Recent work in Ontology learning and Text mining has mainly focused on engineering methods to solve practical problem. In this thesis, we investigate methods that can substantially...
Traditional content-based image retrieval (CBIR) systems often fail to meet a user's need due to the `semantic gap' between the extracted features of the systems and the...
We revisit one of the most fundamental problems in multimedia that is receiving enormous attention from researchers without making much progress in solving it: the problem of brid...
The major scientific problem for content-based video retrieval is the semantic gap. Generally speaking, there are two appropriate ways to bridge the semantic gap: the first one is...
Lei Bao, Juan Cao, Yongdong Zhang, Jintao Li, Ming...
Increasing applications are demanding effective and efficient support to perform retrieval in large collections of digital images. The work presented here is an early stage resear...
Giovanna Castellano, Gianluca Sforza, Maria Alessa...
Automatic semantic classification of video databases is very useful for users searching and browsing but it is a very challenging research problem as well. Combination of visual an...
Relational databases are widely used today as a mechanism for providing access to structured data. They, however, are not suitable for typical information finding tasks of end use...
One of the major problems in CBIR is the so-called `semantic gap': the difference between low-level features, extracted from images, and the high-level `information need'...
Walter ten Brinke, David McG. Squire, John Bigelow
Object-oriented techniques have been along the last decade one of the most useful programming paradigms. However, for distributed embedded systems the semantic gap between the obj...
In this paper, an interactive image retrieval scheme using MPEG-7 visual descriptors is proposed. The performance of image retrieval systems is still limited due to semantic gap, w...