2,223 research outputs found
A Compressive Survey on New Technique Towards Successful Document Research Using Key Phrase Annotations Together with Querying Benefit
Generally it can be challenging to find out the particular pertinent data inside unstructured wording paperwork. This kind of information is still suffocated within unstructured wording and terminology. Annotations by means of Characteristic name-value frames tend to be more significant for retrieval of this sort of documents. This system proposes a novel, different, alternative approach for document retrieval which includes annotations identification. This system identifies the values of structured attributes by reading, analyzing and parsing the uploaded documents. This system proposes an approach for efficient document retrieval using effective methods. The main use of this system is that when users of author perform query based search, they could get minimum and distinct accurate results where it could be easy for retr ieval data from the database. By using these techniques two techniques, workload of system can reduce by large amount. And it also, given the fact the effic iency of searching annotation document will be faster because of using the query-based searching technique or content value searching
An intelligent information forwarder for healthcare big data systems with distributed wearable sensors
© 2016 IEEE. An increasing number of the elderly population wish to live an independent lifestyle, rather than rely on intrusive care programmes. A big data solution is presented using wearable sensors capable of carrying out continuous monitoring of the elderly, alerting the relevant caregivers when necessary and forwarding pertinent information to a big data system for analysis. A challenge for such a solution is the development of context-awareness through the multidimensional, dynamic and nonlinear sensor readings that have a weak correlation with observable human behaviours and health conditions. To address this challenge, a wearable sensor system with an intelligent data forwarder is discussed in this paper. The forwarder adopts a Hidden Markov Model for human behaviour recognition. Locality sensitive hashing is proposed as an efficient mechanism to learn sensor patterns. A prototype solution is implemented to monitor health conditions of dispersed users. It is shown that the intelligent forwarders can provide the remote sensors with context-awareness. They transmit only important information to the big data server for analytics when certain behaviours happen and avoid overwhelming communication and data storage. The system functions unobtrusively, whilst giving the users peace of mind in the knowledge that their safety is being monitored and analysed
Context caches in the clouds
In context-aware systems, the contextual information about human and computing situations has a strong temporal aspect i.e. it remains valid for a period of time. This temporal property can be exploited in caching mechanisms that aim to exploit such locality of reference. However, different types of contextual information have varying temporal validity durations and a varied spectrum of access frequencies as well. Such variation affects the suitability of a single caching strategy and an ideal caching mechanism should utilize dynamic strategies based on the type of context data, quality of service heuristics and access patterns and frequencies of context consuming applications. This paper presents an investigation into the utility of various context-caching strategies and proposes a novel bipartite caching mechanism in a Cloud-based context provisioning system. The results demonstrate the relative benefits of different caching strategies under varying context usage scenarios. The utility of the bipartite context caching mechanism is established both through simulation and deployment in a Cloud platform
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Ontology-based end-user visual query formulation: Why, what, who, how, and which?
Value creation in an organisation is a time-sensitive and data-intensive process, yet it is often delayed and bounded by the reliance on IT experts extracting data for domain experts. Hence, there is a need for providing people who are not professional developers with the flexibility to pose relatively complex and ad hoc queries in an easy and intuitive way. In this respect, visual methods for query formulation undertake the challenge of making querying independent of users’ technical skills and the knowledge of the underlying textual query language and the structure of data. An ontology is more promising than the logical schema of the underlying data for guiding users in formulating queries, since it provides a richer vocabulary closer to the users’ understanding. However, on the one hand, today the most of world’s enterprise data reside in relational databases rather than triple stores, and on the other, visual query formulation has become more compelling due to ever-increasing data size and complexity—known as Big Data. This article presents and argues for ontology-based visual query formulation for end-users; discusses its feasibility in terms of ontology-based data access, which virtualises legacy relational databases as RDF, and the dimensions of Big Data; presents key conceptual aspects and dimensions, challenges, and requirements; and reviews, categorises, and discusses notable approaches and systems
Web services approach for ambient assisted living in mobile environments
Web services appeared as a promising technology for Web environments independent of technologies, services, and applications. First, a performance comparison study between the two most used Web service architectures, SOAP and REST, is presented, considering messages exchange between clients and a server. Based on this study, the REST architecture was chosen to deploy the system because it gets better results compared to SOAP architecture. Currently, there are some issues related with this approach that should be studied. For instance, if massive quantities of data are sent to databases it can influence significantly the performance of the whole system. The Advanced Message Queuing Protocol (AMPQ) appears as a promising solution to address this problem. Then, in order to evaluate the performance of this approach, this work presents a performance evaluation and a comparison study of RESTful Web services and the AMQP Protocol considering exchanging messages between clients and a server. The study is based on the averaged exchanged messages for a certain period of time. It was observed and concluded that, for large quantities of messages exchange, the best results comes from the Advanced Message Queuing Protocol. Message Queuing Telemetry Transport (MQTT) was addressed in this work because it is a similar protocol to AMQP but it can be used by mobile devices with a processing capacity smallest unlike the AMQP that needs greater processing capacity. These studies are performed in the context of Ambient Assisted Living environments, since
the work was applied to this topic in order to experiment the effectiveness and evaluate the performance of these protocols in this scenario
CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines
Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective.
The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines.
From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research
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