An Application of Personalized PageRank Vectors: Personalized Search Engine

We introduce a tool which is an application of personalized pagerank vectors such as personalized search engines. We use pre-computed pagerank vectors to rank the search results in favor of user preferences. We describe the design and architecture of our tool. By using pre-computed personalized pagerank vectors we generate search results biased to user preferences such as top-level domain and regional preferences. We conduct a user study to evaluate search results of three different ranking methods such as similarity-based ranking, plain PageRank and weighted (personalized) PageRank ranking methods. We discuss the results of our user study and evaluate the benefits our personalized PageRank vectors in personalized search engines.