Effective ranking and search techniques for Web resources considering semantic relationships.

Jihyun Lee, Jun-Ki Min, Alice Oh, Chin-Wan Chung

Abstract: Highlights • Semantic search using ontology overcomes the limitation of the current keyword-based search. • The ranking method considering semantic relationships improves the search accuracy. • The ranking method is based on the weighting measure of semantic relationships. • Pruning based on the weight for the semantic relationship reduces the search space. • Top-k Answering based on the keyword index improves the search efficiency. Abstract On the Semantic Web, the types of resources and the semantic relationships between resources are defined in an ontology. By using that information, the accuracy of information retrieval can be improved. In this paper, we present effective ranking and search techniques considering the semantic relationships in an ontology. Our technique retrieves top-k resources which are the most relevant to query keywords through the semantic relationships. To do this, we propose a weighting measure for the semantic relationship. Based on this measure, we propose a novel ranking method which considers the number of meaningful semantic relationships between a resource and keywords as well as the coverage and discriminating power of keywords. In order to improve the efficiency of the search, we prune the unnecessary search space using the length and weight thresholds of the semantic relationship path. In addition, we exploit Threshold Algorithm based on an extended inverted index to answer top- k results efficiently. The experimental results using real data sets demonstrate that our retrieval method using the semantic information generates accurate results efficiently compared to the traditional methods. Previous article in issue Next article in issue