Results 11 - 20
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718
Do Life-logging Technologies Support Memory for the Past? An Experimental Study Using Sensecam
- In Proc. CHI 2007, ACM Press
, 2007
"... We report on the results of a study using SenseCam, a ―lifelogging‖ technology in the form of a wearable camera, which aims to capture data about everyday life in order to support people‘s memory for past, personal events. We find evidence that SenseCam images do facilitate people‘s ability to conne ..."
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Cited by 83 (7 self)
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We report on the results of a study using SenseCam, a ―lifelogging‖ technology in the form of a wearable camera, which aims to capture data about everyday life in order to support people‘s memory for past, personal events. We find evidence that SenseCam images do facilitate people‘s ability to connect to their past, but that images do this in different ways. We make a distinction between ―remembering ‖ the past, and ―knowing ‖ about it, and provide evidence that SenseCam images work differently over time in these capacities. We also compare the efficacy of user-captured images with automatically captured images and discuss the implications of these findings and others for how we conceive of and make claims about life-logging technologies.
An Empirical Study of Geographic User Activity Patterns in Foursquare
"... We present a large-scale study of user behavior in Foursquare, conducted on a dataset of about 700 thousand users that spans a period of more than 100 days. We analyze user checkin dynamics, demonstrating how it reveals meaningful spatio-temporal patterns and offers the opportunity to study both use ..."
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Cited by 83 (3 self)
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We present a large-scale study of user behavior in Foursquare, conducted on a dataset of about 700 thousand users that spans a period of more than 100 days. We analyze user checkin dynamics, demonstrating how it reveals meaningful spatio-temporal patterns and offers the opportunity to study both user mobility and urban spaces. Our aim is to inform on how scientific researchers could utilise data generated in Location-based Social Networks to attain a deeper understanding of human mobility and how developers may take advantage of such systems to enhance applications such as recommender systems.
Optimal and scalable distribution of content updates over a mobile social network
- In Proc. IEEE INFOCOM
, 2009
"... Number: CR-PRL-2008-08-0001 ..."
The diameter of opportunistic mobile networks
, 2007
"... Portable devices have more data storage and increasing communication capabilities everyday. In addition to classic infrastructure based communication, these devices can exploit human mobility and opportunistic contacts to communicate. We analyze the characteristics of such opportunistic forwarding p ..."
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Cited by 75 (15 self)
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Portable devices have more data storage and increasing communication capabilities everyday. In addition to classic infrastructure based communication, these devices can exploit human mobility and opportunistic contacts to communicate. We analyze the characteristics of such opportunistic forwarding paths. We establish that opportunistic mobile networks in general are characterized by a small diameter, a destination device is reachable using only a small number of relays under tight delay constraint. This property is first demonstrated analytically on a family of mobile networks which follow a random graph process. We then establish the validity of this result empirically with four data sets capturing human mobility, using a new methodology to efficiently compute all the paths that impact the diameter of an opportunistic mobile networks. We complete our analysis of network diameter by studying the impact of intensity of contact rate and contact duration. This work is, to our knowledge, the first validation that the so called “small world ” phenomenon applies very generally to opportunistic networking between mobile nodes. 1.
Mobility Detection Using Everyday GSM Traces
- in Proceedings of the Eighth International Conference on Ubiquitous Computing (Ubicomp 2006
, 2006
"... Abstract. Recognition of everyday physical activities is difficult due to the challenges of building informative, yet unobtrusive sensors. The most widely deployed and used mobile computing device today is the mobile phone, which presents an obvious candidate for recognizing activities. This paper e ..."
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Cited by 69 (7 self)
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Abstract. Recognition of everyday physical activities is difficult due to the challenges of building informative, yet unobtrusive sensors. The most widely deployed and used mobile computing device today is the mobile phone, which presents an obvious candidate for recognizing activities. This paper explores how coarse-grained GSM data from mobile phones can be used to recognize high-level properties of user mobility, and daily step count. We demonstrate that even without knowledge of observed cell tower locations, we can recognize mobility modes that are useful for several application domains. Our mobility detection system was evaluated with GSM traces from the everyday lives of three data collectors over a period of one month, yielding an overall average accuracy of 85%, and a daily step count number that reasonably approximates the numbers determined by several commercial pedometers. 1
Routing in Socially Selfish Delay Tolerant Networks
"... Abstract—Existing routing algorithms for Delay Tolerant Networks (DTNs) assume that nodes are willing to forward packets for others. In the real world, however, most people are socially selfish; i.e., they are willing to forward packets for nodes with whom they have social ties but not others, and s ..."
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Cited by 67 (8 self)
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Abstract—Existing routing algorithms for Delay Tolerant Networks (DTNs) assume that nodes are willing to forward packets for others. In the real world, however, most people are socially selfish; i.e., they are willing to forward packets for nodes with whom they have social ties but not others, and such willingness varies with the strength of the social tie. Following the philosophy of design for user, we propose a Social Selfishness Aware Routing (SSAR) algorithm to allow user selfishness and provide better routing performance in an efficient way. To select a forwarding node, SSAR considers both users ’ willingness to forward and their contact opportunity, resulting in a better forwarding strategy than purely contact-based approaches. Moreover, SSAR formulates the data forwarding process as a Multiple Knapsack Problem with Assignment Restrictions (MKPAR) to satisfy user demands for selfishness and performance. Trace-driven simulations show that SSAR allows users to maintain selfishness and achieves better routing performance with low transmission cost. I.
Exploiting place features in link prediction on location-based social networks.
- In KDD,
, 2011
"... ABSTRACT Link prediction systems have been largely adopted to recommend new friends in online social networks using data about social interactions. With the soaring adoption of locationbased social services it becomes possible to take advantage of an additional source of information: the places peo ..."
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Cited by 67 (5 self)
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ABSTRACT Link prediction systems have been largely adopted to recommend new friends in online social networks using data about social interactions. With the soaring adoption of locationbased social services it becomes possible to take advantage of an additional source of information: the places people visit. In this paper we study the problem of designing a link prediction system for online location-based social networks. We have gathered extensive data about one of these services, Gowalla, with periodic snapshots to capture its temporal evolution. We study the link prediction space, finding that about 30% of new links are added among "place-friends", i.e., among users who visit the same places. We show how this prediction space can be made 15 times smaller, while still 66% of future connections can be discovered. Thus, we define new prediction features based on the properties of the places visited by users which are able to discriminate potential future links among them. Building on these findings, we describe a supervised learning framework which exploits these prediction features to predict new links among friends-of-friends and place-friends. Our evaluation shows how the inclusion of information about places and related user activity offers high link prediction performance. These results open new directions for realworld link recommendation systems on location-based social networks.
Recruitment Framework for Participatory Sensing Data Collections
"... Abstract. Mobile phones have evolved from devices that are just used for voice and text communication to platforms that are able to capture and transmit a range of data types (image, audio, and location). The adoption of these increasingly capable devices by society has enabled a potentially pervasi ..."
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Cited by 67 (2 self)
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Abstract. Mobile phones have evolved from devices that are just used for voice and text communication to platforms that are able to capture and transmit a range of data types (image, audio, and location). The adoption of these increasingly capable devices by society has enabled a potentially pervasive sensing paradigm- participatory sensing. A coordinated participatory sensing system engages individuals carrying mobile phones to explore phenomena of interest using in situ data collection. For participatory sensing to succeed, several technical challenges need to be solved. In this paper, we discuss one particular issue: developing a recruitment framework to enable organizers to identify well-suited participants for data collections based on geographic and temporal availability as well as participation habits. This recruitment system is evaluated through a series of pilot data collections where volunteers explored sustainable processes on a university campus.
A socio-aware overlay for publish/subscribe communication in delay tolerant networks
- In Proc. MSWiM
, 2007
"... The emergence of Delay Tolerant Networks (DTNs) has culminated in a new generation of wireless networking. We focus on a type of human-to-human communication in DTNs, where human behaviour exhibits the characteristics of networks by forming a community. We show the characteristics of such networks f ..."
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Cited by 65 (1 self)
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The emergence of Delay Tolerant Networks (DTNs) has culminated in a new generation of wireless networking. We focus on a type of human-to-human communication in DTNs, where human behaviour exhibits the characteristics of networks by forming a community. We show the characteristics of such networks from extensive study of realworld human connectivity traces. We exploit distributed community detection from the trace and propose a Socio-Aware Overlay over detected communities for publish/subscribe communication. Centrality nodes have the best visibility to the other nodes in the network. We create an overlay with such centrality nodes from communities. Distributed community detection operates when nodes (i.e. devices) are in contact by gossipping, and subscription propagation is performed along with this operation. We validate our message dissemination algorithms for publish/subscribe with connectivity traces.
