Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Learning Information Extraction Rules for Semi-Structured and Free Text
Machine Learning - Special issue on natural language learning
Information Extraction with HMM Structures Learned by Stochastic Optimization
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
FACTS: An Approach to Unearth Legacy Contracts
WEC '04 Proceedings of the First IEEE International Workshop on Electronic Contracting
Queue - Semi-structured Data
A framework for projected clustering of high dimensional data streams
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Detecting distance-based outliers in streams of data
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Tapping into unstructured data: integrating unstructured data and textual analytics into business intelligence
DW 2.0: The Architecture for the Next Generation of Data Warehousing
DW 2.0: The Architecture for the Next Generation of Data Warehousing
Foundations and Trends in Databases
Data integration flows for business intelligence
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Leveraging web streams for contractual situational awareness in operational BI
Proceedings of the 2010 EDBT/ICDT Workshops
Business intelligence on complex graph data
Proceedings of the 2012 Joint EDBT/ICDT Workshops
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In today’s enterprise, business processes and business intelligence applications need to access and use structured and unstructured information to extend business transactions and analytics with as much adjacent data as possible. Unfortunately, all this information is scattered in many places, in many forms; managed by different database systems, document management systems, and file systems. Companies end up having to build one-of-a-kind solutions to integrate these disparate systems and make the right information available at the right time and in the right form for their business transactions and analytical applications. Our goal is to create an operational business intelligence platform that manages all the information required by business transactions and combines facts extracted from unstructured sources with data coming from structured sources along the DW2.0 pipeline to enable actionable insights. In this paper, we give an overview of the platform functionality and architecture focusing in particular in the information extraction and analytics layers and their application to situational awareness for epidemics medical response.