Using Online Data Sources to Make Query Suggestions for Children

Document Type

Article

Publication Date

11-20-2017

DOI

https://doi.org/10.3233/WEB-170367

Abstract

Existing popular web search engines have been widely used for retrieving information of interests by their users and offer query suggestions (QS) to assist them in exploring the wealth of information online. These search tools, however, are designed without any specific group of users in mind and thus are not tailored towards the specific needs of children, which can diminish their usability and design objectives when they are employed by children. Given the increasing use of the Web for educational and entertainment purposes by children, there is an urgent need to help them search the Web effectively. In this paper, we present a QS module, denoted CQS, which assists children in finding appropriate query keywords to capture their information needs by (i) analyzing content written for/by children, (ii) examining phrases and other metadata extracted from reputable (children’s) websites, and (iii) using a supervised learning approach to rank suggestions that are appealing to children. CQS offers suggestions with vocabulary that can be comprehended by children and with topics of interest to them. We conducted a number of empirical studies using keyword queries initiated by children, besides gathering feedback on the usefulness of CQS-generated suggestions through crowdsourcing. The performance evaluation of CQS revealed the effectiveness of the methodology of CQS. In addition, it demonstrated that CQS-generated suggestions were preferred over suggestions provided by Bing and Yahoo! and at least as comparable to queries suggested by Google.

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