Wyniki wyszukiwania - BazTech

Ograniczanie wyników

1 Journal of Telecommunications and Information Technology

1 2015

Znaleziono wyników: 1

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: Web store

Sortuj według:

Ogranicz wyniki do:

A k-Nearest Neighbors Method for Classifying User Sessions in E-Commerce Scenario

Suchacka G., Skolimowska-Kulig M., Potempa A.

Journal of Telecommunications and Information Technology

2015

nr 3

64--69

This paper addresses the problem of classification of user sessions in an online store into two classes: buying sessions (during which a purchase confirmation occurs) and browsing sessions. As interactions connected with a purchase confirmation are typically completed at the end of user sessions, some information describing active sessions may be observed and used to assess the probability of making a purchase. The authors formulate the problem of predicting buying sessions in a Web store as a supervised classification problem where there are two target classes, connected with the fact of finalizing a purchase transaction in session or not, and a feature vector containing some variables describing user sessions. The presented approach uses the k-Nearest Neighbors (k-NN) classification. Based on historical data obtained from online bookstore log files a k-NN classifier was built and its efficiency was verified for different neighborhood sizes. A 11-NN classifier was the most effective both in terms of buying session predictions and overall predictions, achieving sensitivity of 87.5% and accuracy of 99.85%.