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Method and System for Recommending Travel Destinations based on Predictive Television (TV) Viewing Data Analysis

IP.com Disclosure Number: IPCOM000240978D
Publication Date: 2015-Mar-16
Document File: 3 page(s) / 109K

Publishing Venue

The IP.com Prior Art Database

Abstract

A method and system is disclosed for recommending travel destinations based on predictive television (TV) viewing data analysis.

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Method and System for Recommending Travel Destinations based on Predictive Television (TV) Viewing Data Analysis

Smart television (TV), have become a standard and offer greater capability for viewers to navigate, watch and interact with many types of content including TV broadcast, streaming content, web content, audio content, etc. There are many different types of TV programming or content such as travel, animals, documentaries, history that have a location context. A viewer can learn a lot about places around the globe from watching TV for places the viewer has not yet traveled. For example, the viewer can learn of new information about a specific country or a river from documentaries such as, for example, longest fish of a river, or beach along a coastline. The viewer may be a frequent traveler and like to visit places the viewer learns about. One of the challenges of watching various programs and content is that there is no easy method to associate related content that is watched over a period of time for a specific location or geography. There needs a method and system that is capable of recording location related information from TV programming and performs data analysis on the location and viewer sentiment for predicting and recommend travel destinations to the viewer.

Disclosed is a method and system for recommending travel destinations based on predictive TV viewing data analysis. The method and system utilizes a software application that performs data analysis on TV content viewing patterns to determine geographic destinations and the viewer sentiment. The associated TV content location and the viewer sentiment are plotted on an electronic map available on social media.

In accordance with the method and system, the software application installed in TV analyzes the viewer's TV viewing pattern (ie. show, frequency, duration, etc.) and tracks geographic locations from metadata and analytics processing available from the content being played. The viewing data and location are then plotted in the form of an electronic map by also tracking and considering one or more objects of interest to the viewer. The software application installed tracks various types of sentiments such as, but not limited to, viewer sentiments (likes, text, voice, gestures, pattern of viewing) real time TV sentiments (gestures, object of interest and focus, audio) and social network sentiments (additional feedback from viewer, likes). Further, the social network server aggregates and correlates the gathered information from electronic map, and uses the data for predicting or recommending destinations for future travel. Alternatively, the viewer's geo interest is thus measured and accordingly related future TV programming content is recommended.

As illustrated in the Figure 1, recommendations are presented to a viewer watching a TV program. Location information being determined from analysis and plotted in an electronic map associated with the viewer's...