Abstract :
With the rapid development of World Wide Web, search engines have become the main tool for people to get network information. However, the search results are widely criticized due to the poor accuracy and redundancy disadvantages. After the advent of semantic Web, new search engine with the ability of understanding queries and documents has attracted more and more attentions. This paper starts from the traditional search engine, and firstly introduces its classification, popular technology, advantages and disadvantages, thus leads to the semantic search engine model. Then we research the semantic search technology in depth, which can be divided into enhanced semantic search based on traditional search, knowledge semantic search based on ontology inference and other semantic search types. In addition, key techniques in semantic search engine development, such as automated inference technique, ontology knowledge system and expert system are presented in this paper. Lastly, we conclude the current research and forecast the prospect of future research.
Keywords :
expert systems; inference mechanisms; ontologies (artificial intelligence); query processing; search engines; semantic networks; World Wide Web; automated inference technique; expert system; knowledge semantic search; network information; ontology inference; ontology knowledge system; query understanding ability; semantic Web; semantic search types; semantic-based search engine model design; semantic-based search engine model development; Crawlers; Engines; Expert systems; Ontologies; Search engines; Semantics; Ontology Inference; Search Engine; Semantic Search Engine;