Computer Science ›› 2019, Vol. 46 ›› Issue (10): 295-398.doi: 10.11896/jsjkx.180801473

Special Issue: Medical Imaging

• Graphics,Image & Pattern Recognition • Previous Articles     Next Articles

Research and Improvement of Web Fingerprint Identification Algorithm Based on Cosine Measure

TANG Wen-liang1, TANG Shu-fang2, ZHANG Ping2   

  1. (School of Information Engineering,East China Jiaotong University,Nanchang 330013,China)1
    (School of Software,East China Jiaotong University,Nanchang 330013,China)2
  • Received:2018-08-09 Revised:2018-08-27 Online:2019-10-15 Published:2019-10-21

Abstract: In order to realize the accurate identification of Web fingerprints in the Web fingerprint database,it is necessary to study the Web fingerprint identification algorithm.When the current fingerprint recognition algorithm is used to identify the Web fingerprint in the Web fingerprint database,there is an error between the recognition result and the actual result,and the recognition takes a long time,which result in low recognition accuracy and recognition efficiency.Based on the cosine measure,a Web fingerprint identification algorithm was proposed.The source fingerprint method is used to select the Web fingerprint in the four aspects of structural features,static files,cookie design and keywords,and a Web fingerprint database is established.Firstly,the characteristics of the data in the Web fingerprint database are extracted,and the abnormal data existing in the Web fingerprint database are removed according to the feature extraction result.Then,the cosine distance function is used as the similarity measurement function,and the K-means algorithm is used to cluster the Web fingerprints in the Web fingerprint database.Finally,the identification of the web fingerprint is completed according to the clustering result.The experimental results show that the proposed method can accurately complete the Web fingerprint identification in the Web fingerprint database in a short time,and has the advantages of high recognition accuracy and high recognition efficiency.

Key words: Cosine measure, Recognition algorithm, Web fingerprint

CLC Number: 

  • TP391.41
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