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This paper addresses the semantic gap between the domain knowledge and software application engineering by proposing a framework for mapping and integrating multiple heterogeneous data sources with application business logic by means of data semantic enrichment, aggregation, filtering and processing. Based on the main drawbacks identified in the current knowledge enhanced software application architectures,...
The success of big data projects depends heavily on the ability to decide which technological expertise and architectures are required in such a context. However, there is confusion in scientific discourse regarding the systemization of big data technologies which exacerbates this problem. Therefore, in this paper, a structured literature review is conducted to assess the current state of the art...
Software architecture patterns present solutions for software architecture problems and help to document architectural design decisions. Complexity and variability of patterns, and the required expertise for selecting an appropriate pattern, would cause some difficulties in utilizing architectural patterns. Using an ontology for registering architectural patterns is an efficient step in solving those...
PubMed mining is currently at the epicenter of intense interdisciplinary research. Text mining methodologies provide a way to retrieve and analyze emotionally charged words, punctuation, and syntax. Moreover, they can analyze scientific literature and process document collections. Moving beyond traditional document-term matrix representation, an architecture for content based retrieval from PubMed...
In this paper, we present a big data software architecture that uses an ontology, based on the Experience API specification, to semantically represent the data streams generated by the learners when they undertake the learning activities of a course, e.g., in a course. These data are stored in a RDF database to provide a high performance access so learning analytics services can process the large...
Large systems engineering projects involve the cooperation of various stakeholders from different engineering disciplines. Individual stakeholders apply various tools and related data storage approaches that (a) might hinder seamless interoperability and (b) include limited capability to support data versioning. Project-level concepts enable the mapping of engineering data coming from different disciplines...
The cloud computing paradigm with its pay-as-you-use business model is envisioned to provide immense benefits and promising returns. Hybrid cloud computing deployment model offers a viable solution of in-house private cloud with limited or unavailable resources on hand to meet the application requirements or at runtime. However, due to the large-scale, widely distributed and complexity of the underlying...
This paper presents ontology based cloud service discovery mechanism that aims to provide cloud users to find desired cloud services over the internet. The main objective is to construct cloud ontology on the basis of services and attributes, that helps to rearrange the query and to discover the cloud services for user's requirement. Cloud ontology brings various CSPS services under same name convention...
This article presents an architecture for storing ontologically annotated medical images in a GRID. We will be able to extract information from the annotations, which are represented ontologically using RDF. We implement GRID services associated with the development of methodologies for ontological annotations of data contained in a Data Grid (specifically on the Storage Elements). We also provide...
E-learning systems provide processes of delivering the learning contents to learners who have different backgrounds, interests, and locations away from a classroom in order to maximize the effectiveness of learning. Usually, the classical e-learning system is based on client/server architecture thus they lack of the scalability, flexibility and interoperability. It makes the learning resources cannot...
This paper presents a new system to automatically recognize fishes based their digital pictures. The system follows the requirement of SOA (Service Oriented Architecture) in order to provide a self-service platform for public. The system provides services like the training mode, the recognition mode, and the consulting mode. These services can be deployed onto various application servers at different...
This paper presents a new network management system with ontology-supported multi-agent techniques. This technique derived from the ontology combining with related free software - Ethereal and Cacti which stored the operating information of network management perfectly into the backend database; furthermore, from the view of the fundamental functions of information agents, the system could sketch...
Nowadays, with the rapid development of Web services technologies as a solution to achieve SOA, the number of Web services on the web that offer similar functions is increasing. Therefore, not only the discovery and selection of the best Web services based on functional property requirements and preferences of users is not sufficient, but also owning to improve and achieve more accurate results, the...
Requirements engineering is an important research area in software engineering. Recent years, with the exponentially growing amount of software developed, it is necessary to elicit appropriate software requirements at an early phase of software development. We provide the complementary classification techniques that combine folksonomy, keyword and facet-based retrieval methods to retrieve software...
The objective of knowledge integration is to promote knowledge collection, sharing and retrieval in distributed and heterogeneous environment. Our workgroup develops a domain-oriented model for knowledge integration in distributed heterogeneous environment such as semantic grid, which promises better access to relevant knowledge by producing a global domain ontology that is used for establishing semantic...
There are many new challenges in building Scientific Data Management System (SDMS), and the most initial and important one of them is designing a reasonably and effectively data architecture. The data architecture should focus on massive metadata, complex data flow, multi-classification data, various data productions and uniform query. Based on the applied projects, we present the classificatory criterions,...
The demand for quickly delivering robust enterprise applications has increasingly become a business imperative today. Semantic web technologies have received much interest due to their prospect in facilitating seamless legacy system integration in support of new functionality development. In this article, we present a team collaboration oriented development framework (SSC-I) for designing and developing...
Urban Computing is an extension of Ubiquitous Computing. It shares common requirements with its predecessor, like context awareness, user centricity, composability and dynamicity. However, a challenging issue of urban computing is to provide available services to diverse, spontaneous social groups. A major requirement for this challenge is spontaneity, which is about supporting social groups by coordinating...
To enable effective access to databases on the Web, it is critical to integrate the large scale deep Web sources. Therefore, schema matching is a basic problem in many database application domains, such as data integration, E-business, data warehousing, and semantic query processing. In current implementations, schema matching has some significant limitations until now. And also, there are some problems...
This paper presents a process to build Websites based on personalization issues, aiming the improvement of services for the users. In this process not only the history of navigation and preferences detected or expressed by the user are considered for personalization but also the types of devices and networks used for communication, and even the content presented. The information related to the user...
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