WebKIV: visualizing structure and navigation for Web mining applications

Abstract

Abstract

Application and Significance of Web Usage Mining in the 21st Century: A Literature Review

“…The most used techniques are:  Visualization: this is a very successful method to help in understanding user behaviour. Several tools have been developed to apply this method; for example, WebKIV, which is a tool that provides structural visualization for small and large web structures, web navigation, which is for individuals and aggregate user navigation patterns, and result comparison [10].  On-Line Analytical Processing (OLAP) tools enable users to analyze multi-dimensional data from multiple viewpoints.…”

Visual Data Mining of Web Navigational Data

“…While there are many systems [6,15,16,19,20] that focus on visualizing data mining results and the source data, Ankerst et al [2,3] developed the PBC system to visualize decision tree construction and the data classification process. J. Han et al proposed the RuleViz model [10] and developed the DTViz [9] and CVizT [8] systems to visualize the decision tree and classification rule construction process to use visual space in a more efficient way.…”

“…The graph has been used to visualize web site evolution, web usage trends over time, and evaluation of information "foraging" [5]. The WebKIV [15] system implemented the disktree representation to compare web navigational patterns and defined a three dimensional scale to describe the web visualization task. A visual web mining prototype framework was designed in [4] to describe the object manipulation for visual data mining purposes.…”

“…One of the most popular methods to visualize web structure is Chi's radial disktree representation [6]. Since the radial tree layout uses screen space more efficiently than other layout methods, many systems [4,5,15,16] adapted the disktree method to visualize web structure. Other similar approaches include the ConeTree [17] and the Hyperbolic tree [12].…”

Visualizing and discovering web navigational patterns

“…Although web visualization is a complex task, researchers can begin to understand its characteristics by decomposing the task into the three dimension of scale, first proposed in [7], of web structure visualization, representation of aggregate and individual navigation usage behaviour, and the comparative display of navigation improvement methods. The authors also present Web Knowledge and Information Visualization (WEBKIV), a system that combines the strategies from several other web visualization tools, as part of the WebFrame project [11], which presents a initial development of a framework for gathering, analyzing, and re-deploying web data.…”