Quality, Relevance and Importance in Information Retrieval with Fuzzy Semantic Networks
Roy Lachica, Dino Karabeg, Sasha Rudan · 2008
Abstract. We propose a framework for ranking information based on quality, relevance and importance, and argue that a socio-semantic contextual approach that extends topicality can lead to enhanced precision in information retrieval. We use Topic Maps to implement our framework, and discuss procedures for collecting the pertinent metadata and for calculating the resource ranking. A fuzzy neural network approach is envisioned to complement the process of manual metadata creation.