Using social annotation and web log to enhance search engine

TL;DR

This paper proposes a hybrid search ranking method combining LPageRank and Social Sim Rank algorithms, utilizing social annotations and web logs to improve search accuracy for music websites.

Contribution

It introduces a novel hybrid model that integrates link-based and social annotation-based ranking algorithms for enhanced search results.

Findings

Improved search accuracy demonstrated on Music Machine Website data.

Effective use of social annotations to create semantic associations.

Hybrid approach outperforms traditional link-based ranking methods.

Abstract

Search services have been developed rapidly in social Internet. It can help web users easily to find their documents. So that, finding a best method search is always an imagine. This paper would like introduce hybrid method of LPageRank algorithm and Social Sim Rank algorithm. LPageRank is the method using link structure to rank priority of page. It doesn't care content of page and content of query. Therefore, we want to use benefit of social annotations to create the latent semantic association between queries and annotations. This model, we use algorithm SocialPageRank and LPageRank to enhance accuracy of search system. To experiment and evaluate the proposed of the new model, we have used this model for Music Machine Website with their web logs.