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

Keywords

Related Articles

Digitizing resources for University of Nigeria repository: Process and challenges

This paper reports on the implementation of digitization of resources at the University of Nigeria, Nsukka (UNN); the processes involved and the challenges faced. In the context of the establishment of a digital library...

Identification of the characteristics of e-commerce websites

E-commerce websites must possess certain characteristics in order to attract customers/users. Although previous studies have been conducted to determine some of these characteristics of different categories of websites,...

Citation analysis of Journal of Documentation

Citation analysis of all the journal articles published in the Journal of Documentation from 1996-2010 is carried out. 487 articles are published in the journal during 15 years. Highest numbers (44) of articles are publi...

Towards Information Anxiety and Beyond

This study provides an overview of the historical background of information anxiety, critically reviews the existing framework, and proposes a new framework for information anxiety that goes beyond information retrieval...

Visualizing Subjective Mapping in the Field of E-book Publishing in the Context of Users and Librarians

The present paper reports the findings of a research which aimed to visualize subjective mapping of "e-books" in the context of users and libraries. The research is a kind of scientometrics studies via qualitative conten...

Download PDF file
  • EP ID EP687806
  • DOI 10.14704/WEB/V16I1/a180
  • Views 229
  • Downloads 0

How To Cite

Mozaffar Cheshmeh Sohrabi and Neda Abbasi Dashtaki (2019). Ask Search Engine: Features and Performance identification. Webology, 16(1), -. https://europub.co.uk/articles/-A-687806