11,440 research outputs found
Community Detection on Evolving Graphs
Clustering is a fundamental step in many information-retrieval and data-mining applications. Detecting clusters in graphs is also a key tool for finding the community structure in social and behavioral networks. In many of these applications, the input graph evolves over time in a continual and decentralized manner, and, to maintain a good clustering, the clustering algorithm needs to repeatedly probe the graph. Furthermore, there are often limitations on the frequency of such probes, either imposed explicitly by the online platform (e.g., in the case of crawling proprietary social networks like twitter) or implicitly because of resource limitations (e.g., in the case of crawling the web). In this paper, we study a model of clustering on evolving graphs that captures this aspect of the problem. Our model is based on the classical stochastic block model, which has been used to assess rigorously the quality of various static clustering methods. In our model, the algorithm is supposed to reconstruct the planted clustering, given the ability to query for small pieces of local information about the graph, at a limited rate. We design and analyze clustering algorithms that work in this model, and show asymptotically tight upper and lower bounds on their accuracy. Finally, we perform simulations, which demonstrate that our main asymptotic results hold true also in practice
Challenges in Bridging Social Semantics and Formal Semantics on the Web
This paper describes several results of Wimmics, a research lab which names
stands for: web-instrumented man-machine interactions, communities, and
semantics. The approaches introduced here rely on graph-oriented knowledge
representation, reasoning and operationalization to model and support actors,
actions and interactions in web-based epistemic communities. The re-search
results are applied to support and foster interactions in online communities
and manage their resources
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Prevention is a solution: building the HIVe
This Special Issue of Digital Culture and Education (DCE), Building the HIVe, offers relevant and applicable examples of digital technologies being leveraged, positioned and practiced towards community-based and led HIV prevention as a solution in a digital era. The contributors to this Special Issue, frontline workers, activists, researchers and educators alike, have taken risks as they have explored innovative prevention approaches with and through digital technologies, and documented and analysed their pedagogical innovations in different cultural contexts. Importantly this Special Issue also includes the critical voices and leadership of individuals living with HIV as designers of prevention as a solution. Their timely insights, advice and understandings of HIV prevention as a solution merit close scrutiny as evidence of resourceful, imaginative and critical endeavour; they are offered to share successful interventions and stimulate further discussion
Effects of Knowledge Base Quality on Peer-to-peer Information Propagation
Peer reviewedPublisher PD
Technology Integration around the Geographic Information: A State of the Art
One of the elements that have popularized and facilitated the use of geographical information on a variety of computational applications has been the use of Web maps; this has opened new research challenges on different subjects, from locating places and people, the study of social behavior or the analyzing of the hidden structures of the terms used in a natural language query used for locating a place. However, the use of geographic information under technological features is not new, instead it has been part of a development and technological integration process. This paper presents a state of the art review about the application of geographic information under different approaches: its use on location based services, the collaborative user participation on it, its contextual-awareness, its use in the Semantic Web and the challenges of its use in natural languge queries. Finally, a prototype that integrates most of these areas is presented
The Fog Makes Sense: Enabling Social Sensing Services With Limited Internet Connectivity
Social sensing services use humans as sensor carriers, sensor operators and
sensors themselves in order to provide situation-awareness to applications.
This promises to provide a multitude of benefits to the users, for example in
the management of natural disasters or in community empowerment. However,
current social sensing services depend on Internet connectivity since the
services are deployed on central Cloud platforms. In many circumstances,
Internet connectivity is constrained, for instance when a natural disaster
causes Internet outages or when people do not have Internet access due to
economical reasons. In this paper, we propose the emerging Fog Computing
infrastructure to become a key-enabler of social sensing services in situations
of constrained Internet connectivity. To this end, we develop a generic
architecture and API of Fog-enabled social sensing services. We exemplify the
usage of the proposed social sensing architecture on a number of concrete use
cases from two different scenarios.Comment: Ruben Mayer, Harshit Gupta, Enrique Saurez, and Umakishore
Ramachandran. 2017. The Fog Makes Sense: Enabling Social Sensing Services
With Limited Internet Connectivity. In Proceedings of The 2nd International
Workshop on Social Sensing, Pittsburgh, PA, USA, April 21 2017
(SocialSens'17), 6 page
Adaptive service discovery on service-oriented and spontaneous sensor systems
Service-oriented architecture, Spontaneous networks, Self-organisation, Self-configuration, Sensor systems, Social patternsNatural and man-made disasters can significantly impact both people and environments. Enhanced effect can be achieved through dynamic networking of people, systems and procedures and seamless integration of them to fulfil mission objectives with service-oriented sensor systems. However, the benefits of integration of services will not be realised unless we have a dependable method to discover all required services in dynamic environments. In this paper, we propose an Adaptive and Efficient Peer-to-peer Search (AEPS) approach for dependable service integration on service-oriented architecture based on a number of social behaviour patterns. In the AEPS network, the networked nodes can autonomously support and co-operate with each other in a peer-to-peer (P2P) manner to quickly discover and self-configure any services available on the disaster area and deliver a real-time capability by self-organising themselves in spontaneous groups to provide higher flexibility and adaptability for disaster monitoring and relief
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