With a plethora of sensors and ubiquitous access to the Internet, modern smartphones have enabled a broad range of context-based applications. Most applications make use of the user's physical location to filter r...
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With a plethora of sensors and ubiquitous access to the Internet, modern smartphones have enabled a broad range of context-based applications. Most applications make use of the user's physical location to filter relevant content. However, filtering based on dynamic contextual information results in high complexity of the filtering process. This limits the applicability of existing publish/subscribe systems, as they rely on aggregation of filters and fast decentralized matching and forwarding. In this work, we propose a mechanism for transitions between different filter schemes for location-based services. Our mechanism adapts the filtering process to the dynamics in user behavior and resulting load by trading computational complexity at the broker against communication overhead and computational complexity at the mobile client. We integrate our mechanism into an existing publish/subscribe system and evaluate transitions between a context-based filter scheme and two channel-based filter schemes, showing the applicability of our approach.
The proceedings contain 25 papers. The special focus in this conference is on 2nd international workshop on emerging technologies for smart devices, ETSD 2014, 2nd international workshop on marine sensors and systems,...
ISBN:
(纸本)9783662463376
The proceedings contain 25 papers. The special focus in this conference is on 2nd international workshop on emerging technologies for smart devices, ETSD 2014, 2nd international workshop on marine sensors and systems, MARSS 2014, multimedia wireless ad hoc networks 2014, MWaoN 2014, 2nd smart sensor protocols and algorithms - SSPA2014 and 8th international workshop on wireless sensor and actuator and robot networks - WiSARN 2014. The topics include: multimediacontent delivery between mobile cloud and mobile devices;delayed key exchange for constrained smart devices;the time calibration system of KM3NET: the laser beacon and the nanobeacon;adaptive data collection in sparse underwater sensor networks using mobile elements;cross layer ant based routing protocol for wireless multimedia sensor network;access and resources reservation in 4G-VANETs for multimedia applications;a smart M2M deployment to control the agriculture irrigation;a location prediction based data gathering protocol for wireless sensor networks using a mobile sink;virtual localization for robust geographic routing in wireless sensor networks and micro robots for dynamic sensor networks.
With the continuous rise of multimedia, the question of how to access large-scale multimedia databases efficiently has become of crucial importance. Given a multimedia database comprising millions of multimedia object...
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ISBN:
(纸本)9781450337946
With the continuous rise of multimedia, the question of how to access large-scale multimedia databases efficiently has become of crucial importance. Given a multimedia database comprising millions of multimedia objects, how to approximate the content-based properties of the corresponding feature representations in order to carry out similarity search efficiently and with high accuracy? In this paper, we propose the concept of gradient-based signatures in order to aggregate content-based features of multimedia objects by means of generative models. We provide theoretical insights into our approach including closed-form expressions for the computation of gradient-based signatures with respect to Gaussian mixture models and additionally investigate different binarization methods for gradient-based signatures in order to query databases comprising millions of multimedia objects with high accuracy in less than one second.
Recommender systems have been widely used in e-commerce platforms, such as Amazon and Taobao. Among the available recommendation algorithms, Item Collaborative Filtering (ItemCF) Algorithm and content Filtering Algori...
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ISBN:
(纸本)9781631901041
Recommender systems have been widely used in e-commerce platforms, such as Amazon and Taobao. Among the available recommendation algorithms, Item Collaborative Filtering (ItemCF) Algorithm and content Filtering Algorithm have gained wide adoption because of various strengths. For example, hidden interests can be digged so as to get fresh recommendations, and highly individual recommendations can be made. Despite their strengths and wide adoption, there are still some weaknesses associated with them. One representative weakness is the existence of duplicated, and outdated recommendations due to the lack of purchasing cycles, e.g., weekly or seasonal, of goods. We name such cycles Commodity Purchase Cycle (CPC), and propose a new recommendation algorithm based on CPC in this paper. We leverage CPC attributes to modify the collaborative filtering output rating matrix acquired by the ItemCF Algorithm, and take into consideration both user behaviors and commodity characteristics to make timely recommendations. We utilize a realistic dataset from Taobao to verify the performance of the proposed algorithm. Experimental results demonstrate good performance of CPC algorithm. Specifically, from the perspective of Root Mean Square Error (RMSE), the CPC Algorithm promotes the recommendation accuracy by 15%-20%, compared with the state-of-the-art ItemCF Algorithm.
The paper presents a solution of content interoperability among three digital library systems keeping Orthodox artefacts and knowledge: Encyclopaedia Slavica Sanctorum Calendar, Bulgarian Iconographical Digital Librar...
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The usage of mobile devices in everyday life poses new challenges for processing, adaptation and rendering of multimediacontent, which can’t be accomplished due to mobile device limitations (battery lifetime, storag...
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This paper presents an open and extendable platform that provides access to ICH resources, enables knowledge exchange between researchers and contributes to the transmission of rare know-how from their holders to the ...
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ISBN:
(纸本)9789897581076
This paper presents an open and extendable platform that provides access to ICH resources, enables knowledge exchange between researchers and contributes to the transmission of rare know-how from their holders to the next generations. The platform is a hybrid content-Learning Management system that permits the creation of new content of cultural heritage. It supports different user profiles for access, learning and analysis of the ICH, such as experts, learners, researchers as well as the large public. It is also supports the outcomes of sensorimotor learning functionalities of a game-based learning module. The platform integrates different modules based on multi-sensory technologies into an operating open-source content management system, which is enriched with a significant number of functionalities.
This article investigates an evolved elastic resource virtualization algorithm (E-ERVA) for Orthogonal Frequency-Division Multiple access (OFDMA) wireless communication systems. The objective of this algorithm is to m...
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The development of Vehicular Ad-hoc Networks (VANET) has witnessed the release of various multimedia services and made it important to develop architectures and routing protocols capable of (a) handling the multimedia...
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The importance of contextual information is widely acknowledged and has become a major topic of interest, investigation, and experimentation for quite some time, generating numerous papers and many scientific works. I...
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