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This paper presents novel algorithms which are able to generate recommendations within a heterogeneous service environment. In this work explicitly set preferences as well as implicitly logged viewing behavior are employed to generate recommendations for Digital Video Broadcast (DVB) content. This paper also discusses the similarity between the DVB genres and YouTube categories. In addition it presents results to show the comparison between well known collaborative filtering methods. The outcome of this comparison study is used to identify the most suitable filtering method to use in the proposed environment. Finally the paper presents a novel Personal Program Guide (PPG), which is used as a tool to visualize the generated recommendations within a heterogeneous service environment. This PPG is also capable of showing the linear DVB content and the non-linear YouTube videos in a single view.
Keywords Personalized television – Recommendations – Content-based – Collaborative filtering – Similarity – Media convergence – Personal Program Guide – DVB – YouTube
A social network perspective on the management of product development programs
Jan Kratzera, , , Roger Th.A.J. Leendersb, 1, , Jo M.L. van Engelenb, 1,
a
Berlin Institute of Technology, Strasse des 17. Juni 135, 10623 Berlin, Germany
b
University of Groningen, P.O. Box 800, 9700 AV Groningen, The Netherlands
Available online 17 October 2009.
Abstract
Creativity is essential to the performance of product development programs (PDPs). Most PDPs are designed around teams that jointly work together according to the product decomposition into components, the design and development procedure, and the methods of the final integration. Since the creative product development task requires the teams to combine and integrate input from multiple other teams, the team's structure of interaction is an important determinant of their creativity. In research and practice, however, little is known about the social networks of the teams and their creativity within PDPs. In this study we investigate different structural aspects of social networks of such teams and their creativity within two multinational PDPs. The main results of our investigation imply that many direct network contacts around a weekly intensity stimulate the creativity of teams of PDPs, whereas very open networks with a high information variety minimizes the team's creativity.
Keywords:Social Networks; Creativity; Product development programs; Space research; Regression
Project Management Graduate Programme, Room 335 PNR, J05, Faculty of Engineering and Information Technologies, The University of Sydney NSW 2006, Australia
Available online 30 October 2009.
Abstract
We present a study exploring the connection between social networks and collaborative process. We focus on exploring academics' network position and its effect on their collaborative networks. In this paper, we discuss two types of networks of collaboration—(i) citation; and, (ii) co authorship. We explore the effects of social networks on these two types of collaborative process. By defining network position in this way, we develop a social network that uses the academics as nodes within the network instead of each published paper. We obtained the collaboration data through archival records (i.e. Web of Science) and examined the interactions among different actors from the archival records for determining the existence and strength of relations between actors.
Project Management Graduate Programme, The University of Sydney, NSW 2006, Australia
b
Accenture, Sydney, Australia
Available online 27 March 2009.
Abstract
The technology acceptance model (TAM) has been widely used to study user acceptance of new computer technologies. However, it does not incorporate social structure and influence as a significant factor. In this study, we ask the following questions: (i) What are the limitations of the existing TAM for studying virtual community? (ii) What is effect of social networks on user acceptance of technology for virtual community? and (iii) How can the influence of different types of social ties serve as a basis for exploring the user acceptance of technology in a virtual community? Here, we explore the possibility for extending TAM to incorporate the influence of the different types of social ties as a new theoretical construct. Preliminary analysis of data from a virtual community results show that weak and strong ties influence technology acceptance. The findings enable HCI researchers to account for influence of social ties in future investigations using TAM.
Keywords:Technology acceptance; User behaviour; Strong ties; Weak ties; Social networks; Virtual community
There are two kinds of uncertainty for providing green service over Internet of Things (IoT): network service period and user satisfaction model. In this paper, we consider a power-aware service problem over IoT where both of the uncertainties are incorporated. Specifically, we consider a generic IoT’s service scenario: a server provides different kinds of services without knowledge of user satisfaction model and network service period. Our objective aims at dynamically adjusting the power allocation for each service over a uncertain period to maximize expected user satisfaction. It should be noted that practical user satisfaction rate is observed over time, but the inherent functional relationship between the power and satisfaction rate is unknown. In order to present a quantitative analysis, we consider a general user satisfaction model belonging to a class of functions that do not deploy any parametric representation. In this case, a blind dynamic powering algorithm is developed, in which one learns the satisfaction function and optimizes power-aware user satisfaction with on-line operation. More precisely, the algorithm performance is measured in terms of regret which denotes the satisfaction loss compared to the optimal satisfactions that can be obtained when the service period and satisfaction rate are known. Moreover, a tight bound on this regret is proposed for any possible powering policy, and we show that the proposed algorithm can achieve a regret that is close to this bound.
Keywords Internet of Things – Green service – Dynamic powering – Satisfaction model
The increasing use of wireless Internet and smartphone has accelerated the need for pervasive and ubiquitous computing (PUC). Smartphones stimulate growth of location-based service and mobile cloud computing. However, smartphone mobile computing poses challenges because of the limited battery capacity, constraints of wireless networks and the limitations of device. A fundamental challenge arises as a result of power-inefficiency of location awareness. The location awareness is one of smartphone’s killer applications; it runs steadily and consumes a large amount of power. Another fundamental challenge stems from the fact that smartphone mobile devices are generally less powerful than other devices. Therefore, it is necessary to offload the computation-intensive part by careful partitioning of application functions across a cloud. In this paper, we propose an energy-efficient location-based service (LBS) and mobile cloud convergence. This framework reduces the power dissipation of LBSs by substituting power-intensive sensors with the use of less-power-intensive sensors, when the smartphone is in a static state, for example, when lying idle on a table in an office. The substitution is controlled by a finite state machine with a user-movement detection strategy. We also propose a seamless connection handover mechanism between different access networks. For convenient on-site establishment, our approach is based on the end-to-end architecture between server and a smartphone that is independent of the internal architecture of current 3G cellular networks.
Keywords Low-power location awareness – Location-based service – Mobile cloud offloading – Connection handover – Pervasive and ubiquitous computing – Cloud computing
SXSW秀展有個脫穎而出的隊伍是一家讓你到一家餐廳用你的手機掃描 QR 碼就可以把你放入他們的後補名單中。這個 QR 碼是一個廣為平常的一個印在產品包裝上或是任何物品上的碼。在美國很常是印在產品包裝上所以如果你在逛街看到一個產品了話，你如果想要更了解這個產品了話，可以用你的手機特別的軟體掃描這個 QR 碼，然後這個軟體或是網路會回覆給你更多有關這個產品的資訊，以助你做你的購買決定。
Groupon is arguably the biggest deals provider on the web and the company has used its clout to launch Groupon Now!—an application that offers time-specific daily deals based on GPS location.
The Groupon Now! app is synced with your Groupon account, so when you download it to your smartphone, your credit card and account information is automatically transferred. When accessed on a smartphone, Groupon Now!’s simple interface offers two categories for deals: “I’m Hungry” and “I’m Bored.”
The deals listed in each category correspond to the user’s smartphone GPS, so they can be redeemed for vendors in the immediate vicinity.
So, if you’re going to lunch and looking for an instant bargain, you just have to head out to the street and pull upGroupon Now! on your phone to connect with a local, affordable option.
On the web, Groupon organizes the instant deals into categories based on the things people like to do, like massages in “Get Pampered”, teeth whitening in “Take Care of Myself” and discovery flights in “Have Fun.” There are also self-explanatory categories like “Eat Something”, “Get Flowers” and “Take a Class.”
Unlike the regular Groupon Daily Deal, Groupon Now! deals are only available for limited amounts of time—typically two or three hours, when vendors are looking to fill their seats.
Groupon Now! presents a win-win situation for consumers and local businesses—the consumers get great, relevant and useful deals, and merchants can take advantage of the opportunity to boost sales and offer deals on slow business days.
“We want people to think about Groupon every time they walk out the door,” Groupon Founder and CEO Andrew Mason told Bloomberg Businessweek.
“For merchants, the daily deal is like teeth whitening, and Groupon Now! Is like brushing your teeth. It can be an everyday thing to keep your business going.”
LivingSocial Instant
Although LivingSocial was founded before Groupon, the company didn’t start offering daily deals until Groupontook off. Since then, history has proven that any time Groupon leaps, LivingSocial follows (it’s not as if it has much of a choice, anyhow).
In order to stand up to Groupon Now! LivingSocial has developed LivingSocial Instant.
Similarly to Groupon Now!, LivingSocial Instant serves up real-time deals that are redeemable at local vendors and available for limited windows of time. LivingSocial Instant is currently only available in Washington D.C., New York and San Francisco, but the company plans to roll-out to more U.S. locations in coming months.
LivingSocial celebrated its launch in all three cities with a Dollar Lunch Day promotion, which sent instant $1 lunch offers within walking distance to smartphones with the app within city limits.
LivingSocial commits to increasing profitability for partner merchants by aligning them with a local contact who works with them to determine a marketable offer structure.
“If you look at it from a consumer perspective, merchants can basically tell you how much they want your business, and if you look at it from a merchant perspective, if they’re having a slow lunch rush and it’s 12:30, they have an immediate way to juice that,” LivingSocial’s CEO Tim O’Shaughnessy told Business Insider.
Zaarly
Say you want to buy an iPad, a concert for your office or even a spacesuit but you yearn for the simplicity of touch-screen picking and choosing from your mobile phone.
Zaarly’s got you covered.
Zaarly operates much like an ultra-hip, technologically superior hybrid of Craigslist and eBay. It’s a localized, auction-style marketplace that allows users to search for and purchase items from other users on theirsmartphones.
As with Craigslist, users can make requests for whatever their hearts fancy, no matter how bizarre they may be.
“We facilitate in-person transactions so it is hyper-local in the truest sense,” said one of Zaarly’s founders, BoFishback. “If you want to pay $50 for someone to bring you a pizza and you want it in the next 45 minutes, you post it on Zaarly and we make sure it gets as broadly syndicated as possible. People who are willing to fulfill that order for you, in that amount of time, for that amount of money, can make it happen.”
The startup company was founded by Fishback, Eric Koester and Ian Hunter during a 54-hour cram session at February’s Los Angeles Startup Weekend competition. Within three weeks, Zaarly went live during the 2011 South by Southwest Festival in Austin, Texas.
Earlier this year, Zaarly rounded up $1 million in funding from some angel investors, including Ashton Kutcher andLightbank, a venture fund created by the founders of Groupon.
