Model-Based Multi-modal Information Retrieval from Large Archives
Date Issued
2000
Date
2000
Author(s)
Li, Chung-Sheng
Chang, Yuan-Chi
Bergman, Lawrence D.
Smith, John R.
DOI
20060927122753664431
Abstract
In this paper, we describe a new paradigm for
information retrieval in which the retrieval target is based
on a model. Three types of models – linear, finite state,
and knowledge models are discussed. These information
retrieval scenarios often arise from applications such as
environmental epidemiology, oil/gas production and
exploration, and precision agriculture/forestry.
Traditional model-based data and information processing
usually requires the processing of each and every data
points. The proposed new framework, in contrast, will
process the data progressively using a set of progressive
models and utilize indexing techniques specialized for the
model to facilitate retrieval, thus achieving a dramatic
speedup.
Publisher
臺北市:國立臺灣大學電機工程學系
Type
thesis
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