Knowledge Discovery From Web Usage Data: Survey

Raju, G. T.; Sathyanarayana, P. S.; Patnak, L. M.

doi:10.1142/9781860948534_0026

Cited by 7 publications

(7 citation statements)

References 2 publications

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“…Munk et al (2010) adopted 10-minute timeout intervals for session identification and identified path completion pre-processing as an important step for improving the quality of extracted data. Similarly, Raju and Satyanarayana (2008) proposed a complete pre-processing methodology and suggested the use of 30-minute session timeout intervals.…”

Section: Process and Heuristicsmentioning

confidence: 99%

Does Time-on-task Estimation Matter? Implications on Validity of Learning Analytics Findings

et al. 2016

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ABSTRACT:With widespread adoption of Learning Management Systems (LMS) and other learning technology, large amounts of data -commonly known as trace data -are readily accessible to researchers. Trace data has been extensively used to calculate time that students spend on different learning activities -typically referred to as time-on-task. These measures are used to build predictive models of student learning in order to understand and improve learning processes. While time-on-task measures have been used in Learning Analytics research, the consequences of their use are not fully described or examined. This paper presents findings from two experiments regarding different time-on-task estimation methods and their influence on research findings. Based on modelling different student performance measures with popular statistical methods in two datasets (one online, one blended), our findings indicate that time-on-task estimation methods play an important role in shaping the final study results, particularly in online settings where the amount of interaction with LMS is typically higher. The primary goal of this paper is to raise awareness and initiate debate on the important issue of time-on-task estimation within the broader learning analytics community. Finally, the paper provides an overview of commonly adopted time-on-task estimation methods in educational and related research fields.

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Section: Process and Heuristicsmentioning

confidence: 99%

Does Time-on-task Estimation Matter? Implications on Validity of Learning Analytics Findings

et al. 2016

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“…Therefore, it is of paramount importance to acquire and further develop techniques that conveniently and efficiently metamorphose web usage data to propitious knowledge discovery (Liu, 2011;Raju & Satyanarayana, 2008). The ideal tactic to gain knowledge regarding web-page performance issues is to examine weblog transactions (Facca & Lanzi, 2005).…”

Section: Measuring Web Site Performancementioning

confidence: 99%

Concurrent multiresponse non-linear screening: Robust profiling of webpage performance

Besseris

2015

European Journal of Operational Research

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“…A session is a sequence of requests made by a single user with a unique IP address on a particular web domain during a specified period of time. Several methods to identify sessions are discussed in [13]- [15]. We are combining two trivial approaches (time & navigation oriented) with our concept name match approach.…”

Section: A Preprocessingmentioning

confidence: 99%

A New Web Usage Mining Approach for Website Recommendations Using Concept Hierarchy and Website Graph

Kumar¹,

Guruprasad²,

Kumar³

et al. 2014

IJCEE

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Abstract-To have a clear and well organized website have become one of the primary objectives of enterprises and organizations. Website administrators may want to know how they can attract visitors, which pages are being accessed most/least frequently, which part of website is most/least popular and need enhancement, etc. Of late, the rapid growth of the use of Internet has made automatic knowledge extraction from server log files a necessity. Analysis of server log data can provide significant and useful information. Information provided can help to find out user intuition. This can improve the effectiveness of the Web sites by adapting the information structure to the users' behavior. Most of the Web Usage Mining techniques use Server log files as raw data to produce the user navigation patterns. Along with the server access log file, we incorporate Website knowledge (i.e., Concept hierarchy and Website Graph) into the web usage mining phases. This incorporation can lead to superior patterns. These patterns can be used to provide set of recommendations for the web site which can be deployed by web site administrator for website enhancement. In this paper, we have considered the server log files of the Website www.enggresources.com for overall study and analysis.Index Terms-Concept based website graph, concept hierarchy, web mining, web usage mining, website graph.

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Knowledge Discovery From Web Usage Data: Survey

Cited by 7 publications

References 2 publications

Does Time-on-task Estimation Matter? Implications on Validity of Learning Analytics Findings

Does Time-on-task Estimation Matter? Implications on Validity of Learning Analytics Findings

Concurrent multiresponse non-linear screening: Robust profiling of webpage performance

A New Web Usage Mining Approach for Website Recommendations Using Concept Hierarchy and Website Graph

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