摘要：With the advent of Web 2.0 technologies a new attitude towards processing
contents in the Internet has emerged. Nowadays it is a lot easier to create,
share and retrieve multimedia contents on the Web. However, with the increasing
amount in contents retrieval becomes more challenging and often leads to
inadequate search results. One main reason is that image clustering and
retrieval approaches usually stick either solely to the images' low-level
features or their user-generated tags (high-level features). However, this is
frequently inappropriate since the "real" semantics of an image can only be
derived from the combination of low-level and high-level features. Consequently,
we investigated a more holistic view on image semantics based on a system called
Imagesemantics. This system combines MPEG-7 descriptions for low-level
content-based retrieval features and MPEG-7 keywords by a machine learning
approach producing joined OWL rules. The rule base is used in Imagesemantics to
improve retrieval results.
关键词：MPEG-7, Web 2.0, social media platform, user-generated content
