Material Detail

Pure Spreading Activation is Pointless

Pure Spreading Activation is Pointless

This video was recorded at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Bled 2009. Spreading activation is a popular technique for retrieving and ranking indirectly related information by activating query items and spreading their activation along relatedness links. Almost every use of the technique is accompanied by its own set of restrictions on the dynamics, though, and the usual motivation is a reduced computational demand or an improved t to specific types of data. We show that in linear, constraint-free scenarios spreading activation would actually yield query-independent results, so that applications crucially depend on the imposed restrictions. To avoid this undesirable behavior, we study natural modifications that ensure query-dependent results even without heuristic restrictions and provide experimental evidence for their effectiveness.


  • User Rating
  • Comments
  • Learning Exercises
  • Bookmark Collections
  • Course ePortfolios
  • Accessibility Info

More about this material


Log in to participate in the discussions or sign up if you are not already a MERLOT member.