An adaptive learning book system based on user's study interest

In this study, we present the prototype of an adaptive learning book system according to a user's learning behavior. The system consists of a paper textbook and a 3D CG content viewer on a smart phone display. In this hybrid learning book system, a learner's learning history and behavior are stored in a study profile database using the smart phone's monitoring functions. A user's study interest is extracted in the form of a weighted term set by analyzing the study profile database so that learning contents related to the user's study interest can be adaptively provided in a series of learning opportunities.

[1]  John Riedl,et al.  GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.

[2]  John Riedl,et al.  Analysis of recommendation algorithms for e-commerce , 2000, EC '00.

[3]  Benjamin Piwowarski,et al.  A user browsing model to predict search engine click data from past observations. , 2008, SIGIR '08.

[4]  Young-Woo Seo,et al.  Learning user's preferences by analyzing Web-browsing behaviors , 2000, AGENTS '00.

[5]  Akimichi Tanaka,et al.  System for reminding a user of information obtainedthrough a web browsing experience , 2007, WWW '07.

[6]  Wei-Ying Ma,et al.  Improving pseudo-relevance feedback in web information retrieval using web page segmentation , 2003, WWW '03.

[7]  Paul-Alexandru Chirita,et al.  Personalized query expansion for the web , 2007, SIGIR.

[8]  Kin Fun Li,et al.  An Adaptive e-Learning Recommender Based on User's Web-Browsing Behavior , 2010, 2010 International Conference on P2P, Parallel, Grid, Cloud and Internet Computing.

[9]  David Heckerman,et al.  Empirical Analysis of Predictive Algorithms for Collaborative Filtering , 1998, UAI.

[10]  Pedro José Marrón,et al.  User centric walk: an integrated approach for modeling the browsing behavior of users on the Web , 2005, 38th Annual Simulation Symposium.

[11]  Kin Fun Li,et al.  An Adaptive Personalized Recommender Based on Web-Browsing Behavior Learning , 2009, 2009 International Conference on Advanced Information Networking and Applications Workshops.

[12]  Russel Pears,et al.  Contextual relevance feedback in web information retrieval , 2006, IIiX.

[13]  Emanuela De Vita,et al.  SEARCHY: An Agent to Personalize Search Results , 2008, 2008 Third International Conference on Internet and Web Applications and Services.

[14]  Kin Fun Li,et al.  Keysurf: a character controlled browser for people with physical disabilities , 2008, WWW.

[15]  Ieee Staff.  2013 Eighth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC) , 2013 .

[16]  Ryen W. White,et al.  Mining the search trails of surfing crowds: identifying relevant websites from user activity , 2008, WWW.