Paper Info
Title
Multi-dimensional search for personal information management systems
Abstract
With the explosion in the amount of semi-structured data users access and store in personal information management systems, 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 multi-dimensional approach to semi-structured data searches in personal information management systems by allowing users to provide fuzzy structure and metadata conditions in addition to keyword conditions. Our techniques provide a complex query interface that is more comprehensive than content-only searches as it considers three query dimensions (content, structure, metadata) in the search. We propose techniques to individually score each dimension, as well as a framework to integrate the three dimension scores into a meaningful unified score. Our work is integrated in Wayfinder, an existing fully-functioning file system. We perform a thorough experimental evaluation of our techniques to show the effect of approximating individual dimensions on the overall scores and ranks of files, as well as on query performance. Our experiments show that our scoring strategy adequately takes into account the approximation in each dimension to efficiently evaluate fuzzy multi-dimensional queries. In addition, fuzzy query conditions in non-content dimensions can significantly improve scoring (and thus ranking) accuracy.
Year
DOI
Venue
2008
10.1145/1353343.1353400
EDBT
Keywords
Field
DocType
dimension score,multi-dimensional search,fuzzy structure,fuzzy query condition,existing fully-functioning file system,query performance,fuzzy multi-dimensional query,heterogeneous data,personal information management system,query dimension,complex query interface,semi structured data,personal information management,query optimization
Query optimization,Web search query,Data mining,Query language,Information retrieval,Personal information management,Query expansion,Computer science,Sargable,Web query classification,Ranking (information retrieval),Database
Conference
Citations 
PageRank 
References 
11
0.85
19
Authors
4
Name
Order
Citations
PageRank
Christopher Peery12139.97
Wei Wang2152.27
Amélie Marian3128077.92
Thu D. Nguyen41518102.53