A novel approach for frequent phrase mining in web search engine query streams

被引：0

作者：

Barouni-Ebarhimi, M. ^{[1
]}

Ghorbani, Ali A. ^{[1
]}

机构：

[1] Univ New Brunswick, Fac Comp Sci, Fredericton, NB E3B 5A3, Canada

来源：

CNSR 2007: PROCEEDINGS OF THE FIFTH ANNUAL CONFERENCE ON COMMUNICATION NETWORKS AND SERVICES RESEARCH | 2007年

基金：

加拿大自然科学与工程研究理事会;

关键词：

D O I：

暂无

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

In this paper conceptual frequency rate, a new frequency definition suitable for query stream mining, is introduced. An online single-pass algorithm called OFSD (Online Frequent Sequence Discovery) is given, to mine the set of all conceptual frequent sequences in a data stream whose conceptual frequency rates satisfy a minimum user defined frequency rate. Phrase recommender algorithm is then described based on the set of conceptual frequent phrases extracted by the OFSD algorithm. We have also designed a query recommender algorithm, OQD (Online Query Discovery). OQD is used for comparison purposes along side the proposed phrase recommender algorithm. Simulation results show the efficiency of the proposed Phrase recommender algorithm compared to OQD.

引用

页码：125 / +

页数：2

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