CMU's Andrew project: a retrospective
Communications of the ACM - Electronic supplement to the December issue
Intelligent analysis of user interactions with web applications
Proceedings of the 7th international conference on Intelligent user interfaces
The state of the art in automating usability evaluation of user interfaces
ACM Computing Surveys (CSUR)
Building an instructional portal: channeling the writing lab
SIGUCCS '02 Proceedings of the 30th annual ACM SIGUCCS conference on User services
Clustering Web Sessions by Sequence Alignment
DEXA '02 Proceedings of the 13th International Workshop on Database and Expert Systems Applications
Analysis of navigation behaviour in web sites integrating multiple information systems
The VLDB Journal — The International Journal on Very Large Data Bases
Strategies for managing the execution of unauthorized programs on a university computer network
Journal of Computing Sciences in Colleges
Data Mining Methods and Models
Data Mining Methods and Models
LabDisplay: bringing computer lab management into the new millennium
Proceedings of the 33rd annual ACM SIGUCCS conference on User services
A layered framework for evaluating on-line collaborative learning interactions
International Journal of Human-Computer Studies
Evaluating CSCL log files by social network analysis
CSCL '99 Proceedings of the 1999 conference on Computer support for collaborative learning
Current trends in web data analysis
Communications of the ACM - Entertainment networking
Balancing act: community and local requirements in an open source development process
Proceedings of the 34th annual ACM SIGUCCS fall conference: expanding the boundaries
Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage
Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Mining learner profile utilizing association rule for web-based learning diagnosis
Expert Systems with Applications: An International Journal
Educational data mining: A survey from 1995 to 2005
Expert Systems with Applications: An International Journal
Using web metrics to analyze digital libraries
Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries
Insights and surprises from usage patterns: some benefits of data mining in academic online systems
Proceedings of the 36th annual ACM SIGUCCS fall conference: moving mountains, blazing trails
Proceedings of the 38th annual ACM SIGUCCS fall conference: navigation and discovery
Proceedings of the 39th annual ACM SIGUCCS conference on User services
Data Mining User Activity in Free and Open Source Software FOSS/ Open Learning Management Systems
International Journal of Open Source Software and Processes
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Usage data captured and logged by computers has long been an essential source of information for software developers, support services personnel, usability designers, and learning researchers [1, 2]. Whether from mainframes, file servers, network devices, or workstations, the user event data logged in its many forms has served as an essential source of information for those who need to improve software, analyze problems, monitor security, track workflow, report on resource usage, evaluate learning activities etc. With today's generation of open and community source web-based frameworks, however, new challenges arise as to how, where, and when user activity gets captured and analyzed. These frameworks' flexibility in allowing easy integration of different applications, presentation technologies, middleware, and data sources has side effects on usage data: fragmented logs in a wide range of formats often bestrewn across many locations. This paper focuses on common issues faced especially by academic computing support personnel who need to gather and analyze user activity information within heterogeneous, distributed open source web frameworks like Sakai and uPortal. As described in this paper, these kinds of challenges can be met by drawing upon techniques for coordinated distributed event monitoring along with some basic data mining and data visualization approaches. In particular, this paper describes a work-in-progress to develop an approach towards building a distributed capture and analysis systems for a large production deployment of the Sakai Collaboration and Learning Environment in order to meet a wide range of tracking, monitoring, and reporting log analysis in one university setting.