Personalized PageRank: a user sensitive affair. Shhhhhh be very quiet, we’re hunting information retrievers Let's bounce off in a new direction, begin anew as it where and look at what resides in the craniums that index the world’s information.
I would like to introduce to you a concept, (much like page segmentation),that isn’t a new one. It has been in front you all this time, but like a black hatter at dollar domain bazzar, you were to busy to notice. As the regular Trail riders would know, we’ve gone from extreme interest in behavioural metrics and personalized search to more tempered views of potential usage.
Personalized pagerank. The PageRank algorithm, as used by the Google search engine, exploits the linkage structure of the web to compute global "importance" scores that can be used to influence the ranking of search results.
While the use of PageRank has proven very effective, the web's rapid growth in size and diversity drives an increasing demand for greater flexibility in ranking. Ideally, each user should be able to define his own notion of importance for each individual query. While in principle a personalized version of the PageRank algorithm can achieve this task, its naive implementation requires computing resources far beyond the realm of feasibility. Query Log Mining.