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Title:DOLOČANJE UPORABNIŠKEGA PROFILA Z ANALIZO KLIKOV
Authors:ID Kolar, Diana (Author)
ID Ojsteršek, Milan (Mentor) More about this mentor... New window
Files:.pdf UNI_Kolar_Diana_2011.pdf (1,58 MB)
MD5: 81E35D84A05FD06848A832DC3AE632A2
PID: 20.500.12556/dkum/46ab5511-57d7-4444-ad7e-377cd4f5e741
 
Language:Slovenian
Work type:Bachelor thesis/paper
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu obravnavamo problematiko poosebitve spletnih portalov in gradnjo uporabniških profilov na podlagi analize klikov. V teoretičnem delu smo najprej opisali načine zbiranja in obdelave podatkov iz spletnega strežnika. Nato smo predstavili algoritme podatkovnega rudarjenja in strojnega učenja, ki se uporabljajo za gradnjo skupinskih uporabniških profilov. Za zbiranje podatkov iz spletnega strežnika smo uporabili prosto dostopno orodje Piwik, za obdelavo podatkov s pomočjo podatkovnega rudarjenja pa odprtokodno programsko zbirko Weka. V praktičnem delu smo obdelali podatke o klikih na gradiva v Digitalni knjižnici Univerze v Mariboru (DKUM). Opisali smo način zbiranja podatkov, uporabo orodja Weka za določitev pravil poosebitve gradiv in podali predloge za vključitev poosebitve v DKUM. Na koncu smo prikazali rezultate in podali napotke za nadaljne delo.
Keywords:spletno rudarjenje, poosebitev z analizo klikov, uporabniški profili, Weka, Piwik
Place of publishing:Maribor
Publisher:[D. Kolar]
Year of publishing:2011
PID:20.500.12556/DKUM-20461 New window
UDC:004.6:004.77(043.2)
COBISS.SI-ID:15564054 New window
NUK URN:URN:SI:UM:DK:A08O2TYC
Publication date in DKUM:25.09.2011
Views:2241
Downloads:160
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Secondary language

Language:English
Title:DETERMINATION OF USER PROFILE WITH CLICK STREAM ANALYSIS
Abstract:This diploma work discusses the issue of web portal personalization and user profiles building based on click-stream analysis. In the theoretical part, we describe the methods for collecting and processing data from a Web server. Then we present the algorithms of data mining and machine learning, which are used for the construction of collective user profiles. We used open source tool Piwik to collect data from a web server, and Weka open source database for data processing using data mining. In the practical work we process information about clicks on the items in the Digital Library of the University of Maribor (DLUM). We describe the data collection process, the role of Weka tool for inferring the personalization rules and suggest ideas for DLUM personalization. Finally, we discuss the results and give guidance for further work.
Keywords:web mining, personalizition with clickstream analysis, user profiles, Weka, Piwik


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