Suggesting simple and comprehensive queries to elementary-grade children

Conference Paper (2016)
Author(s)

Meher T. Shaikh (Brigham Young University)

M.S. Pera (Boise State University)

Yiu Kai Ng (Brigham Young University)

Affiliation
External organisation
DOI related publication
https://doi.org/10.1109/WI-IAT.2015.193
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Publication Year
2016
Language
English
Affiliation
External organisation
Pages (from-to)
252-259
ISBN (electronic)
9781467396172

Abstract

Query suggestions (QS) tailored specifically for children are slowly gaining research attention in response to the growth in Internet use by children. Even though QS offered by popular search engines adequately meet the information needs of the general public, they do not achieve equivalent effectiveness from a child's perspective. This is because children's search behaviors, interests, cognitive levels, and ability to read and understand complex content are different from adults. Given the ubiquitous nature of the Web, its importance in today's society, and its increasing use in education, it is an urgent need to help children 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. Empirical studies conducted using keyword queries initiated by children, in addition to feedback gathered through crowdsourcing, have verified not only the effectiveness of CQS, but also the fact that children favor CQS-generated suggestions over the suggestions provided by Google, Yahoo!, and Bing.

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