MINING REFERRAL AUDIENCES OF A NEWS WEBSITE

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HASSANIAN ESFAHANI ROYA; KARGAR MOHAMMAD JAVAD

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2015 | Issue:1

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Title

MINING REFERRAL AUDIENCES OF A NEWS WEBSITE

Author(s)

HASSANIAN ESFAHANI ROYA | KARGAR MOHAMMAD JAVAD

Keywords

TERMS- REFERRAL ACQUISITION

DATA MINING

K-MEANS CLUSTERING

NEWS WEBSITE

Abstract

WEB TRAFFIC ANALYSIS IS A KNOWN ONLINE MARKETING APPROACH. THIS STUDY ANALYZES THE REFERRAL ACQUISITIONS OF A NEWS WEBSITE BY APPLYING DATA MINING TECHNIQUES. RESEARCH RESULTS SHOW THAT THERE IS NO SIGNIFICANT RELATIONSHIP BETWEEN THE NUMBER OF REFERRAL VISITS FROM A SPECIFIC REFERRER'S WEBSITE AND IT'S ALEXA RANK. ALSO THE REFERRAL AUDIENCE FIT INTO THREE CLUSTERS USING K-MEANS SQUARED EUCLIDEAN DISTANCE CLUSTERING ALGORITHM. EXAMINING THE DATASET SHOWS THAT OUR CLUSTERING METHOD IS CAPABLE OF RECOGNIZING AUTOMATIC NEWS AGGREGATOR WEBSITES THROUGH REFERRER WEBSITES.

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APA: Copy

HASSANIAN ESFAHANI, ROYA, & KARGAR, MOHAMMAD JAVAD. (2015). MINING REFERRAL AUDIENCES OF A NEWS WEBSITE. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/948794/en

Vancouver: Copy

HASSANIAN ESFAHANI ROYA, KARGAR MOHAMMAD JAVAD. MINING REFERRAL AUDIENCES OF A NEWS WEBSITE. 2015. Available from: https://sid.ir/paper/948794/en

IEEE: Copy

ROYA HASSANIAN ESFAHANI, and MOHAMMAD JAVAD KARGAR, “MINING REFERRAL AUDIENCES OF A NEWS WEBSITE,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2015, [Online]. Available: https://sid.ir/paper/948794/en

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