wayGoo recommender system: personalized recommendations for events scheduling, based on static and real-time information

Konstantinos-Georgios Thanos; Stelios C. A. Thomopoulos

doi:10.1117/12.2223397

17 May 2016 wayGoo recommender system: personalized recommendations for events scheduling, based on static and real-time information

Konstantinos-Georgios Thanos, Stelios C. A. Thomopoulos

Author Affiliations +

Proceedings Volume 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV; 98420S (2016) https://doi.org/10.1117/12.2223397
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

Abstract

wayGoo is a fully functional application whose main functionalities include content geolocation, event scheduling, and indoor navigation. However, significant information about events do not reach users’ attention, either because of the size of this information or because some information comes from real – time data sources. The purpose of this work is to facilitate event management operations by prioritizing the presented events, based on users’ interests using both, static and real – time data. Through the wayGoo interface, users select conceptual topics that are interesting for them. These topics constitute a browsing behavior vector which is used for learning users’ interests implicitly, without being intrusive. Then, the system estimates user preferences and return an events list sorted from the most preferred one to the least. User preferences are modeled via a Naïve Bayesian Network which consists of: a) the ‘decision’ random variable corresponding to users’ decision on attending an event, b) the ‘distance’ random variable, modeled by a linear regression that estimates the probability that the distance between a user and each event destination is not discouraging, ‘ the seat availability’ random variable, modeled by a linear regression, which estimates the probability that the seat availability is encouraging d) and the ‘relevance’ random variable, modeled by a clustering – based collaborative filtering, which determines the relevance of each event users’ interests. Finally, experimental results show that the proposed system contribute essentially to assisting users in browsing and selecting events to attend.

Citation Download Citation

Konstantinos-Georgios Thanos and Stelios C. A. Thomopoulos "wayGoo recommender system: personalized recommendations for events scheduling, based on static and real-time information", Proc. SPIE 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV, 98420S (17 May 2016); https://doi.org/10.1117/12.2223397

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KEYWORDS

Visualization

Remote sensing

Visual process modeling

Databases

Geographic information systems

Printed circuit board testing

Statistical modeling

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