Query Processing for Personal Management Systems Based On Multidimensional Search
Recently, parallel search engines have been implemented based on scalable distributed file systems such as Google file system. Existing tools typically support some IR-style ranking on the textual part of the query, but only consider structure (e.g., file directory) and metadata (e.g., date, file type) as filtering conditions. The authors propose a novel multi-dimensional search approach that allows users to perform fuzzy searches for structure and metadata conditions in addition to keyword conditions. Their techniques individually score each dimension and integrate the three dimension scores into a meaningful unified score.