Rational Research model for ranking semantic entities

—Ranking plays important roles in contemporary Internet and vertical search engines. Among existing ranking algorithms, link analysis based algorithms have been proved as effective means for ranking retrieved documents from large-scale text repositories, such as the current Web. Recent development in semantic Web and semantic search raises considerable interests in new ranking paradigms for various applications. While ranking methods in this context exist, they have not gained much popularity. In this article we propose the RareRank algorithm for ranking entities in semantic search applications. The algorithm is based on the “Rational Research” model which reflects search behaviour of a “rational” researcher in a scientific research environment. Justification, design, and implementation of the algorithm are elaborated in details. In the experiment, the algorithm is deployed for ranking semantic entities, and results were evaluated by domain experts using popular ranking pe...

• Type: Journal
• Year: 2011
• Where: ISCI
• Authors: Wang Wei, Payam M. Barnaghi, Andrzej Bargiela
• Keywords: Algorithms, ISCI 2011, Natural Language Processing, Ranking, Semantic Search