Conflict Management in Interactive Financial Service Selection

Knowledge-based systems are often used to support search and navigation in a set of financial services. In a typical process users are defining their requirements and the system selects and ranks alternatives that seem to be appropriate. In such scenarios situations can occur in which requirements can not be fulfilled and alternatives (repairs) must be proposed to the user. In this paper we provide an overview of model-based diagnosis techniques that can be applied to indicate ways out from such a ”no solution could be found” dilemma. In this context we focus on scenarios from the domain of financial services.

[1]  Alexander Felfernig,et al.  Recommender Systems: An Overview , 2011, AI Mag..

[2]  Jock D. Mackinlay,et al.  The information visualizer, an information workspace , 1991, CHI.

[3]  Alexander Felfernig,et al.  Towards recommending configurable offerings , 2010 .

[4]  Alexander Felfernig,et al.  Knowledge-based Interactive Selling of Financial Services with FSAdvisor , 2005, AAAI.

[5]  Alexander Felfernig,et al.  Recommendation Technologies for Configurable Products , 2011, AI Mag..

[6]  Johan de Kleer,et al.  Using Crude Probability Estimates to Guide Diagnosis , 1990, Artif. Intell..

[7]  Michael Pinedo,et al.  Scheduling: Theory, Algorithms, and Systems , 1994 .

[8]  Markus Zanker,et al.  Konzepte zur flexiblen Konfiguration von Finanzdienstleistungen , 2004 .

[9]  Alexander Felfernig,et al.  An efficient diagnosis algorithm for inconsistent constraint sets , 2011, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[10]  Markus Stumptner,et al.  Consistency-based diagnosis of configuration knowledge bases , 1999, Artif. Intell..

[11]  Gerhard Friedrich.  Interactive debugging of knowledge-bases ( extended abstract ) , 2014 .

[12]  Raymond Reiter,et al.  Characterizing Diagnoses and Systems , 1992, Artif. Intell..

[13]  Andrew E. Fano,et al.  Personal choice point: helping users visualize what it means to buy a BMW , 2003, IUI '03.

[14]  Pasquale Lops,et al.  Financial Product Recommendation through Case-based Reasoning and Diversification Techniques , 2014, RecSys Posters.

[15]  Mikolás Janota,et al.  Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence On Computing Minimal Correction Subsets , 2022 .

[16]  Alan K. Mackworth.  Consistency in Networks of Relations , 1977, Artif. Intell..

[17]  Francesco Ricci,et al.  Case-Based Recommender Systems: A Unifying View , 2003, ITWP.

[18]  Alexander Felfernig,et al.  The VITA Financial Services Sales Support Environment , 2007, AAAI.

[19]  Ulrich Junker,et al.  QUICKXPLAIN: Preferred Explanations and Relaxations for Over-Constrained Problems , 2004, AAAI.

[20]  Barry O'Sullivan,et al.  Representative Explanations for Over-Constrained Problems , 2007, AAAI.

[21]  Eugene C. Freuder.  In Pursuit of the Holy Grail , 1996, CSUR.

[22]  Paul Resnick,et al.  Recommender systems , 1997, CACM.

[23]  Robert Winter,et al.  Konfiguration von Versicherungsleistungen , 1994, Wirtsch..

[24]  Alexander Felfernig,et al.  Personalized Diagnosis for Over-Constrained Problems , 2013, IJCAI.

[25]  W. Edwards,et al.  Decision Analysis and Behavioral Research , 1986 .

[26]  P. M. Wognum,et al.  Diagnosing and Solving Over-Determined Constraint Satisfaction Problems , 1993, IJCAI.

[27]  Gerhard Friedrich,et al.  Recommender Systems: Collaborative recommendation , 2010 .

[28]  Alexander Felfernig,et al.  Knowledge-Based Configuration: From Research to Business Cases , 2014 .

[29]  Raymond Reiter,et al.  A Theory of Diagnosis from First Principles , 1986, Artif. Intell..