Comparative Analysis of Semantic Search Engines Based on Requirement Space Pyramid

Abstract

Abstract-Semantic Web promises to add metadata to web content to make it understandable to computers. Search is the most widely used activity on web. Semantic search engines have already changed the way we search the data on web. Uren. V, Yuanguilei Uren et al., proposed requirement space pyramid arguing that iterative and exploratory search modes are important to the usability of search engines. It identified the types of semantic queries the users need to make, the issues concerning the search development and the problems intrinsic to semantic search in particular. We have extensively examined the semantic search engines and have done broad survey to analyse the semantic search engines. Comparative analysis of the semantic search engines have been done on the basis of factors cited in the pyramid. The research provides deep understanding of five main semantic search engines based on comparative analysis that may help for future work for semantic web in general and for semantic search engines in particular.Index Terms-Semantic web, semantic search engine, requirement space pyramid. I. INTRODUCTIONSemantic Web [1], the future of web, promises to provide content that will be understandable to computer. Search is the most important and popular applications of the web. Semantic search [2] is one of the most significant applications of semantic web. Recently a number of semantic search engines have been introduced. Semantic Search engine is a tool that produces precise results to user queries by retrieving data semantically [3]. The purpose of this paper is to compare semantic search engines along with their salient characteristic approaches. This paper focuses mainly on five semantic search engines including Hakia, Sensebot, Powerset, Lexxe and Cognition. There are many benchmarks and standards used in every field and computer science is not an exception. Google and other search engines have revolutionized the world with their services but with the idea of semantic search, the rise of semantic search engines has changed the requirements and issues related with search engines. A pyramid scheme has been used as model for discussion to present the requirements, issues and challenges for semantic search engines. The remaining paper has been formatted as follows that related work have discussed in section II. Comparative evaluation of the semantic search engines on the basis of the pyramid has been described in Manuscript received November 8, 2012; revised January 28, 2013 section III. The semantic search engines along with their GUI's have been discussed in section IV while finally the concluding remarks include the issues and challenges of semantic search engines. II. RELATED WORKSSemantic search engine is new field and realtively less work has been done in this domain. Hakia has been compared with google, yahoo and msn in [4] and that of Hakia with dogpile. A relation-based page rank algorithm has been proposed to be used as semantic web search engine. In this work, relevance is measured as probability of finding con...

Comparative Study of Semantic and Keyword Based Search Engines

“…The Semantic Search Engines (SSE)s are the intelligent engines that search for keywords depending on their meaning [20]. In addition, they guarantee the results those are related to the meaning of searched keywords.…”

“…; also, they can be divided according to the date or relevance. The technology which is used in Hakia is the OntoSem technology, which is a linguistic database [20]. The words here are categorized into different senses by depending on the QDEX (Query indexing technique), which considered as an infrastructure to index the data by Semantic Rank algorithm.…”

“…In addition, some other languages are also used such as OWL, DAML, PDFS and RDF. The analysis part of the engine used to create metadata to describe documents to classify the Semantic Web Ontologies (SWOs) and Semantic Web Databases (SWDBs) [20]. The last part of the system called services which considered as the engine interface that tries to provide data services depending on ontologies at the term level [28].…”

“…Qureshi et al [20] focus on exploring differences of SW search dimensions. They use the excellent pyramid to test the different dimensions to study about the SSEs.…”

A comprehensive framework for the semantic cache systems

“…The modern distributed systems for query processing need to balance the query loads and leverage the caches results to maximize the system throughput. The survey (Qureshi et al, 2013) provides valuable insights in learning various types of semantic search modes and the behavior of existing semantic search engines. Another work (Eom et al, 2015) proposed scheduling policies in the context of distributed query processing.…”