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1 – 2 of 2Bahjat Fatima, Huma Ramzan and Sohail Asghar
The purpose of this paper is to critically analyze the state-of-the-art session identification techniques used in web usage mining (WUM) process in terms of their limitations…
Abstract
Purpose
The purpose of this paper is to critically analyze the state-of-the-art session identification techniques used in web usage mining (WUM) process in terms of their limitations, features, and methodologies.
Design/methodology/approach
In this research, systematic literature review has been conducted using review protocol approach. The methodology consisted of a comprehensive search for relevant literature over the period of 2005-2015, using four online database repositories (i.e. IEEE, Springer, ACM Digital Library, and ScienceDirect).
Findings
The findings revealed that this research area is still immature and existing literature lacks the critical review of recent session identification techniques used in WUM process.
Originality/value
The contribution of this study is to provide a structured overview of the research developments, to critically review the existing session identification techniques, highlight their limitations and associated challenges and identify areas where further improvements are required so as to complement the performance of existing techniques.
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Keywords
Juan D. Velásquez, Sebastían A. Ríos, Alejandro Bassi, Hiroshi Yasuda and Terumasa Aoki
Since the creation of the web, the designers are looking for friendlier ways of make web page contents, which pictures, sounds, movies and free texts attract the users’ interest…
Abstract
Since the creation of the web, the designers are looking for friendlier ways of make web page contents, which pictures, sounds, movies and free texts attract the users’ interest. Special attention receive the text content, because is the most frequently parameter used to retrieve information from the web. A simple way in order to understand the user’s text preferences, could be collect the words used in a searching. However, this information is only well‐know for the owner of the specific searching engine. In this paper we introduce a methodology in order to extract the most interest words for a user in a particular web site, based of the user browsing behavior and the web page text content. The methodology was tested using data originated in a bank web site showing the effectiveness of our approach.
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