Efficient Context Management and Personalized User Recommendations in a Smart Social TV environment

07/09/2017
by   Fotis Aisopos, et al.
0

With the emergence of Smart TV and related interconnected devices, second screen solutions have rapidly appeared to provide more content for end-users and enrich their TV experience. Given the various data and sources involved - videos, actors, social media and online databases- the aforementioned market poses great challenges concerning user context management and sophisticated recommendations that can be addressed to the end-users. This paper presents an innovative Context Management model and a related first and second screen recommendation service, based on a user-item graph analysis as well as collaborative filtering techniques in the context of a Dynamic Social & Media Content Syndication (SAM) platform. The model evaluation provided is based on datasets collected online, presenting a comparative analysis concerning efficiency and effectiveness of the current approach, and illustrating its added value.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/01/2017

Second Screen User Profiling and Multi-level Smart Recommendations in the context of Social TVs

In the context of Social TV, the increasing popularity of first and seco...
research
02/10/2023

Trauma-Informed Social Media: Towards Solutions for Reducing and Healing Online Harm

Social media platforms exacerbate trauma, and many users experience vari...
research
09/10/2018

Detecting Gang-Involved Escalation on Social Media Using Context

Gang-involved youth in cities such as Chicago have increasingly turned t...
research
11/11/2021

Personalized multi-faceted trust modeling to determine trust links in social media and its potential for misinformation management

In this paper, we present an approach for predicting trust links between...
research
10/21/2022

Collaborative Image Understanding

Automatically understanding the contents of an image is a highly relevan...
research
11/07/2017

Deep density networks and uncertainty in recommender systems

Building robust online content recommendation systems requires learning ...
research
08/30/2020

Personalized TV Recommendation: Fusing User Behavior and Preferences

In this paper, we propose a two-stage ranking approach for recommending ...

Please sign up or login with your details

Forgot password? Click here to reset