Social Network Analysis of yahoo web-search engine query logs
This addresses a problem for data analysts and search engine users by improving query relevance, but it appears incremental as it builds on existing network analysis methods.
The paper tackled the challenge of search engines recognizing users' specific interests from initial queries by building query networks from web search engine logs, with nodes as queries and edges showing semantic relatedness, but no concrete results or numbers were provided.
Web is now the undisputed warehouse for information. It can now provide most of the answers for modern problems. Search engines do a great job by combining and ranking the best results when the users try to search for any particular information. However, as we know 'with great power comes great responsibility', it is not an easy task for data analysts to find the most relevant information for the queries. One major challenge is that web search engines face difficulties in recognizing users' specific search interests given his initial query. In this project, we have tried to build query networks from web search engine query logs, with the nodes representing queries and the edges exhibiting the semantic relatedness between Queries.