An improved algorithm of mining preferred browsing paths

Author

Hongbo Li ; Ning Wang ; Yu Wu

Author_Institution

Inst. of Web Intell., Chongqing Univ. of Posts & Telecommun., Chongqing, China

fYear

2014

fDate

19-21 Aug. 2014

Firstpage

807

Lastpage

811

Abstract

Existing algorithms of mining preferred browsing paths just consider the influence of user visiting times, but ignore the accuracy influenced by other factors. In order to solve the problem, an improved algorithm which imports page similarity and support-preference concepts is proposed. Firstly a Web-log-based user access matrix is set up. Then by calculating the angel cosine similarity and support-preference, the 2-items preferred browsing sub-path set is obtained. Finally all the sub-paths are combined. Experiments show that the algorithm is more accurate and efficient.

Keywords

Internet; data mining; human computer interaction; system monitoring; UPBPA; Web-log-based user access matrix; angle cosine similarity; page similarity; preferred browsing path mining; support-preference concepts; use preferred browsing paths algorithm; user visiting times; Accuracy; Algorithm design and analysis; Computers; Data mining; Educational institutions; Uniform resource locators; Vectors; Preferred Browsing Paths; Similarity Matrix; Support-preference;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2014 10th International Conference on

Conference_Location

Xiamen

Print_ISBN

978-1-4799-5150-5

Type

conf

DOI

10.1109/ICNC.2014.6975941

Filename

6975941