Developing an ontology-supported information integration and recommendation system for scholars

With the growing popularity of Internet technology, information is increasing in a geometric-progressively manner. How to find advantage information to meet user queries in the information torrent of Internet has become the first goal of lots of scholars. This paper focused on developing an ontology-supported information integration and recommendation system for scholars. Not only can it rapidly integrate specific domain documents, but also it can extract important information from them by information integration and recommendation ranking. The core technologies adopted in this study included: ontology-supported webpage crawler, webpage classifier, information extractor, information recommender, and a user integration interface. The preliminary experiment outcomes proved both the webpage crawler and classifier in the core technology can achieve an excellent precision rate of webpage treatment and the reliability and validation measurements of the whole system performance can also achieve the high-level outcomes of information recommendation. Further, this paper also discussed and examined the advantages and shortcomings of the construction of a recommendation system with different approaches and accordingly provided the design philosophy of customized services for recommendation systems.