IRIS2: A Semantic Search Engine That Does Rational Research
Wei Wang, Hai‐Ning Liang · 2014
Popular techniques used in today's Web search engines and digital libraries for retrieving and ranking scientific publications have foundations in modern information retrieval. Information and users in the scientific research communities have their own characteristics, however, they have not been sufficiently exploited in existing retrieval and ranking methods. We present a semantic search engine, IRIS2, which represents the semantic entities and their relations using ontologies and knowledge bases. It utilises a ranking method based on the "rational research" model, which restores an elegant idea that a researcher does rational research in an academic environment. We explain in detail the design and implementation of the IRIS2 prototype and compare its retrieving and ranking performance with existing methods.