The visual display of quantitative information
The visual display of quantitative information
Visualizing the structure of the World Wide Web in 3D hyperbolic space
VRML '95 Proceedings of the first symposium on Virtual reality modeling language
Visualizing the evolution of Web ecologies
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Adaptive Web sites: automatically synthesizing Web pages
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Using path profiles to predict HTTP requests
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Predicting users' requests on the WWW
UM '99 Proceedings of the seventh international conference on User modeling
Visualization of navigation patterns on a Web site using model-based clustering
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Web Site Stats: Tracking Hits and Analyzing Web Traffic
Web Site Stats: Tracking Hits and Analyzing Web Traffic
Information Visualization in Data Mining and Knowledge Discovery
Information Visualization in Data Mining and Knowledge Discovery
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Sensemaking of Evolving Web Sites Using Visualization Spreadsheets
INFOVIS '99 Proceedings of the 1999 IEEE Symposium on Information Visualization
Visualizing and discovering web navigational patterns
Proceedings of the 7th International Workshop on the Web and Databases: colocated with ACM SIGMOD/PODS 2004
A logical framework for web data mining based on heterogeneous algebraic structure hierarchies
MMACTEE'06 Proceedings of the 8th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering
| Hi-index | 0.00 |
The goal of web mining is relatively simple: provide both computationally and cognitively efficient methods for improving the value of information to users of the WWW. The need for computational efficiency is well-recognized by the data mining community, which sprung from the database community concern for efficient manipulation of large datasets. The motivation for cognitive efficiency is more elusive but at least as important. In as much as cognitive efficiency can be informally construed as ease of understanding, then what is important is any tool or technique that presents cognitively manageable abstractions of large datasets.We present our initial development of a framework for gathering, analyzing, and redeploying web data. Not dissimilar to conventional data mining, the general idea is that good use of web data first requires the careful selection of data (both usage and content data), the deployment of appropriate learning methods, and the evaluation of the results of applying the results of learning in a web application. Our framework includes tools for building, using, and visualizing web abstractions.We present an example of the deployment of our framework to navigation improvement. The abstractions we develop are called Navigation Compression Models (NCMs), and we show a method for creating them, using them, and visualizing them to aid in their understanding.