iMecho: an associative memory based desktop search system

  • Authors:
  • Jidong Chen;Hang Guo;Wentao Wu;Wei Wang

  • Affiliations:
  • EMC Research China, Beijing, China;EMC Research China, Beijing, China;Fudan University, Shanghai, China;Fudan University, Shanghai, China

  • Venue:
  • Proceedings of the 18th ACM conference on Information and knowledge management
  • Year:
  • 2009

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Abstract

Traditional desktop search engines only support keyword based search that needs exact keyword matching to find resources. However, users generally have a vague picture of what is stored but forget the exact location and keywords of the resource. According to observations of human associative memory, people tend to remember things from some memory fragments in their brains and these memory fragments are connected by memory cues of user activity context. We developed iMecho (My Memory Echo), an associative memory based desktop search system, which exploits such associations and contexts to enhance traditional desktop search. Desktop resources are connected with semantic links mined from explicit and implicit user activities according to specific access patterns. Using these semantic links, associations among memory fragments can be built or rebuilt in a user's brain during a search. Moreover, our personalized ranking scheme uses these links together with a user's personal preferences to rank results by both relevance and importance to the user. In addition, the system provides a faceted search feature and association graph navigation to help users refine and associate search results generated by full-text keyword search. Our experiments investigating precision and recall quality of iMecho prototype show that the association-based search system is superior to the traditional keyword search in personal search engines since it is closer to the way that human associative memory works.