Automatic Discovery of the Sequential Accesses From Web Log Data Files via a Genetic Algorithm
Yükleniyor...
Dosyalar
Tarih
2006
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Science Bv
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This paper is concerned with finding sequential accesses from web log files, using 'Genetic Algorithm' (GA). Web log files are independent from servers, and they are ASCII format. Each transaction, whether completed or not, is recorded in the web log files and these files are unstructured for knowledge discovery in database techniques. Data which is stored in web logs have become important for discovering of user behaviors since the using of internet increased rapidly. Analyzing of these log files is one of the important research area of web mining. Especially, with the advent of CRM (Customer Resource Management) issues in business circle, most of the modem firms operating web sites for several purposes are now adopting web-mining as a strategic way of capturing knowledge about potential needs of target customers, future trends in the market and other management factors. Our work (ALMG-Automatic Log Mining via Genetic) has mined web log files via genetic algorithm. When we search the studies about web mining in literature, it can be seen that, GA is generally used in web content and web structure mining. On the other hand, ALMG is a study about web mining usage. The difference between ALMG and other similar works at literature is this point. As for in another work that we are encountering, GA is used for processing the data between HTML tags which are placed at client PC. But ALMG extracts information from data which is placed at server. It is thought to use log files is an advantage for our purpose. Because, we find the character of requests which is made to the server than detect a single person's behavior. We developed an application with this purpose. Firstly, the application is analyzed web log files, than found sequential accessed page groups automatically.
Açıklama
Anahtar Kelimeler
web mining, genetic algorithm, knowledge discovery, sequential access
Kaynak
Knowledge-based Systems
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
19
Sayı
Künye
Arslan, A., Şakiroğlu, M., Tuğ, E., (2006). Automatic Discovery of the Sequential Accesses From Web Log Data Files via a Genetic Algorithm. Knowledge-based Systems, (19), 180-186. Doi: 10.1016/j.knosys.2005.10.008
