A personalized search engine research based on Bloom filter

Personalization of search engines is to achieve retrieval for different users with different interests. In this paper, we propose a personalized search engine based on Bloom filter. Bloom filter, an effective space data structure, is used in the research of personalized search. The user interest model based on Bloom filter contains one standard Bloom filter and multiple Counting Bloom filters, and the design of multi-level structure can accurately represent weights of interest keywords. According to this structure, the interest adjustment algorithm and the keywords matching algorithm are proposed at the same time. After experimental evaluation, the results indicate that this model has not only high space efficiency but high retrieval accuracy as well.