A model of user behaviour based automated planning
is introduced in this work. The behaviour of users of web interactive
systems can be described in term of a planning domain encapsulating
the timed actions patterns representing the intended user profile. The
user behaviour recognition is then posed as a planning problem
where the goal is to parse a given sequence of user logs of the
observed activities while reaching a final state.
A general technique for transforming a timed finite state automata
description of the behaviour into a numerical parameter planning
model is introduced.
Experimental results show that the performance of a planning
based behaviour model is effective and scalable for real world
applications. A major advantage of the planning based approach is to
represent in a single automated reasoning framework problems of
plan recognitions, plan synthesis and plan optimisation.
[1] Alur R., Dill D., "A theory of timed automata", Theoretical Computer
Science, vol. 126, num. 2, p. 183-235, 1994.
[2] B. Berendt, M. Spiliopoulou, "Analysis of navigation behaviour in web
sites integrating multiple information systems", The VLDB Journal, 9,
Springer-Verlag, 2000, pp. 56-75.
[3] B. Berendt, G. Stumme, A. Hotho, "Usage mining for and on the
Semantic Web", In: H. Kargupta, A. Joshi, K. Sivakumar, & Y. Yesha
(Eds.), Data Mining: Next Generation Challenges and Future
Directions, AAAI/MIT Press, Menlo Park, CA, 2004, pp. 461-480.
[4] S. Ceri, F. Daniel, V. Demaldé, F. M. Facca, "An Approach to User-
Behavior-Aware Web Applications", ICWE 5 Proceedings, Sydney,
Australia, Springer, 2005.
[5] R. Cooley, B. Mobasher, J. Srivastava, "Data preparation for mining
world wide web browsing patterns", Journal of Knowledge and
Information Systems, 1(1), 1999.
[6] F. Masseglia, P. Poncelet, M. Teisseire, A. Marascu, "Web Usage
Mining: Extracting Unexpected Periods from Web Logs", TDM 2 -
ICDM'05 Proceedings, Houston, USA, 2005.
[7] M. M├╝hlenbrock, "Automatic Action Analysis in an Interactive Learning
Environment", AIED-2005 Proceedings, Amsterdam, NL, pp. 73-80.
[8] M. Teltzrow, B. Berendt, "Web-Usage-Based Success Metrics for Multi-
Channel Businesses", WebKDD 2003 9th ACM SIGKDD Proceedings,
Washington DC, USA, 2003.
[9] Marco Baioletti, Stefano Marcugini, Alfredo Milani: Encoding Planning
Constraints into Partial Order Planners. KR98 Proceeding, 6t Int. Conf.
on Principles of Knowledge Representation and Reasoning, pp.608-616,
Morgan Kauffmann 1998, ISBN 1-55860-554-1.
[10] Marco Baioletti Stefano Marcugini, Alfredo Milani: Task Planning and
Partial Order Planning: A Domain Transformation Approach. in Lecture
Notes in Computer Science, Vol.1348, pp.52-63, Springer-Verlag,
Berlin, Germany, 1997, ISBN 3-540-64912-8.
[11] Blum, A., and Frust, M. Fast planning graph analysis. Artificial
Intelligence 90, 1-2 (1997), 279-298.
[12] Kautz, H., and Selman, B. Planning as satisfiability. In 10th European
Confernce on Artificial Intelligence (ECAI) (1992), B. Neumann, Ed.,
Wiley & Sons, pp. 360-363.
[13] Kautz, H., and Selman, B. BLACKBOX: A new approach to the
application of thorem proving to ploblem solving. In working notes of
the AIPS-98 Workshop on Planning as Combinatorial Search (1998),
pp. 58-60.
[14] Suriani, S. Numerical Parameters in Automated Planning. PhD Thesis -
Department of Mathematics and Computer Science - University of
Perugia.
[15] Wolfaman, S., and Weld, D. The LPSAT engine and its application to
resource planning. In Proc. of IJCAI-99 (!999).
[16] Vossen, T., Ball, M. Lotem, A. and Nau, D. Applying integer
programming to AI planning, Knowledge Engineering Review 16:85-
100, 2001.
[17] Van de Briel, M. and Kambhampati, S. Optiplan: Unifying ip-based and
graph-based planning. Journal of Artificial Intelligence Research 24
(2005), 919-931.
[1] Alur R., Dill D., "A theory of timed automata", Theoretical Computer
Science, vol. 126, num. 2, p. 183-235, 1994.
[2] B. Berendt, M. Spiliopoulou, "Analysis of navigation behaviour in web
sites integrating multiple information systems", The VLDB Journal, 9,
Springer-Verlag, 2000, pp. 56-75.
[3] B. Berendt, G. Stumme, A. Hotho, "Usage mining for and on the
Semantic Web", In: H. Kargupta, A. Joshi, K. Sivakumar, & Y. Yesha
(Eds.), Data Mining: Next Generation Challenges and Future
Directions, AAAI/MIT Press, Menlo Park, CA, 2004, pp. 461-480.
[4] S. Ceri, F. Daniel, V. Demaldé, F. M. Facca, "An Approach to User-
Behavior-Aware Web Applications", ICWE 5 Proceedings, Sydney,
Australia, Springer, 2005.
[5] R. Cooley, B. Mobasher, J. Srivastava, "Data preparation for mining
world wide web browsing patterns", Journal of Knowledge and
Information Systems, 1(1), 1999.
[6] F. Masseglia, P. Poncelet, M. Teisseire, A. Marascu, "Web Usage
Mining: Extracting Unexpected Periods from Web Logs", TDM 2 -
ICDM'05 Proceedings, Houston, USA, 2005.
[7] M. M├╝hlenbrock, "Automatic Action Analysis in an Interactive Learning
Environment", AIED-2005 Proceedings, Amsterdam, NL, pp. 73-80.
[8] M. Teltzrow, B. Berendt, "Web-Usage-Based Success Metrics for Multi-
Channel Businesses", WebKDD 2003 9th ACM SIGKDD Proceedings,
Washington DC, USA, 2003.
[9] Marco Baioletti, Stefano Marcugini, Alfredo Milani: Encoding Planning
Constraints into Partial Order Planners. KR98 Proceeding, 6t Int. Conf.
on Principles of Knowledge Representation and Reasoning, pp.608-616,
Morgan Kauffmann 1998, ISBN 1-55860-554-1.
[10] Marco Baioletti Stefano Marcugini, Alfredo Milani: Task Planning and
Partial Order Planning: A Domain Transformation Approach. in Lecture
Notes in Computer Science, Vol.1348, pp.52-63, Springer-Verlag,
Berlin, Germany, 1997, ISBN 3-540-64912-8.
[11] Blum, A., and Frust, M. Fast planning graph analysis. Artificial
Intelligence 90, 1-2 (1997), 279-298.
[12] Kautz, H., and Selman, B. Planning as satisfiability. In 10th European
Confernce on Artificial Intelligence (ECAI) (1992), B. Neumann, Ed.,
Wiley & Sons, pp. 360-363.
[13] Kautz, H., and Selman, B. BLACKBOX: A new approach to the
application of thorem proving to ploblem solving. In working notes of
the AIPS-98 Workshop on Planning as Combinatorial Search (1998),
pp. 58-60.
[14] Suriani, S. Numerical Parameters in Automated Planning. PhD Thesis -
Department of Mathematics and Computer Science - University of
Perugia.
[15] Wolfaman, S., and Weld, D. The LPSAT engine and its application to
resource planning. In Proc. of IJCAI-99 (!999).
[16] Vossen, T., Ball, M. Lotem, A. and Nau, D. Applying integer
programming to AI planning, Knowledge Engineering Review 16:85-
100, 2001.
[17] Van de Briel, M. and Kambhampati, S. Optiplan: Unifying ip-based and
graph-based planning. Journal of Artificial Intelligence Research 24
(2005), 919-931.
@article{"International Journal of Information, Control and Computer Sciences:57839", author = "Alfredo Milani and Silvia Suriani", title = "Modeling User Behaviour by Planning", abstract = "A model of user behaviour based automated planning
is introduced in this work. The behaviour of users of web interactive
systems can be described in term of a planning domain encapsulating
the timed actions patterns representing the intended user profile. The
user behaviour recognition is then posed as a planning problem
where the goal is to parse a given sequence of user logs of the
observed activities while reaching a final state.
A general technique for transforming a timed finite state automata
description of the behaviour into a numerical parameter planning
model is introduced.
Experimental results show that the performance of a planning
based behaviour model is effective and scalable for real world
applications. A major advantage of the planning based approach is to
represent in a single automated reasoning framework problems of
plan recognitions, plan synthesis and plan optimisation.", keywords = "User behaviour, Timed Transition Automata,Automated Planning.", volume = "2", number = "2", pages = "475-7", }
