An innovative data collection method to eliminate the preprocessing phase in web usage mining

Fuente: arXiv
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Main Authors: Canay, Ozkan, Kocabicak, Umit
Format: Preprint
Published: 2025
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_version_ 1866917887130730496
author Canay, Ozkan
Kocabicak, Umit
author_facet Canay, Ozkan
Kocabicak, Umit
contents The underlying data source for web usage mining (WUM) is commonly thought to be server logs. However, access log files ensure quite limited data about the clients. Identifying sessions from this messy data takes a considerable effort, and operations performed for this purpose do not always yield excellent results. Also, this data cannot be used for web analytics efficiently. This study proposes an innovative method for user tracking, session management, and collecting web usage data. The method is mainly based on a new approach for using collected data for web analytics extraction as the data source in web usage mining. An application-based API has been developed with a different strategy from conventional client-side methods to obtain and process log data. The log data has been successfully gathered by integrating the technique into an enterprise web application. The results reveal that the homogeneous structured data collected and stored with this method is more convenient to browse, filter, and process than web server logs. This data stored on a relational database can be used effortlessly as a reliable data source for high-performance web usage mining activity, real-time web analytics, or a functional recommendation system.
format Preprint
id arxiv_https___arxiv_org_abs_2501_04364
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle An innovative data collection method to eliminate the preprocessing phase in web usage mining
Canay, Ozkan
Kocabicak, Umit
Information Retrieval
68P20, 68T09, 68T35, 68W40, 68U35 68P20, 68T09, 68T35, 68W40, 68U35 68P20, 68T09, 68T35, 68W40, 68U35
H.1.2; H.2.2; H.3.4; H.4.2; K.4.3; K.6.4; D.1.1; D.2.2; D.2.3; D.2.8; D.2.11; C.2.6; C.4; C.5.5
The underlying data source for web usage mining (WUM) is commonly thought to be server logs. However, access log files ensure quite limited data about the clients. Identifying sessions from this messy data takes a considerable effort, and operations performed for this purpose do not always yield excellent results. Also, this data cannot be used for web analytics efficiently. This study proposes an innovative method for user tracking, session management, and collecting web usage data. The method is mainly based on a new approach for using collected data for web analytics extraction as the data source in web usage mining. An application-based API has been developed with a different strategy from conventional client-side methods to obtain and process log data. The log data has been successfully gathered by integrating the technique into an enterprise web application. The results reveal that the homogeneous structured data collected and stored with this method is more convenient to browse, filter, and process than web server logs. This data stored on a relational database can be used effortlessly as a reliable data source for high-performance web usage mining activity, real-time web analytics, or a functional recommendation system.
title An innovative data collection method to eliminate the preprocessing phase in web usage mining
topic Information Retrieval
68P20, 68T09, 68T35, 68W40, 68U35 68P20, 68T09, 68T35, 68W40, 68U35 68P20, 68T09, 68T35, 68W40, 68U35
H.1.2; H.2.2; H.3.4; H.4.2; K.4.3; K.6.4; D.1.1; D.2.2; D.2.3; D.2.8; D.2.11; C.2.6; C.4; C.5.5
url https://arxiv.org/abs/2501.04364