into account the approximation in each dimension to efficiently evaluate fuzzy multi-dimensional queries.
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