Selection criterion and implementation of a trouble tracking system: what's in a paradigm?
SIGUCCS '94 Proceedings of the 22nd annual ACM SIGUCCS conference on User services
An algorithm for suffix stripping
Readings in information retrieval
Fault Management in Computer Networks Using Case-Based Reasoning: DUMBO System
ICCBR '99 Proceedings of the Third International Conference on Case-Based Reasoning and Development
A Case-Based Reasoning Approach to the Resolution of Faults in Communication Networks
Proceedings of the IFIP TC6/WG6.6 Third International Symposium on Integrated Network Management with participation of the IEEE Communications Society CNOM and with support from the Institute for Educational Services
Distributed Case-Based Reasoning for Fault Management
AIMS '07 Proceedings of the 1st international conference on Autonomous Infrastructure, Management and Security: Inter-Domain Management
Fault representation in case-based reasoning
DSOM'07 Proceedings of the Distributed systems: operations and management 18th IFIP/IEEE international conference on Managing virtualization of networks and services
Fault Resolution in Case-Based Reasoning
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Mobile peer-to-peer approach for social computing services in distributed environment
Proceedings of the Fourth Symposium on Information and Communication Technology
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The Web has become an important knowledge source for resolving system installation problems and for working around software bugs. In particular, web-based bug tracking systems offer large archives of useful troubleshooting advice. However, searching bug tracking systems can be time consuming since generic search engines do not take advantage of the semi-structured knowledge recorded in bug tracking systems. We present work towards a semantics-based bug search system which tries to take advantage of the semi-structured data found in many widely used bug tracking systems. We present a study of bug tracking systems and we describe how to crawl them in order to extract semi-structured data. We describe a unified data model to store bug tracking data. The model has been derived from the analysis of the most popular systems. Finally, we describe how the crawled data can be fed into a semantic search engine to facilitate semantic search.