Ask Search Engine: Features and Performance identification
Journal Title: Webology - Year 2019, Vol 16, Issue 1
Abstract
The structural and content features of the Ask search engine together with its assessment based on the three types of keyword, phrase and question queries run on information retrieval performance are identified in this article. This is an applied research run by adopting the survey and documentation methods. Two checklists were used to collect data: one for identifying the structural and content features and the other for recording the recall and precision ratios. The obtained data is then recorded to calculate the recall and precision. In total, 48 structural and 16 content features are identified. The findings indicate an average of 44.95 percent recall and of 31.54 percent precision in this search engine. This fact reveals that the Ask search engine performance is not appropriate. The obtained results emphasize the fact that the performance of information retrieval through question search method outperforms keyword search and phrase search methods.
Authors and Affiliations
Mozaffar Cheshmeh Sohrabi and Neda Abbasi Dashtaki
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