Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Query logs of search engines record a huge amount of data about the actions of the users who search for information on the b. Hence, they contain a alth of valuable knowledge about the users' interests and preferences, as ll as the implicit feedback that b searchers provide when they click on the results obtained for their queries.#R##N##R##N#  propose a general and completely unsupervised methodology for query-log analysis, which consists of aggregating multiple graph representations of a query log, tailored to capturing different semantic information. The combination is carried out by applying simple but efficient graph-mining techniques.  show that our approach achieves very good performance for two different applications, which are classifying query transitions and recognizing spam queries.
['Ilaria Bordino', 'Debora Donato', 'Ricardo A. Baeza-Yates']
I am writing a research paper on a idea Coniunge et impera: multiple-graph mining for query-log analysis
[{"from": "human", "value": "I am writing a research paper on a idea Coniunge et impera: multiple-graph mining for query-log analysis"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Query logs of search engines record a huge amount of data about the actions of the users who search for information on the b. Hence, they contain a alth of valuable knowledge about the users' interests and preferences, as ll as the implicit feedback that b searchers provide when they click on the results obtained for their queries.#R##N##R##N#  propose a general and completely unsupervised methodology for query-log analysis, which consists of aggregating multiple graph representations of a query log, tailored to capturing different semantic information. The combination is carried out by applying simple but efficient graph-mining techniques.  show that our approach achieves very good performance for two different applications, which are classifying query transitions and recognizing spam queries."}]