A Graph based collaborative and context aware recommendation system for TV programs

Download

index.pdf

Date

2014

Author

Şamdan, Emrah

Metadata

Show full item record

Item Usage Stats

226
views

96
downloads

With the increasing amount of TV programs and the integration of broadcasting and the Internet with smart TV’s, users suffer the difficulty of selecting the most appealing TV programs among various different programs available. User decisions are mostly affected by the contextual properties of programs such as the time of day, genre, actors and directors of program. This thesis proposes the design, development and evaluation of a graph based context-aware collaborative recommender system for TV programs. The proposed graph based algorithm is based on random walks performed on a tri-partite graph. The graph is constructed by using context aware pre-filtering in order to filter out programs which are irrelevant in the given context. The recommendation list generated by the graph based collaborative algorithm is updated by re-ranking the recommended items according to additional contextual variables. Thus, the proposed recommender system exploits both contextual pre- filtering and post-filtering to produce more effective recommendations. In order to measure the effectiveness of the context variables, we have implemented evaluation metrics on both context-free and contextual graph based methods. We have also tested the effects of parameters used in the graph based collaborative algorithm to the success of the recommender. The results indicate that context can provide better recommendations for TV programs. .

Subject Keywords

Television programs, Context-aware computing., Computer graphics., Recommender systems (Information filtering).

URI

http://etd.lib.metu.edu.tr/upload/12617831/index.pdf
https://hdl.handle.net/11511/24011

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

A Graph-based core model and a hybrid recommender system for TV users Taşcı, Arda; Çiçekli, Fehime Nihan; Department of Computer Engineering (2015) This thesis proposes a core model to represent user profiles in a graph-based environment which can be the base of different recommender system approaches as well as other cutting edge applications for TV domain. The proposed graph-based core model is explained in detail with node types, properties and edge weight metrics. The capabilities of this core model are described in detail. Moreover, in this thesis, a hybrid recommender system based on this core model is presented with its design, development and e...
A PARAMETRIC VIDEO QUALITY MODEL BASED ON SOURCE AND NETWORK CHARACTERISTICS Zerman, Emin; Konuk, Baris; NUR YILMAZ, GÖKÇE; Akar, Gözde (2014-10-30) The increasing demand for streaming video raises the need for flexible and easily implemented Video Quality Assessment (VQA) metrics. Although there are different VQA metrics, most of these are either Full-Reference (FR) or Reduced-Reference (RR). Both FR and RR metrics bring challenges for on-the-fly multimedia systems due to the necessity of additional network traffic for reference data. No-eference (NR) video metrics, on the other hand, as the name suggests, are much more flexible for user-end applicatio...
A TV Content Augmentation System Exploiting Rule Based Named Entity Recognition Method Isiklar, Yunus Emre; Cicekli, Nihan (2015-09-24) This paper presents a TV content augmentation system that enhances the contents of TVprograms by retrieving context related data and presenting them to the viewers without the necessity of another device. The paper presents both the conceptual description of the system and a prototype implementation. The implementation utilizes program descriptions crawled from web resources in order to extract named entities such as person names, locations, organizations, etc. For this purpose, a rule based Named Entity Re...
A New service architecture for IPTV over internet Özkardeş, Merve; Schmidt, Şenan Ece; Department of Electrical and Electronics Engineering (2013) Multimedia applications over the Internet and Internet Protocol Television (IPTV) gain a lot of attention. IPTV has a number of service requirements such as; high bandwidth, scalability, minimum delay, jitter and channel switch time. IP multicast, IMS (IP Multimedia System) Protocol and peer-to-peer approaches are proposed for implementing IPTV. However, IP multicast requires all the routers in the core network to possess multicast capability, IMS does not easily scale and P2P cannot e ciently utilize the n...
A scalable multi view audiovisual entertainment framework with content aware distribution Ekmekçioğlu, Erhan; Günel Kılıç, Banu; Dissanayake, Maheshi; Worral, Stewart; Kondoz, Ahmet (2010-09-29) Delivery of 3D immersive entertainment to the home remains a highly challenging problem due to the large amount of data involved, and the need to support a wide variety of different displays. Support of such displays may require different numbers of views, delivered over time varying networks. This requires a delivery scheme featuring scalable compression to adapt to varying network conditions, and error resiliency to overcome disturbing losses in the 3D perception. Audio and video attention models can be u...

Citation Formats

E. Şamdan, “A Graph based collaborative and context aware recommendation system for TV programs,” M.S. - Master of Science, Middle East Technical University, 2014.