Performance Evaluation of Keyword and Semantic based Search Engines-An Empirical Study

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Junaid Rashid
Syed Muhammad Adnan
Muhammad Wasif Nisar

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Guest Editors Benchmarking Linked Data 2017

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Survey Article
The Keyword search engines do not know the meanings of words, expressions with terms using in different web pages. Therefore they don't provide the relevant search results for the user queries. In this paper, we discuss the semantic searching, technologies used for semantic searching and compare some semantic search engines. After that, some traditional search engines (keyword based search engines) and semantic-based search engine performance are compared. Firstly, the three keyword search engines (Google, Yahoo, and AOL) and four semantic web based search engines (Bing, Duckduckgo, Sensebot, and Exalead) are taken. These keyword and semantic search engines are compared to check the performance of their searching, by the precision ratio, Mean, and the Geometric Mean. Forty queries on different topics were selected and execute on every search engine. The first twenty links of documents were retrieved and categorized as relevant and irrelevant. The precision ratio, mean and geometric was calculated for the first twenty documents to find out search engines performance. In this study, it was found that the relevant document retrieved by Bing is more (570 out of 800) than any of the other search engine. Sensebot whole performance regarding precision ratio is lowest (23.87 %). After Bing, the DuckDuckGo retrieves (515 documents out of the 800). The precision ratio of Bing is 71.25% which are greater than others search engines. After Bing, the DuckDuckGo precision ratio is 64.37%.The Google precision ratio is 59% which is a keyword based search engine.
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