With the explosion in the amount of semi-structured data users access and store, there is a need for complex search tools to retrieve often very heterogeneous data in a simple and efficient way. Existing tools usually index text content, allowing for 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. We propose a novel multidimensional querying approach to semi-structured data searches in personal information systems by allowing users to provide fuzzy structure and metadata conditions in addition to traditional keyword conditions. The provided query interface is more comprehensive than content-only searches as it considers three query dimensions (content, structure, metadata) in the search. We have implemented our proposed approach in the Wayfinder file system. In this demo, we will use this implementation to both present an overview of the unified scoring framework underlying the fuzzy multi-dimensional querying approach and demonstrate its potential in improving search results.
['Christopher Peery', 'Wei Wang', 'Amélie Marian', 'Thu D. Nguyen']
Fuzzy Multi-Dimensional Search in the Wayfinder File System