![Top of Menu](/www2007/images/menuTop.jpg)
![Home](/www2007/images/menuHome.jpg)
![CFP](/www2007/images/menuCfp.jpg)
![Program](/www2007/images/menuProgramS.jpg)
![Committees](/www2007/images/menuCommittee.jpg)
![Key Dates](/www2007/images/menuKeyDates.jpg)
![Location](/www2007/images/menuLocation.jpg)
![Hotel](/www2007/images/menuHotel.jpg)
![Registration](/www2007/images/menuRegistration.jpg)
![Students](/www2007/images/menuStudents.jpg)
![Sponsors](/www2007/images/menuSponsors.jpg)
![Media](/www2007/images/menuMedia.jpg)
![Submission](/www2007/images/menuSubmission.jpg)
![Tutorials](/www2007/images/menuTutorial.jpg)
![Workshops](/www2007/images/menuWorkshops.jpg)
![Travel Info](/www2007/images/menuTravel.jpg)
![Proceedings](/www2007/images/menuProceedings.jpg)
Track: Search
Paper Title:
On Ranking Techniques for Desktop Search
Authors:
Abstract:
This paper addresses the desktop search problem by considering various
techniques for ranking results of a search query over the
file system. First, basic ranking techniques, which are based on
a single file feature (e.g., file name, file content, access date, etc.)
are considered. Next, two learning-based ranking schemes are presented, and are shown to be
significantly more effective than the basic ranking methods. Finally,
a novel ranking technique, based on query selectiveness is considered,
for use during the cold-start period of the system. This method is
also shown to be empirically effective, even though it does not
involve any learning.