Title :
Query logs mining for query suggestion
Author :
Liu, Jianyi ; Zhu, Li ; Wang, Cong
Author_Institution :
Beijing Univ. of Posts & Telecommun., Beijing, China
Abstract :
A query suggestion algorithm is presented based on query logs mining and semantic. First construct a weighted Query-URL bipartite graph from query log data. Then compute the semantic similarity of queries by distance of queries nodes and synonymy similarity to extracting semantic related queries based on graph path. Experiments show that the algorithm is more effective than substring extending algorithm and log mining algorithm in recall and precision.
Keywords :
data mining; graph theory; query processing; log mining algorithm; query logs mining; query semantic similarity; query suggestion algorithm; semantic related query extraction; substring extension algorithm; weighted query-URL bipartite graph; Boosting; Conferences; Data mining; Google; Search engines; Semantics; Telecommunications; query logs; query suggestion; semantic similarity;
Conference_Titel :
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location :
Deng Leng
Print_ISBN :
978-1-4577-0535-9
DOI :
10.1109/AIMSEC.2011.6011080
