MONGOOSE - Overview
Data Analytics technology is becoming increasingly important as people try to extract as much value as possible from their most valuable resource - the information around them, whether in their organizations or freely and publicly available. While many data analytics efforts are focused on deriving information from a particularly interesting, and often difficult, question, these projects tend to spend most of their cycles acquiring and ingesting data. Thus, the focus of these efforts is more directed towards data ingestion.

MONGOOSE is
  1. A suite of technologies that one can plug domain knowledge cartridges into and that outputs data suitable for OLAP or BI consumption. One plugs in small amounts of domain knowledge that involves pulling in unstructured, semi-structured and structured data, and MONGOOSE converts it all into structured form.
  2. A Platform for Worst-Case Scenario Workflow Management. MONGOOSE is built on the assumption that failure happens and it must be handled quickly and seamlessly, such that it does not stop or hinder information ingest.
  3. A Platform for Community-Based Information Extraction around specific phenomenon that can be fed into statistical analysis tools.

MONGOOSE - Presentations



MONGOOSE - Publications

  1. Varun Bhagwan, Tyrone Grandison, Alfredo Alba, Daniel Gruhl, Jan Pieper. "MONGOOSE: MONitoring Global Online Opinions via Semantic Extraction". Proc of 2009 Service Quality and Assurance Management (SQAM) workshop, September 21-25, 2009, Bangalore, India.
  2. Varun Bhagwan, Tyrone Grandison, Daniel Gruhl, "Sound Index: Music Charts By The People, For The People". Communications of the ACM. September 2009. Vol 52, No 9.
  3. Alfredo Alba, Varun Bhagwan, Tyrone Grandison, Daniel Gruhl, Jan Pieper. "Change Detection and Correction Facilitation for Web Applications and Services". The Proceedings of the 7th IEEE International Conference on Web Services (ICWS 2009). Los Angeles, CA, USA. July 2009.
  4. Varun Bhagwan, Tyrone Grandison. "Deactivation of Unwelcomed Deep Web Extraction Services through Random Injection". The Proceedings of the 7th IEEE International Conference on Web Services (ICWS 2009). Los Angeles, CA, USA. July 2009.
  5. Tyrone Grandison, Christan Grant, Kun Liu, varun Bhagwan, Tarun Thakur."Leveraging Online Data To Deliver Better Decision Support For Personalized Chronic Disease Management", American Medical Informatics Association (AMIA) 2009 Spring Congress. Orlando, Florida. May 28-30, 2009.
  6. Kun Liu, Tyrone Grandison, Evimaria Terzi, Tarun Thakur. "Optimizing The Delivery Of Social Services", American Medical Informatics Association (AMIA) 2009 Spring Congress. Orlando, Florida. May 28-30, 2009.
  7. Tyrone Grandison, Daniel Gruhl."Turning Web X.0 Data Into Competitive Advantage". The First Caribbean Conference on Information and Communications Technology (CCICT 2009). Kingston, Jamaica. March 2009.
  8. Zack Zakharian, Manvendra Mishra, Senthil Chandramohan. "Cars 2.0". Masters Thesis, San Jose State University, December 2008.
  9. Alfredo Alba, Varun Bhagwan, Tyrone Grandison. "Accessing The Deep Web: When Good Ideas Go Bad". To appear in the Proceedings of the ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA). Nashville, Tennessee. October 2008.
  10. Alfredo Alba, Varun Bhagwan, Tyrone Grandison, Daniel Gruhl, Jan Pieper, "Text Analytics and Integration of Web 2.0 Sources to Transform Media & Entertainment". Information On Demand (IOD). Las Vegas, Nevada. October 2008.
  11. Alfredo Alba, Varun Bhagwan, Julia Grace, Daniel Gruhl, Kevin Haas, Meenakshi Nagarajan, Jan Pieper, Christine Robson, Nachiketa Sahoo. "Applications of Voting Theory to Information Mashups". Second IEEE International Conference on Semantic Computing. Santa Clara, CA, USA. Aug 2008.
  12. Daniel M. Russell , Andreas Dieberger , Varun Bhagwan, Daniel Gruhl. "Large Visualizations for System Monitoring of Complex, Heterogeneous Systems". INTERACT 2005 : 938-941.