Query recommendation for children

by Sergio Duarte Torres, Djoerd Hiemstra, Ingmar Weber, Pavel Serdyukov. 

One of the biggest problems that children experience while searching the web occurs during the query formulation process. Children have been found to struggle formulating queries based on keywords given their limited vocabulary and their difficulty to choose the right keywords.
In this work we propose a method that utilizes tags from social media to suggest queries related to children topics. Concretely we propose a simple yet effective approach to bias a random walk defined on a bipartite graph of web resources and tags through keywords that are more commonly used to describe resources for children. We evaluate our method using a large query log sample of queries aimed at retrieving information for children. We show that our method outperforms query suggestions of state-of-the-art search engines and state-of-the art query suggestions based on random walks.
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An analysis of queries intended to search information for children

by Sergio Duarte Torres, Djoerd Hiemstra and Pavel Serdyukov. 

The majority of children and teenagers are active users of the Internet for education and entertainment purposes, thus developing children’s abilities to find and understand information is a key in their development as young adults. However, children’sability to use the Internet is severely hampered by the lack of appropriate search tools. Most Information Retrieval (IR) systems are designed for adults: they return information in a form that is unsuitable for children.The aim of this presentation is twofold: (i) introduce the research lines and outcome of the PuppyIR project which is aimed at providing a infrastructure and framework for developing child-focused information service; and (ii) explore the outcome of our research on understanding the search behavior of children in the Internet and provide a brief description of query recommendation mechanisms tailored at young users. Read the paper.