Analysis of Search and Browsing Behavior of Young Users on the Web

by Sergio Duarte Torres, Ingmar Weber and Djoerd Hiemstra 

In this journal paper we expanded the study presented in paper What and How Children Search on the Web in two directions. Firstly, We provide a more detailed analysis of the topics that are searched by children on a state-of-the-art search engine by using novel classification based on fine-grained topics derived from the categories of the Yahoo! Answers service. The findings obtained through this analysis allow us to provide concrete recommendations for the development of modern IR systems for young users in specific age ranges.


Secondly, we employed toolbar logs from the Yahoo! search engine to characterize the browsing behavior of young users, particularly to understand the activities on the Internet that trigger search. We quantified the proportion of browsing and search activity in the toolbar sessions and we estimated the likelihood of a user to carry out search on the Web vertical and multimedia verticals (i.e.\ videos and images) given that the previous event is another search event or a browsing event. We found that certain group of young users are more likely to carried out multimedia search and that certain browsing events are more likely to trigger web search, such as knowledge related websites (e.g. Wikipedia).

Published at TWEB ACM, March 2014, Volume 8 Issue 2. Read the paper.

Query Recommendation in the Domain of Information for Children

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

Children represent an increasing part of web users. One of the key problems that hamper their search experience is their limited vocabulary, their difficulty to use the right keywords, and the inappropriateness of general-purpose query suggestions. In this journal paper, we expanded the biased random walk introduced in our paper Query recommendation for Children by combining the score of the random walk with topical and language modeling features to emphasize even more the child-related aspects of the query suggestions.


We evaluate our methods using a large query log sample of queries submitted by children (from the Yahoo! Search logs). We show that our method outperforms by a large margin the query suggestions of modern search engines and state-of-the art query suggestions based on random walks.

Published at JASIST, February 2014. Read the paper.