OMUS: an optimized multimedia service for the home environment

详细信息    查看全文

• 作者：Simon Dooms (1)
  Toon De Pessemier (1)
  Dieter Verslype (2)
  Jelle Nelis (2)
  Jonas De Meulenaere (3)
  Wendy Van den Broeck (3)
  Luc Martens (1)
  Chris Develder (2)
  
• 关键词：Multimedia ; Information systems ; Graphical user interfaces ; DLNA ; Recommender systems ; Algorithms
• 刊名：Multimedia Tools and Applications
• 出版年：2014
• 出版时间：September 2014
• 年：2014
• 卷：72
• 期：1
• 页码：281-311
• 全文大小：1,717 KB
• 参考文献：1. Baltrunas L, Makcinskas T, Ricci F (2010) Group recommendations with rank aggregation and collaborative filtering. In: Proc. 4th ACM conf. recommender systems (RecSys 2010). ACM, New York, pp聽119鈥?26
  2. Bellandi V, Ceravolo P, Frati F, Maggesi J, Waldhart G, Seeber I (2012) Design principles for competence-based recommender systems. In: Proc. 6th IEEE conf. digital ecosystems technologies (DEST 2012). Campione d鈥橧talia, Italy, pp聽1鈥? CrossRef
  3. Bellog铆n A, Cantador I, Castells P (2010) A study of heterogeneity in recommendations for a social music service. In: Proc. 1st int. workshop information heterogeneity and fusion in recommender systems, HetRec 鈥?0. ACM, New York, pp聽1鈥? CrossRef
  4. Bennett J, Lanning S (2007) The netflix prize. In: Proc. KDD cup workshop 2007. ACM, New York, pp聽3鈥?
  5. Berkovsky S, Freyne J (2010) Group-based recipe recommendations: analysis of data aggregation strategies. In: Proc. 4th ACM conf. recommender systems (RecSys 2010). ACM, New York, pp聽111鈥?18
  6. Bollen D, Knijnenburg BP, Willemsen MC, Graus M (2010) Understanding choice overload in recommender systems. In: Proc. 4th ACM conf. recommender systems (RecSys 2010). ACM, New York, pp聽63鈥?0
  7. Brewka L, Skoldstrom P, Nelis J, Wessing H, Develder C (2011) Automatic provisioning of end-to-end QoS into the home. IEEE Trans Consum Electron 57(4):1670鈥?678 CrossRef
  8. Burke R (2000) Knowledge-based recommender systems. In: Kent A (ed) Encyclopedia of library and information systems, vol 69, supplement 32. Marcel Dekker, New York
  9. Cho SY, Seo DY, Kim TY (2002) Gateway framework for home appliance鈥檚 interoperability based on heterogeneous middleware in residential networks. In: Proc. IEEE int. conf. consumer electronics (ICCE 2002), pp聽98鈥?9
  10. De聽Pessemier T, Dooms S, Martens L (2012) Design and evaluation of a group recommender system. In: Proc. 6th ACM conf. recommender systems (RecSys 2012), RecSys 鈥?2. ACM, New York
  11. Develder C, Lambert P, Van聽Lancker W, Moens S, Van聽de Walle R, Nelis J, Verslype D, Latr S, Staelens N, Vercammen N, Vermeulen B, Masschelein B, Van聽Leeuwen T, Macq JF, Struyve K, De聽Turck F, Dhoedt B (2012) Delivering scalable video with QoS to the home. Telecommun Syst 49(1):129鈥?48 CrossRef
  12. Dooms S, De聽Pessemier T, Martens L (2011) A user-centric evaluation of recommender algorithms for an event recommendation system. In: UCERSTI workshop on user-centric evaluation of recommender systems and their interfaces鈥?. Chicago, IL, USA
  13. Guedes A, Santos D, do聽Nascimento J, Sales L, Perkusich A, Almeida H (2008) Set your multimedia application free with BRisa framework: an open source UPnP implementation for resource limited devices. In: Proc. consumer communications and networking conference (CCNC 2008), pp聽1257鈥?258
  14. Jameson A, Smyth B (2007) The adaptive web. chap. Recommendation to groups. Springer, Berlin, pp聽596鈥?27 CrossRef
  15. Jannach D, Zanker M, Felfernig A, Friedrich G (2011) Recommender systems: an introduction. Cambridge University Press, Cambridge
  16. Jeronimo M, Weast J (2003) UPnP design by example: a software developer鈥檚 guide to universal plug and play. Intel Press
  17. Kang DO, Kang K, Choi SG, Lee J (2005) UPnP AV architectural multimedia system with a home gateway powered by the OSGi platform. In: Proc. IEEE int. conf. consumer electronics (ICCE 2005), pp聽405鈥?06
  18. Kawamoto E, Kadowaki K, Koita T, Sato K (2009) Content sharing among UPnP gateways on unstructured P2P network using dynamic overlay topology optimization. In: Proc. consumer communications and networking conference (CCNC 2009), pp 1鈥?
  19. Kim DS, Lee JM, Kwon WH, Yuh IK (2002) Design and implementation of home network systems using UPnP middleware for networked appliances. IEEE Trans Consum Electron 48(4):963鈥?72
  20. Kim JT, Oh YJ, Lee HK, Paik EH, Park KR (2007) Implementation of the DLNA proxy system for sharing home media contents. In: IEEE trans. consumer electronics (ICCE 2007), pp 1鈥?
  21. Lee HY, Kim JW (2007) An approach for content sharing among UPnP devices in different home networks. IEEE Trans Consum Electron 53(4):1419鈥?426 CrossRef
  22. Masthoff J (2004) Group modeling: selecting a sequence of television items to suit a group of viewers. User Model User-Adapt Interact 14(1):37鈥?5 CrossRef
  23. McCarthy JF, Anagnost TD (1998) Musicfx: an arbiter of group preferences for computer supported collaborative workouts. In: Proc. 1998 ACM conf. computer supported cooperative work, CSCW 鈥?8. ACM, New York, pp 363鈥?72 CrossRef
  24. Mobasher B (2007) Recommender systems. In: Kunstliche intelligenz, special issue on web mining, vol聽3. Bottcher IT Verlag, Bremen, pp聽41鈥?3
  25. Nelis J, Verschueren T, Verslype D, Develder C (2012) DYAMAND: DYnamic, Adaptive MAnagement of Networks and Devices. In: Proc. 37th IEEE conf. local computer netw. (LCN 2012). Clearwater, Florida, USA
  26. Nelis J, Verslype D, Develder C (2011) Intelligent distributed multimedia collection: content aggregation and integration. In: Proc. 36th IEEE conf. local computer networks (LCN 2011). Bonn, Germany, pp聽203鈥?07
  27. O鈥機onnor M, Cosley D, Konstan JA, Riedl J (2001) Polylens: a recommender system for groups of users. In: Proc. 7th Eur. conf. computer supported cooperative work, ECSCW鈥?1. Kluwer Academic Publishers, Norwell, pp 199鈥?18
  28. Purcell K (2010) The state of online video. Tech. rep., PewResearchCenter
  29. Resnick P, Iacovou N, Suchak M, Bergstrom P, Riedl J (1994) Grouplens: an open architecture for collaborative filtering of netnews. In: Proc. ACMF conf. on computer supported cooperative work, CSCW 鈥?4. ACM, New York, pp 175鈥?86
  30. Sales T, Sales L, Pereira M, Almeida H, Perkusich A, Gorg么nio K, de Sales MA (2008) Towards the UPnP-UP: enabling user profile to support customized services in UPnP networks. In: Proc. 2nd int. conf. on mobile ubiquitous computing, systems, services and technologies, UBICOMM 鈥?8. IEEE Computer Society, Washington, pp 206鈥?11 CrossRef
  31. Shani G, Gunawardana A (2011) Evaluating recommendation systems. In: Recommender systems handbook, pp 257鈥?97
  32. Van聽den Broeck W (2011) From analogue to digital: the silent (r)evolution? A qualitative study on the domestication of interactive digital television in flanders. Ph.D. thesis, Vrije Universiteit Brussel, Brussels
  
• 作者单位：Simon Dooms (1)
  Toon De Pessemier (1)
  Dieter Verslype (2)
  Jelle Nelis (2)
  Jonas De Meulenaere (3)
  Wendy Van den Broeck (3)
  Luc Martens (1)
  Chris Develder (2)
  
  1. WiCa, iMinds-Ghent University, G. Crommenlaan 8 box 201, 9050, Ghent, Belgium
  2. IBCN, iMinds-Ghent University, G. Crommenlaan 8 box 201, 9050, Ghent, Belgium
  3. SMIT, iMinds-VUB, Pleinlaan 9, 1050, Brussels, Belgium
  
• ISSN：1573-7721

文摘

Media content in home environments is often scattered across multiple devices in the home network. As both the available multimedia devices in the home (e.g., smartphones, tablets, laptops, game consoles, etc.) and the available content (video and audio) is increasing, interconnecting desired content with available devices is becoming harder and home users are experiencing difficulties in selecting interesting content for their current context. In this paper, we start with an analysis of the home environment by means of a user study. Information handling problems are identified and requirements for a home information system formulated. To meet these requirements we propose the OMUS home information system which includes an optimized content aggregation framework, a hybrid group-based contextual recommender system, and an overall web-based user interface making both content and recommendations available for all devices across the home network. For the group recommendations we introduced distinct weights for each user and showed that by varying the weights, the coverage (i.e., items that can be returned by the recommender) considerably increases. Also the addition of genre filter functionality was proven to further boost the coverage. The OMUS system was evaluated by means of focus groups and by qualitative and quantitative performance assessment of individual parts of the system. The modularity of internal components and limited imposed hardware requirements implies flexibility as to how the OMUS system can be deployed (ranging from e.g., embedded in hardware devices or more software services based).