Exploratory Search of Web Data Services Based on Collective Intelligence

Author(s):  
Devis Bianchini ◽  
Valeria De Antonellis ◽  
Michele Melchiori
Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1204
Author(s):  
Jinhwa Jung ◽  
Donghyeok An

Internet traffic is experiencing rapid growth, with the majority of traffic generated from video steaming, web data services and Internet of Things. As these services include the transmission of small data, such as web pages, video chunks and sensing data, data latency affects the quality of experience rather than the throughput. Therefore, this study aims to decrease latency to improve the quality of the user experience. To this end, we measure the web service delay and throughput in mobile networks. The results indicate a low quality experience for mobile users, even though mobile networks support a large throughput. We therefore propose a light-weight latency reduction scheme for the Quick UDP Internet Connections (QUIC) protocol. The proposed scheme calculates the average congestion window, which is utilized as the initial congestion window when a new connection is established. The proposed scheme is evaluated through experiments on a testbed. The results show that our scheme reduces latency significantly. The results of this study can help improve user experiences of video streaming and web data services.


2013 ◽  
Vol 7 (4) ◽  
pp. 1-33 ◽  
Author(s):  
Silvia Quarteroni ◽  
Marco Brambilla ◽  
Stefano Ceri
Keyword(s):  
Web Data ◽  

2013 ◽  
Vol 22 (5) ◽  
pp. 641-663 ◽  
Author(s):  
Alessandro Bozzon ◽  
Marco Brambilla ◽  
Stefano Ceri ◽  
Davide Mazza

2020 ◽  
Vol 17 (4) ◽  
pp. 1-14
Author(s):  
Abdelhamid Malki ◽  
Sidi Mohammed Benslimane ◽  
Mimoun Malki

Data mashups are web applications that combine complementary (raw) data pieces from different data services or web data APIs to provide value added information to users. They became so popular over the last few years; their applications are numerous and vary from addressing transient business needs in modern enterprises. Even though data mashups have been the focus of many research works, they still face many challenging issues that have never been explored. The ranking of the data returned by a data mashup is one of the key issues that have received little consideration. Top-k query model ranks the pertinent answers according to a given ranking function and returns only the best results. This paper proposes two algorithms that optimize the evaluation of top-k queries over data mashups. These algorithms are built based on the web data APIs' access methods: bind probe and indexed probe.


Author(s):  
Takashi Ikegami ◽  
Yoh-ichi Mototake ◽  
Shintaro Kobori ◽  
Mizuki Oka ◽  
Yasuhiro Hashimoto

A large group with a special structure can become the mother of emergence. We discuss this hypothesis in relation to large-scale boid simulations and web data. In the boid swarm simulations, the nucleation, organization and collapse dynamics were found to be more diverse in larger flocks than in smaller flocks. In the second analysis, large web data, consisting of shared photos with descriptive tags, tended to group together users with similar tendencies, allowing the network to develop a core–periphery structure. We show that the generation rate of novel tags and their usage frequencies are high in the higher-order cliques. In this case, novelty is not considered to arise randomly; rather, it is generated as a result of a large and structured network. We contextualize these results in terms of adjacent possible theory and as a new way to understand collective intelligence. We argue that excessive information and material flow can become a source of innovation. This article is part of the themed issue ‘Reconceptualizing the origins of life’.


Author(s):  
Jiangning Cui ◽  
Taoying Liu ◽  
Qian Chen ◽  
Hong Liu
Keyword(s):  
Web Data ◽  

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