ISBN-13: 9783659341144 / Angielski / Miękka / 2015 / 168 str.
This book is concerned with the study and analysis of search engines and page rank algorithm in semantic space. Several search engines have been proposed, which allow increasing information retrieval accuracy by exploiting a key content of semantic web resources, ie relations. However, in order to rank results, most of the existing solutions need to work on the whole annotated knowledge base.The proposed case and relation based page rank algorithm is designed based on query definition process using ontological relations. The proposed architecture uses a hybrid methodology named case and relation based page rank algorithm which uses past problem solving experience maintained in the case based rank algorithm to form a best matching relations. This proposed approach reduces the search time by avoiding the generation of annotated page graphs for irrelevant results.In this work, a novel ranking strategy is proposed with the capability of fetching the results which are relevant to the user query by using the previous knowledge of search and providing a relevant score for the result pages by considering the user query, the page annotation and the underlying ontology.
This book is concerned with the study and analysis of search engines and page rank algorithm in semantic space. Several search engines have been proposed, which allow increasing information retrieval accuracy by exploiting a key content of semantic web resources, ie relations. However, in order to rank results, most of the existing solutions need to work on the whole annotated knowledge base.The proposed case and relation based page rank algorithm is designed based on query definition process using ontological relations. The proposed architecture uses a hybrid methodology named case and relation based page rank algorithm which uses past problem solving experience maintained in the case based rank algorithm to form a best matching relations. This proposed approach reduces the search time by avoiding the generation of annotated page graphs for irrelevant results.In this work, a novel ranking strategy is proposed with the capability of fetching the results which are relevant to the user query by using the previous knowledge of search and providing a relevant score for the result pages by considering the user query, the page annotation and the underlying ontology.