Personalized Profile Based Search Interface With Ranked and Clustered Display

Abstract

We have developed an experimental meta-search engine, which takes the snippets from traditional search engines and presents them to the user either in the form of clusters, indices or re-ranked list optionally based on the user's profile. The system also allows the user to give positive or negative feedback on the documents, clusters and indices. The architecture allows different algorithms for each of the features to be plugged-in easily, i.e. various clustering, indexing and relevance feedback algorithms, and profiling methods.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2001
Accession Number
ADA439556

Entities

People

  • B. U. Oztekin
  • Euihong Han
  • Levent Ertoz
  • Sachin Kumar
  • Saurabh Singhal
  • Vipin Kumar

Organizations

  • University of Minnesota

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Clustering
  • Computer Languages
  • Computer Programming
  • Computer Science
  • Computers
  • Data Mining
  • Demographic Cohorts
  • Feedback
  • Foreign Languages
  • Hierarchies
  • High Performance Computing
  • Indexes
  • Language
  • Natural Languages
  • Programming Languages

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Linguistics
  • Neural Network Machine Learning.