Predicting Customer Models Using Behavior-Based Features in Shops

Recent sensor technologies have enabled the capture of users' behavior data. Given the large amount of data currently available from sensor-equipped environments, it is important to attempt characterization of the sensor data for automatically modeling users in a ubiquitous and mobile computing environment. As described herein, we propose a method that predicts a customer model using features based on customers' behavior in a shop. We capture the customers' behavior using various sensors in the form of the time duration and the sequence between blocks in the shop. Based on behavior data from the sensors, we design features that characterize the behavior pattern of a customer in the shop. We employ those features using a machine learning approach to predict customer attributes such as age, gender, occupation, and interest. Our results show that our designed behavior-based features perform with F -values of 70---90% for prediction. We also discuss the potential applications of our method in user modeling.

[1]  Henry A. Kautz,et al.  Location-Based Activity Recognition using Relational Markov Networks , 2005, IJCAI.

[2]  Thorsten Joachims,et al.  Text Categorization with Support Vector Machines: Learning with Many Relevant Features , 1998, ECML.

[3]  Céline Rouveirol,et al.  Machine Learning: ECML-98 , 1998, Lecture Notes in Computer Science.

[4]  Daniela Petrelli,et al.  User-Centred Design of Flexible Hypermedia for a Mobile Guide: Reflections on the HyperAudio Experience , 2005, User Modeling and User-Adapted Interaction.

[5]  Tsvi Kuflik,et al.  Analyzing Museum Visitors' Behavior Patterns , 2007, User Modeling.

[6]  Judy Kay,et al.  Consistent Modelling of Users, Devices and Sensors in a Ubiquitous Computing Environment , 2005, User Modeling and User-Adapted Interaction.

[7]  Cristina Conati,et al.  User Modeling 2007, 11th International Conference, UM 2007, Corfu, Greece, June 25-29, 2007, Proceedings , 2007, User Modeling.

[8]  Chih-Jen Lin,et al.  Combining SVMs with Various Feature Selection Strategies , 2006, Feature Extraction.

[9]  Tsvi Kuflik,et al.  Adaptive, intelligent presentation of information for the museum visitor in PEACH , 2007, User Modeling and User-Adapted Interaction.

[10]  Marek Hatala,et al.  Ontology-Based User Modeling in an Augmented Audio Reality System for Museums , 2005, User Modeling and User-Adapted Interaction.

[11]  Max Van Kleek,et al.  A Practical Activity Capture Framework for Personal, Lifetime User Modeling , 2007, User Modeling.

[12]  Christopher G. Atkeson,et al.  The Narrator : A Daily Activity Summarizer Using Simple Sensors in an Instrumented Environment , 2003 .

[13]  Ingrid Zukerman,et al.  # 2001 Kluwer Academic Publishers. Printed in the Netherlands. Predictive Statistical Models for User Modeling , 1999 .

[14]  Andy Hopper,et al.  The active badge location system , 1992, TOIS.

[15]  Ingrid Zukerman,et al.  Using Collaborative Models to Adaptively Predict Visitor Locations in Museums , 2008, AH.

[16]  Alfred Kobsa,et al.  Generic User Modeling Systems , 2001, User modeling and user-adapted interaction.

[17]  Kôiti Hasida,et al.  Inferring Long-term User Properties Based on Users' Location History , 2007, IJCAI.

[18]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[19]  Paul Dourish,et al.  What we talk about when we talk about context , 2004, Personal and Ubiquitous Computing.

[20]  Judy Kay,et al.  Pervasive Personalisation of Location Information: Personalised Context Ontology , 2008, AH.

[21]  Geoffrey I. Webb,et al.  # 2001 Kluwer Academic Publishers. Printed in the Netherlands. Machine Learning for User Modeling , 1999 .

[22]  Anthony Jameson,et al.  Modelling both the Context and the User , 2001, Personal and Ubiquitous Computing.

[23]  Antonio Krüger,et al.  Preface to the Special Issue on User Modeling in Ubiquitous Computing , 2005, User Modeling and User-Adapted Interaction.

[24]  Carlo Strapparava,et al.  Adaptive Hypermedia and Adaptive Web-Based Systems, 5th International Conference, AH 2008, Hannover, Germany, July 29 - August 1, 2008. Proceedings , 2008, AH.