The Study Of Implementation Technique For Ontology-Based Search Engine System In Stock Field

Nowadays the Search Engines on the Internet are mainly divided into two kinds: general search engine and domain-specific search engine. The latter has become the trend of the development of search engine, since some users who have special demands can't satisfy with the shortcoming of unprofessional indexing content, the indexing refreshment problem caused by large amount of memory capacity and so on. All of these problems needs to be solved in the study of domain-specific search engine system.This paper introduces the principle of general search engine first, then explain"Lucene"technology, which is a popular open source project in search engine field recently. The rest of this paper is also based on this technology.As the aspect of data collecting, for the reason of unprofessional processing mode of general crawler, this paper designed and realized a kind of crawler named"Focus Crawler", which can raise the efficiency of domain-specific search engine through our experiment.Then we introduce the principle of data extracting of webpage and put forward a method which is based on statistics. Through the analysis of several web sites, we drew a conclusion that this method has made good progress in the universality and can reach the accurate level above 90%.Further more, now the most popular technology in the search engine field is key word-matching, but each field has its unique words, or one word may means different things in different fields. When users input some common inquiries, it leads to the excessive inflation problem of results, the accurate is too low to make users themselves to find their interesting things.The ontology technology is the most expressive model of the knowledge expressing models. So if we take advantage of the capacity of ontology technique, we can raise the consistency of the inquiries and retrieval languages and reach our aim closely. This paper introduces the principle of semantic web and ontology technique and uses it to design our stock-faced search engine system. The result of experiments shows that our system can reach the demands of users in the stock field basically. Compared with general search engine, it has made good progress on terms of accuracy, allsidedness and so on.