Image Semantic Search Engine

As the search technology rapidly developed, nowadays, main search engines are already able to meet users basic search desire. However, current search algorithms or methodologies mostly depend on keywords matching process, which could be effective for text search while not efficient for keywords-lacking or non-text search scenarios. This paper summarizes the solution adopted by current search engine vendors, and introduces a new approach that attaches content description index based on RDF standard to Web images in order to achieve converting unstructured information search into structured information search. By injecting the Web 2.0 feature-wisdom of crowds, the engine has the characteristics of self-learning: as users amount increases, the knowledge base for semantic content of images accumulates, which makes the search engine more and more intelligent for search and semantics reasoning.