Computational Modelling for Bankruptcy Prediction: Semantic data Analysis Integrating Graph Database and Financial Ontology

In this paper, we propose a novel intelligent methodology to construct a Bankruptcy Prediction Computation Model, which is aimed to execute a company's financial status analysis accurately. Based on the semantic data analysis and management, our methodology considers Semantic Database System as the core of the system. It comprises three layers: an Ontology of Bankruptcy Prediction, Semantic Search Engine, and a Semantic Analysis Graph Database system. The Ontological layer defines the basic concepts of the financial risk management as well as the objects that serve as sources of knowledge for predicting a company's bankruptcy. The Graph Database layer utilises a powerful semantic data technology, which serves as a semantic data repository for our model. The article provides a detailed description of the construction of the Ontology and its informal conceptual representation. We also present a working prototype of the Graph Database system, constructed using the Neo4j application, and show the connection between well-known financial ratios. We argue that this methodology which utilises state of the art semantic data management mechanisms enables data processing and relevant computations in a more efficient way than approaches using the traditional relational database. These give us solid grounds to build a system that is capable of tackling the data of any complexity level

City Data Fusion: Sensor Data Fusion in the Internet of Things

Internet of Things (IoT) has gained substantial attention recently and play a significant role in smart city application deployments. A number of such smart city applications depend on sensor fusion capabilities in the cloud from diverse data sources. We introduce the concept of IoT and present in detail ten different parameters that govern our sensor data fusion evaluation framework. We then evaluate the current state-of-the art in sensor data fusion against our sensor data fusion framework. Our main goal is to examine and survey different sensor data fusion research efforts based on our evaluation framework. The major open research issues related to sensor data fusion are also presented.Comment: Accepted to be published in International Journal of Distributed Systems and Technologies (IJDST), 201

Critical business intelligence practices to create meta-knowledge

In order to successfully implement strategies and respond to business variations in real-time, business intelligence (BI) systems have been deployed by organisations that assist in focused analytical assessments for execution of critical decisions. Although businesses have realised the significance of BI, few studies have explored their analytical decision-enabling capabilities linked to organisational practices. This study investigates the BI practices critical in creating meta-knowledge successfully for strategy-focused analytical decision-making. First, key BI suppliers are interviewed to develop an understanding of their BI capabilities and current deployment practices. Subsequently, two large BI implementation case studies are conducted to examine their practices in data transformation process. Findings reveal that BI practices are highly context-specific in mapping decisions with data assets. Complimentary static and dynamic evaluations provide holistic intelligence in predicting and prescribing a more complete picture of the enterprise. These practices vary across firms in their effectiveness reflecting numerous challenges and improvement opportunities.Publishe

Social Media Roadmaps. Exploring the futures triggered by social media.

Social media refers to a combination of three elements: content, user communities and Web 2.0 technologies. This foresight report presents six roadmaps of the anticipated developments of social media in three themes: society, companies, and local environment. One of the roadmaps, the meta-roadmap, is the synthesis of them all. The society sub-roadmap explores societal participation through communities. There are three sub-roadmaps relating to companies: interacting with companies through communities, social media in work environment, and social media enhanced shopping. The local environment sub-roadmap looks at social media in local environment. The roadmapping process was carried out through two workshops at VTT. The results of the report are crystallized into five main development lines triggered by social media. First development line is transparency referring to its increasing role in society, both with positive and negative consequences. The second development line is the rise of ubiquitous participatory communication model. This refers to an increase of two-directional and community-based interactivity in every field, where it has some added value. The third development is reflexive empowerment. This refers to the role of social media as an enabler of grass-root community collaboration. The fourth development line is the duality personalization/fragmentation vs. mass effects/integration. Personalization /fragmentation emphasises the tailoring of the web services and content. This development is counterweighted by mass effects/integration, like the formation of super-nodes in the web. The fifth development line is the new relations of physical and virtual worlds. This development line highlights the idea that practices induced by social media, e.g. communication, participation, co-creation, feedback and rating, will get more common in daily environment, and that virtual and physical worlds will be more and more interlinked.</p

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes