- David J. Redcliff
- Research Papers
- Semantic Search
Evaluation of Keyword Search Engine Using First 20 Precision
Evaluation of a Semantic Search Engine against a Keyword Search Engine Using First 20 Precision
The growth of the Semantic Web has resulted in the development of Semantic applications such as search engines. The continuous development of these applications has prompted many researchers to declare that the Semantic Web is a solution to the many problems faced by the current World Wide Web. However, there is a lack of proper evidence to prove that the Semantic Web is actually superior to the WWW. In our research, we collected queries from 30 university students and entered these queries into two search engines: Google – the most widely used search engine and Hakia – an upcoming Semantic search engine. Precision was thereafter calculated using a pre-determined formula. Our calculation revealed that Google outperforms Hakia as it has a higher mean precision at 0.64 as compared to Hakia at 0.54. Google also has a lower standard deviation at 0.14as compared to Hakia at 0.25. The results show that Google, which is a keyword search engine, is superior to Hakia, a Semantic Search engine in terms of the first 20 precision. While there is a possibility of this fact changing in the future with the current advancement rates of the Semantic Web, it remains absolutely true for now.
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