Automatic Discovery of the Sequential Accesses From Web Log Data Files via a Genetic Algorithm

Basit Öğe Kaydı
dc.contributor.authorTuğ, Emine
dc.contributor.authorŞakiroğlu, Merve
dc.contributor.authorArslan, Ahmet
dc.date.accessioned2020-03-26T17:03:06Z
dc.date.available2020-03-26T17:03:06Z
dc.date.issued2006
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThis 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.en_US
dc.identifier.citationArslan, 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
dc.identifier.doi10.1016/j.knosys.2005.10.008en_US
dc.identifier.endpage186en_US
dc.identifier.issn0950-7051en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage180en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.knosys.2005.10.008
dc.identifier.urihttps://hdl.handle.net/20.500.12395/20349
dc.identifier.volume19en_US
dc.identifier.wosWOS:000239182800004en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorTuğ, Emine
dc.institutionauthorŞakiroğlu, Merve
dc.institutionauthorArslan, Ahmet
dc.language.isoenen_US
dc.publisherElsevier Science Bven_US
dc.relation.ispartofKnowledge-based Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectweb miningen_US
dc.subjectgenetic algorithmen_US
dc.subjectknowledge discoveryen_US
dc.subjectsequential accessen_US
dc.titleAutomatic Discovery of the Sequential Accesses From Web Log Data Files via a Genetic Algorithmen_US
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
20349.pdf
Boyut:
267.61 KB
Biçim:
Adobe Portable Document Format
Açıklama:
Makale Dosyası
İndir

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu