Automatic knowledge base construction using probabilistic extraction, deductive reasoning, and human feedback

Authors:
Daisy Zhe Wang;Yang Chen;Sean Goldberg;Christan Grant;Kun Li
Affiliations:
University of Florida;University of Florida;University of Florida;University of Florida;University of Florida
Venue:
AKBC-WEKEX '12 Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction
Year:
2012

Citing 14
Cited 0

Foundations of statistical natural language processing

Foundations of statistical natural language processing
A guided tour to approximate string matching

ACM Computing Surveys (CSUR)
Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition

Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data

ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data

Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data
BayesStore: managing large, uncertain data repositories with probabilistic graphical models

Proceedings of the VLDB Endowment
Unifying logical and statistical AI

AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Scaling textual inference to the web

EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
PrDB: managing and exploiting rich correlations in probabilistic databases

The VLDB Journal — The International Journal on Very Large Data Bases
The DataPath system: a data-centric analytic processing engine for large data warehouses

Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Analyzing the Amazon Mechanical Turk marketplace

XRDS: Crossroads, The ACM Magazine for Students - Comp-YOU-Ter
Querying probabilistic information extraction

Proceedings of the VLDB Endowment
Tuffy: scaling up statistical inference in Markov logic networks using an RDBMS

Proceedings of the VLDB Endowment
Hybrid in-database inference for declarative information extraction

Proceedings of the 2011 ACM SIGMOD International Conference on Management of data

Quantified Score

Hi-index	0.00

Visualization

Abstract

We envision an automatic knowledge base construction system consisting of three inter-related components. MADden is a knowledge extraction system applying statistical text analysis methods over database systems (DBMS) and massive parallel processing (MPP) frameworks; ProbKB performs probabilistic reasoning over the extracted knowledge to derive additional facts not existing in the original text corpus; CAMeL leverages human intelligence to reduce the uncertainty resulting from both the information extraction and probabilistic reasoning processes.