Learning in graphical models
Optical character recognition
Modern Information Retrieval
Off-Line Handwritten Word Recognition Using a Hidden Markov Model Type Stochastic Network
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Efficient Indexing Technique for Full Text Databases
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Probabilistic Retrieval of OCR Degraded Text Using N-Grams
ECDL '97 Proceedings of the First European Conference on Research and Advanced Technology for Digital Libraries
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
A Fast Regular Expression Indexing Engine
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Finite-state transducers in language and speech processing
Computational Linguistics
Dictionary matching and indexing with errors and don't cares
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Working Models for Uncertain Data
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
MauveDB: supporting model-based user views in database systems
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Creating probabilistic databases from information extraction models
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
Efficient query evaluation on probabilistic databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Event queries on correlated probabilistic streams
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
BayesStore: managing large, uncertain data repositories with probabilistic graphical models
Proceedings of the VLDB Endowment
Approximate lineage for probabilistic databases
Proceedings of the VLDB Endowment
Graphical Models, Exponential Families, and Variational Inference
Foundations and Trends® in Machine Learning
Relaxed maximum a posteriori fault identification
Signal Processing
Probabilistic Networks and Expert Systems: Exact Computational Methods for Bayesian Networks
Probabilistic Networks and Expert Systems: Exact Computational Methods for Bayesian Networks
Exploiting Lineage for Confidence Computation in Uncertain and Probabilistic Databases
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Access Methods for Markovian Streams
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
SPROUT: Lazy vs. Eager Query Plans for Tuple-Independent Probabilistic Databases
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Ef?cient Query Evaluation over Temporally Correlated Probabilistic Streams
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Indexing correlated probabilistic databases
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
General indexation of weighted automata: application to spoken utterance retrieval
SpeechIR '04 Proceedings of the Workshop on Interdisciplinary Approaches to Speech Indexing and Retrieval at HLT-NAACL 2004
OpenFst: a general and efficient weighted finite-state transducer library
CIAA'07 Proceedings of the 12th international conference on Implementation and application of automata
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
UPI: a primary index for uncertain databases
Proceedings of the VLDB Endowment
Local structure and determinism in probabilistic databases
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Report on the first workshop on innovative querying of streams
ACM SIGMOD Record
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The digitization of scanned forms and documents is changing the data sources that enterprises manage. To integrate these new data sources with enterprise data, the current state-of-the-art approach is to convert the images to ASCII text using optical character recognition (OCR) software and then to store the resulting ASCII text in a relational database. The OCR problem is challenging, and so the output of OCR often contains errors. In turn, queries on the output of OCR may fail to retrieve relevant answers. State-of-the-art OCR programs, e.g., the OCR powering Google Books, use a probabilistic model that captures many alternatives during the OCR process. Only when the results of OCR are stored in the database, do these approaches discard the uncertainty. In this work, we propose to retain the probabilistic models produced by OCR process in a relational database management system. A key technical challenge is that the probabilistic data produced by OCR software is very large (a single book blows up to 2GB from 400kB as ASCII). As a result, a baseline solution that integrates these models with an RDBMS is over 1000x slower versus standard text processing for single table select-project queries. However, many applications may have quality-performance needs that are in between these two extremes of ASCII and the complete model output by the OCR software. Thus, we propose a novel approximation scheme called Staccato that allows a user to trade recall for query performance. Additionally, we provide a formal analysis of our scheme's properties, and describe how we integrate our scheme with standard-RDBMS text indexing.