A novel prediction model based on hierarchical characteristic of web site

Lee, Chu-Hui; Lo, Yu-Lung; Fu, Ya–Yuan

doi:10.1016/j.eswa.2010.08.128

Cited by 21 publications

(10 citation statements)

References 24 publications

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“…Major online stores, such as Amazon, use WUM techniques to recommend products to clients based on clients' previous purchases [3]. In general, WUM can be used to enhance web page usability by personalizing the web page toward a specific user experience [1] [4], clustering groups of similar users [5] [6], or predicting future users' behavior [7]. However, many of WUM techniques rely on the server logs data in the analysis [8].…”

Section: Introductionmentioning

confidence: 99%

A Generic Framework for Collecting and Mining Client Paradata for Web Applications

Khasawneh¹,

Al-Salman²,

Al-Hammouri³

et al. 2012

JETWI

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In this paper, we propose a general framework to track and collect user interactions with dynamic webpages. Using the AJAX, PHP, and MySQL technologies, we implement and realize the client-side-scripting framework to collect client paradata in a seamlessly manner. Being stored in a persistent storage at the server, the data were then structured and analyzed to understand the user behavior. We exploited the framework by applying it to two online systems: E-Survey and E-Commerce web applications. In the E-Survey system, we collected student interactions while filling in an online feedback form. We then used the collected data to model the user behavior. With the resultant model, we can infer whether a student is mindful and conscious while answering the feedback questions. In the E-Commerce system, we collected user interactions with a products page. Using a generated classifier, we can predict a user selection based on his or her navigation pattern on the page.

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Section: Introductionmentioning

confidence: 99%

A Generic Framework for Collecting and Mining Client Paradata for Web Applications

Khasawneh¹,

Al-Salman²,

Al-Hammouri³

et al. 2012

JETWI

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“…And lastly kmeans clustering algorithm is implemented using the most appropriate number of clusters and distance measures. Lee and Fu proposed a two level prediction model in 2008 [4]. Here prediction scope is reduced as it works in two levels.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, we get K relevant matrices R to represent K cluster views [4]. In step two, these matrices will be released out for creating index table which will be used for view selection based on user's browsing behavior at that time.…”

Section: Overview Of the Proposed Prediction Frameworkmentioning

confidence: 99%

Prediction Model Using Web Usage Mining Techniques

Bhart¹

2014

IJCATR

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Popularity of WWW increasing day by day which results in the increase of web based services , due to which web is now largest data repository. In order to handle this incremental nature of data various prediction techniques are used. If the prefetched pages are not visited by user in their subsequent access there will be wastage network bandwidth as it is in limited amount. So there is critical requirement of accurate prediction method. As the data present on web is heterogeneous in nature and incremental in nature, during the pre-processing step hierarchical clustering technique is used. Then using Markov model category and page prediction is done and lastly page filtering is done using keywords.

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“…They supposed the hierarchical properties of the website are incorporated into the hierarchical folder structure of web pages. The method decreases the size of the candidate set, increasing the effectiveness of the mining process [4].…”

Section: Literature Reviewmentioning

confidence: 99%

Cost Estimation of the Homogeneous Websites Using Hyper-links Analysis

Al-Hagery¹

2015

IJMECS

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Abstract-Websites hide thousands of links and sub-links. Websites' links contain a huge amount of information and knowledge. This research concentrates mainly on the difficulty of early prediction of web structure size at the beginning of Website Development Life Cycle (WDLC), especially during planning and gathering requirements. There is a lack of finding an appropriate mechanism to assist developers in these steps. The objective of this research is to measure the logical size of a website in order to predict the development time and cost earlier before the development process based on based on the website contents and its internal structure. This objective includes three sub-objectives. First, analysis of seven classes of websites to collect real data sets. Second, extracting a set of relations from the gathered data and use these relations to establish a proposed model. Third, apply the gathered data in the proposed model to predict the development time and cost of a website. This research provides strong and important results that would help developers before the development process to predict total development time and cost which in turn used directly to specify development tools, draw project plan, formulate contract conditions and determine project duration and final price.

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A novel prediction model based on hierarchical characteristic of web site

Cited by 21 publications

References 24 publications

A Generic Framework for Collecting and Mining Client Paradata for Web Applications

A Generic Framework for Collecting and Mining Client Paradata for Web Applications

Prediction Model Using Web Usage Mining Techniques

Cost Estimation of the Homogeneous Websites Using Hyper-links Analysis

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