Modelling user habits and providing recommendations based on the hybrid broadcast broadband television using neural networks

A Smart Program Recommender System Based on the Hybrid Broadcast Broadband Television

“…As before [1] the list of the genres is taken from the European Standard "Digital Video Broadcasting (DVB); Specification for Service Information (SI) in DVB systems" [22] with additional non-standard genres, "Turkish Movie (TM)", "Turkish Drama (TD)", "Foreign Movie (FM)", and "Foreign Drama (FD)", thinking that separate genres would give better results and beneficial to the Turkish consumers since local movies and dramas are very popular in Turkey.…”

“…The method proposed here is an improved version of the original work of Topalli and Kilinc [1]. Tasks are again shared between the receiver and the server, lighter tasks such as data collection and recommendation presentation are carried on the receiver whereas heavy tasks such as GA clustering and ANN learning are performed on the server side.…”

“…Since HbbTV is a widely accepted public consumer electronics standard for digital receivers and most of the recent devices support it, like the original work [1] the model proposed here is also device-agnostic and can reach many people using different consumer devices.…”

“…The method proposed here focuses on the improvements of this previous work [1], when a large number of users are present, a case more close to the real world. For this purpose, a data set is collected from 248 people.…”

“…The work of Topalli and Kilinc [1] also gives a summary of recent works about the television program recommendation systems for both Internet connected and unconnected devices which are DVB (digital video broadcasting) or IPTV based [3]- [14]. But none of the works aforementioned there has used a worldwide specification like HbbTV for data gathering or content recommendation.…”