Clustering for Large Result Sets

1
Clustering for Large Result Sets

• Proposed problem large result sets, most of
  which are irrelevant to the intended meaning
• Our example cheap beautiful Jaguars for sale
• Google returns Jaguar car parts, perfume,
  Jacksonville Jaguar tickets, (animals? Mac OS
  10.2?)
• Existing technology teoma.com, vivismo.com,
  others?
• Many clusters appear identical (Classified ads
  from Fresno, Cars and trucks in San Francisco,
  Cars and trucks in Los Angeles)
• Others dont appear (animals, even though top
  link was Exotic animals for sale)
• Some are just weird (Shop Slashdot? Real Estate?
  Mexico?)

2
Research Topics

• Context
• What makes these clustering engines work?
• What knowledge-base techniques could apply here?
• Natural language processing?
• Research directions
• On what basis do we create clusters?
• Dictionary definitions ? document classification
  using classic IR techniques
• Fixed number (easier for user to visualize?) ?
  minimize some sort of distance metric
• Neural-net classifiers?
• How do we refine the query?
• assuming weve narrowed it down to cars, we may
  want to cluster on cheap or beautiful
• unstructured, semi-structured ? structured
• How do we present the results?
• How do we describe a cluster?
• What document best represents a cluster?