Learning regular sets from queries and counterexamples
Information and Computation
Determination of the Script and Language Content of Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Twenty Years of Document Image Analysis in PAMI
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stochastic Finite Learning of the Pattern Languages
Machine Learning
Proceedings of the 4th International Colloquium on Grammatical Inference
ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
Relational Databases for Querying XML Documents: Limitations and Opportunities
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Potter's Wheel: An Interactive Data Cleaning System
Proceedings of the 27th International Conference on Very Large Data Bases
Finding patterns common to a set of strings (Extended Abstract)
STOC '79 Proceedings of the eleventh annual ACM symposium on Theory of computing
Document Image Layout Comparison and Classification
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Reading handwritten US census forms
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
Architectural styles and the design of network-based software architectures
Architectural styles and the design of network-based software architectures
Interactive Tools for Pattern Discovery
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
The WANDAML Markup Language for Digital Document Annotation
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Grammatical Inference in Bioinformatics
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Engineering diagnosis often involves analyzing complex records of system states printed to large, textual log files. Typically the logs are designed to accommodate the widest debugging needs without rigorous plans on formatting. As a result, critical quantities and flags are mixed with less important messages in a loose structure. Once the system is sealed, the log format is not changeable, causing great difficulties to the technicians who need to understand the event correlations. We describe a modular system for analyzing such logs where document analysis, report generation, and data exploration tools are factored into generic, reusable components and domain-dependent, isolated plug-ins. The system supports incremental, focused analysis of complicated symptoms with minimal programming effort and software installation. We discuss important concerns in the analysis of logs that sets it apart from understanding natural language text or rigorously structured computer programs. We highlight the research challenges that would guide the development of a deep analysis system for many kinds of semi-structured documents.