Contact Recommendations from Aggegrated On-Line Activity

Abstract

We describe a system for recommending people based on similar interests and activities as part of a company-wide social networking site. Our contact recommendation service aggregates input from multiple on-line data sources and combines them using a Bayesian network to generate a rating of the overall match between two users. The system is running as part of an experimental social networking site at MITRE. We present the results of two experiments in which we evaluated the performance of the recommender algorithm and user interface.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2011
Accession Number
AD1108504

Entities

Organizations

  • MITRE Corporation

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Bayesian Networks
  • Coefficients
  • Corporations
  • Filtration
  • Information Retrieval
  • Internet
  • Models
  • Networks
  • New York
  • Organizational Structure
  • Probabilistic Models
  • Probability
  • Questionnaires
  • Research Management
  • Social Media
  • Social Networking Services
  • Social Networks
  • Standards
  • Statistics
  • Test And Evaluation
  • User Interface

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Database Systems and Applications
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML