News impact analysis has become a common task conducted by finance researchers, which involves reading and selecting news articles based on themes sentiments, pairing events relevant stocks, measuring the of selected stock prices. To facilitate more efficient selection, topic modeling can be applied to generate topics out large number documents. However, there is very limited existing literature comparing models in context finance-related analysis. In this paper, we compare three...

With the advancement in intelligent devices, social media, and Internet of Things, staggering amounts new data are being generated pace is continuously accelerating. Real-time analytics (RTA) has emerged as a distinct branch big focusing on velocity aspect data, which prepared, processed analyzed it arrives, with aim generating insights creating business value near real-time. The objective this paper to provide an overview key concepts architectural approaches for designing RTA solutions,...

There is a growing emphasis to find alternative non-traditional ways manage patients ease the burden on health care services largely fuelled by demand from sections of population that ageing. In-home remote patient monitoring applications harnessing technological advancements in area Internet things (IoT), semantic web, data analytics, and cloud computing have emerged as viable alternatives. However, such generate large amounts real-time terms volume, velocity, variety thus making it big...

Credit risk prediction is an effective way of evaluating whether a potential borrower will repay loan, particularly in peer-to-peer lending where class imbalance problems are prevalent.However, few credit models for social consider imbalanced data and, further, the best resampling technique to use with still controversial.In attempt address these problems, this paper presents empirical comparison various combinations classifiers and techniques within novel assessment methodology that...

Architecting distributed software applications is a complex design activity. It involves making decisions about number of inter-dependent choices that relate to range concerns. Each decision requires selecting among alternatives; each which impacts differently on various quality attributes. Additionally, there are usually stakeholders participating in the decision-making process with different, often conflicting, goals, and project constraints, such as cost schedule. To facilitate...

The lack of a common framework often complicates the process provider selection and marginal resource allocation decision. nonlinear relationships among criteria greatly impact decision-making process. paper address critical issue by proposing centralised Quality Experience (QoE) Service (QoS)- CQoES framework. considers customised priority criteria, determine relative importance each criterion intelligently assign weights to criterion. assists service in decision making for resources. To...

The paradigm of service-oriented computing (SOC) has emerged as an approach to provide flexibility and agility, not just in systems development but also business process management. This modular defining flows technology independent services gained unanimous popularity among end-users vendors alike. Although there is a significant amount ongoing research on the potential service oriented architectures (SOAs), paucity literature factors affecting adoption practice. paper reviews current state...

Abstract A Case‐Based Reasoning (CBR) system for medical diagnosis mimics the way doctors make a diagnosis. Given new case, its accuracy in practice depends on successful retrieval of similar cases. CBR systems have had some success dealing with simple diseases because robustness their case base. However, diagnostic suffers when complex particularly those that involve multiple domains medicine. An example such condition is Premenstrual syndrome (PMS) as it falls under both gynaecology and...

Cloud monitoring involves dynamically tracking the Quality of Service (QoS) parameters related to virtualized services (e.g., CPU, storage, network, appliances, etc.), physical resources they share, and applications running on them or data hosted them. Monitoring techniques can help a cloud provider application developer in regards to: (i) keeping operating at peak efficiency; (ii) detecting variations service performance; (iii) accounting SLA violations certain QoS parameters; (iv) leave...

Cloud computing provides on-demand access to affordable hardware (multi-core CPUs, GPUs, disks, and networking equipment) software (databases, application servers data processing frameworks) platforms with features such as elasticity, pay-per-use, low upfront investment time market. This has led the proliferation of business critical applications that leverage various cloud platforms. Such hosted on single or multiple provider have diverse characteristics requiring extensive monitoring...

<em>Background</em>: Early detection of disease outbreaks, using appropriate surveillance methods, is a basic principle for effective control epidemics. Indicator-based such as comprehensive surveillance, sentinel and syndromic have been routinely utilized early epidemic to minimize mortality morbidity related emerging infectious threats. In addition, event-based uses unstructured data sources detect monitor outbreaks media reports, social websites. The use mobile phone technology growing in...

Abstract Quality of Service (QoS) is the key parameter to measure overall performance service-oriented applications. In a myriad web services, QoS data has multiple highly sparse and enormous dimensions. It great challenge reduce computational complexity by reducing dimensions without losing information predict for future intervals. This paper uses an Induced Ordered Weighted Average (IOWA) layer in prediction lessen size dataset analyse accuracy cloud data. The approach enables stakeholders...

The development of artificial intelligence (AI) has revolutionised the medical system, empowering healthcare professionals to analyse complex nonlinear big data and identify hidden patterns, facilitating well-informed decisions. Over last decade, there been a notable trend research in AI, machine learning (ML), their associated algorithms health systems. These approaches have transformed enhancing efficiency, accuracy, personalised treatment, decision-making. Recognising importance growing...

The composition of Web services has gained a considerable momentum as paradigm for enabling Business-to-Business (B2B) Collaborations. Numerous technologies supporting this new are rapidly emerging, thereby creating need methodologies that bring these together. identification and documentation relevant patterns, both at the analysis design levels, is an important step in direction.

Cloud computing provides on-demand access to affordable hardware (e.g., multi-core CPUs, GPUs, disks, and networking equipment) software databases, application servers, data processing frameworks, etc.) platforms. Application services hosted on single/multiple cloud provider platforms have diverse characteristics that require extensive monitoring mechanisms aid in controlling run-time quality of service latency number requests being served per second, etc.). To provide essential real-time...

establish explainability and responsibility in intelligent black box systems-machine learning-based or not.