Paper Info
Title
Using provenance to aid in personal file search
Abstract
As the scope of personal data grows, it becomes increasingly difficult to find what we need when we need it. Desktop search tools provide a potential answer, but most existing tools are incomplete solutions: they index content, but fail to capture dynamic relationships from the user's context. One emerging solution to this is context-enhanced search, a technique that reorders and extends the results of content-only search using contextual information. Within this framework, we propose using strict causality, rather than temporal locality, the current state of the art, to direct contextual searches. Causality more accurately identifies data flow between files, reducing the false-positives created by context-switching and background noise. Further, unlike previous work, we conduct an online user study with a fully-functioning implementation to evaluate user-perceived search quality directly. Search results generated by our causality mechanism are rated a statistically-significant 17% higher on average over all queries than by using content-only search or context-enhanced search with temporal locality.
Year
Venue
Keywords
2007
USENIX Annual Technical Conference
strict causality,content-only search,causality mechanism,personal file search,desktop search tool,temporal locality,context-enhanced search,contextual information,contextual search,user-perceived search quality,search result,indexation,data flow,false positive,statistical significance
Field
DocType
ISBN
Desktop search,Data mining,Contextual information,Causality,Background noise,Locality of reference,Information retrieval,Semantic search,Computer science,Real-time computing,Search analytics,Data flow diagram
Conference
999-8888-77-6
Citations 
PageRank 
References 
27
1.26
10
Authors
4
Name
Order
Citations
PageRank
Sam Shah1271.26
Craig A. N. Soules259145.41
Gregory R. Ganger34560383.16
Brian Noble42954385.01