TY - GEN
T1 - Suggesting simple and comprehensive queries to elementary-grade children
AU - Shaikh, Meher T.
AU - Pera, Maria Soledad
AU - Ng, Yiu Kai
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - Backpropagation
KW - Children
KW - Query suggestion
UR - http://www.scopus.com/inward/record.url?scp=85028298185&partnerID=8YFLogxK
U2 - 10.1109/WI-IAT.2015.193
DO - 10.1109/WI-IAT.2015.193
M3 - Conference contribution
AN - SCOPUS:85028298185
T3 - Proceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015
SP - 252
EP - 259
BT - Proceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015
PB - Institute of Electrical and Electronics Engineers (IEEE)
T2 - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology Workshops, WI-IAT Workshops 2015
Y2 - 6 December 2015 through 9 December 2015
ER -