Abstract

Media analysis and mining involve processing of large quantities of real-time and/or stored data and measurements. Data (whether captured in real-time through sensory measurements or processed, materialized, and stored for later use) are many times accurate only within a margin of error. Moreover, in many applications, the utility of a data element to a particular analysis task depends on the usage context. The fundamental principles that govern the next generation of media/data analysis middleware must include data and operator imprecision, relevance of data to a particular analysis task, and the interest and expertise of the knowledge consumer. In this talk, I will discuss challenges for and opportunities in developing efficient and effective analysis middleware to support large scale data processing and decision making applications, where the data elements, metadata, and the operations on the data may be imprecise.

Original languageEnglish (US)
Title of host publicationSociety for Industrial and Applied Mathematics - 9th SIAM International Conference on Data Mining 2009, Proceedings in Applied Mathematics 133
Number of pages1
StatePublished - Dec 1 2009
Event9th SIAM International Conference on Data Mining 2009, SDM 2009 - Sparks, NV, United States
Duration: Apr 30 2009May 2 2009

Publication series

NameSociety for Industrial and Applied Mathematics - 9th SIAM International Conference on Data Mining 2009, Proceedings in Applied Mathematics
Volume3

Other

Other9th SIAM International Conference on Data Mining 2009, SDM 2009
Country/TerritoryUnited States
CitySparks, NV
Period4/30/095/2/09

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Multimedia data mining workflows: Efficiency and effectiveness'. Together they form a unique fingerprint.

Cite this