Pythia: A Privacy-enhanced Personalized Contextual Suggestion System for Tourism

G. Drosatos, P.S. Efraimidis, A. Arampatzis, G. Stamatelatos, I.N. Athanasiadis

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

14 Citations (Scopus)


We present Pythia, a privacy-enhanced non-invasive contextual suggestion system for tourists, with important architectural innovations. The system offers high quality personalized recommendations, non-invasive operation and protection of user privacy. A key feature of Pythia is the exploitation of the vast amounts of personal data generated by smartphones to automatically build user profiles, and make contextual suggestions to tourists. More precisely, the system utilizes (sensitive) personal data, such as location traces, browsing history and web searches (query logs), to build a POI-based user profile. This profile is then used by a contextual suggestion engine for making POI recommendations to the user based on her current location. Strong privacy guarantees are achieved by placing both mechanisms at the user-side. As a proof of concept, we present a Pythia prototype which implements the aforementioned mechanisms as mobile applications for Android, as well as, web applications.
Original languageEnglish
Title of host publicationComputer Software and Applications Conference (COMPSAC)
EditorsSheikh Iqbal Ahamed, Carl K. Chang, William Chu, Ivica Crnkovic, Pao-Ann Hsiung, Gang Huang, Jingwei Yang
ISBN (Print)9781467365635
Publication statusPublished - 2015
Event 2015 IEEE 39th Annual - TBD, Taichung, Thailand
Duration: 1 Jul 20155 Jul 2015


Conference 2015 IEEE 39th Annual


  • Contextual Suggestion
  • Mobile Computing
  • Non-Invasiveness
  • Personal Data
  • Personalization
  • Privacy
  • Tourism


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