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Application of Trace-Based Subjective Logic to User Preferences Modeling

12 pagesPublished: December 18, 2015

Abstract

A good way to help users make decisions in an interactive application consists in suggesting choices in accordance with their preferences. This decision problem faces challenging tasks, mainly in choosing a good solution that satisfies users and reaches the defined goal. Classical decision methods take into account the goal, but not all the obtained decisions can satisfy users’ preferences. The originality of our explorative research is to associate Subjective Logic (SL) to system’s traces (historical information) in order to model the user preferences that improve the decision process. Following JØsang, SL provides a suitable framework for modeling and formally describing users’ preferences. We propose to connect data collected in past executions, called traces, to the user intuition in order to support subjective reasoning. Based on this result, we can choose a reasonable decision according to users’ preferences. A Tamagotchi system will be presented to validate our result.

Keyphrases: opinion, subjective logic, traces, user preferences

In: Ansgar Fehnker, Annabelle McIver, Geoff Sutcliffe and Andrei Voronkov (editors). LPAR-20. 20th International Conferences on Logic for Programming, Artificial Intelligence and Reasoning - Short Presentations, vol 35, pages 94-105.

BibTeX entry
@inproceedings{LPAR-20:Application_Trace_Based_Subjective,
  author    = {Hoang Nam Ho and Mourad Rabah and Samuel Nowakowski and Pascal Estraillier},
  title     = {Application of Trace-Based Subjective Logic to User Preferences Modeling},
  booktitle = {LPAR-20. 20th International Conferences on Logic for Programming, Artificial Intelligence and Reasoning - Short Presentations},
  editor    = {Ansgar Fehnker and Annabelle McIver and Geoff Sutcliffe and Andrei Voronkov},
  series    = {EPiC Series in Computing},
  volume    = {35},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/R},
  doi       = {10.29007/zl3d},
  pages     = {94-105},
  year      = {2015}}
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