Research on Text Classification Based on Automatically Extracted Keywords

Automatic keywords extraction and classification tasks are important research directions in the domains of NLP (natural language processing), information retrieval, and text mining. As the fine granularity abstracted from text data, keywords are also the most important feature of text data, which has great practical and potential value in document classification, topic modeling, information retrieval, and other aspects. The compact representation of documents can be achieved through keywords, which contains massive significant information. Therefore, it may be quite advantageous to realize text classification with high-dimensional feature space. For this reason, this study designed a supervised keyword classification method based on TextRank keyword automatic extraction technology and optimize the model with the genetic algorithm to contribute to modeling the keywords of the topic for text classification

Challenges in the business model of low-cost airlines: Ryanair case study

In recent decades, low-cost airlines have proliferated in the European market offering cheap tickets and increasing popularity. This business model, characterised by cost leadership, has been studied on numerous occasions. The case of the Irish airline Ryanair has presented different challenges over the last few years in relation to its stakeholders, who are shaping the sustainability of the current era of air travel. This business model should be adapted to the current demands of the market, such as corporate social responsibility or care for the environment. The functioning of low-cost airlines regarding the use they make of ERP management systems is also analysed. They aim to balance their cost strategy with the development of internal resources and capabilities for the company's long-term strategy. A major current challenge for low-cost airlines is the implementation of ERP management systems to make strategies oriented to the customer, sustainability, and corporate social responsibility

Enterprise Architecture in Healthcare Networks: A Systematic Literature Review

Healthcare organizations collaborate, share knowledge, and need to be accountable to each other. Therefore, healthcare organizations manage a dynamic information system landscape. Enterprise Architecture (EA) is a management tool for aligning these landscapes to the primary information needs that healthcare organizations have. EA is of value in some environments, but it seems to be not well suited to the dynamics of healthcare. Despite the publication of several systematic literature reviews on EA in healthcare, a systematic literature study comparing EA applicability at various levels of cooperation (intra, inter, and network collaboration) is lacking. Therefore, we posed the following research question: To what extent is EA researched within healthcare organizations in the context of intra, inter and network collaboration? A systematic literature review was used to select 94 scientific publications for evaluation. These studies make explicit the EA elements at three levels of collaboration in the context of healthcare. The findings show that EA is most frequently studied in relation to a single healthcare organization with a wide range of topics. IT governance and EA implementation are the subjects of the majority of EA network level studies (17 out of 94 studies), followed by building/developing EA, EA acceptance, EA issues and root causes, and EA modeling. Although numerous EA frameworks are discussed in studies at the intra- and interorganizational levels, they are rarely referenced in studies at the network level. Additionally, the EA benefits, success factors, and challenges are comparable at high level, but details differ per level. These findings demonstrate that EA is researched within the healthcare sector context. The majority of knowledge on EA is focused on a single healthcare organization, but little is known about EA in a networked healthcare environment. To learn more about how EA might be used in a healthcare network setting, a research agenda has been set up based on the results

A systematic mapping study

Corte-Real, N., Ruivo, P., & Oliveira, T. (2014). The diffusion stages of business intelligence & analytics (BI&A):: A systematic mapping study. In Procedia Technology (Vol. 16, pp. 172-179). (Procedia Technology). DOI: 10.1016/j.protcy.2014.10.080Business intelligence & analytics (BI&A) has evolved to become a foundational cornerstone of enterprise decision support. Since the way BI&A is implemented and assimilated is quite different among organizations is important to approach BI&A literature by four selected diffusion stages (adoption, implementation, use and impacts of use). The diffusion stages assume a crucial importance to track the BI&A evolution in organizations and justify the investment made. The main focus of this paper is to evidence BI&A research on its several diffusion stages. It provides an updated bibliography of BI&A articles published in the IS journal and conferences during the period of 2000 and 2013. A total of 30 articles from 11 journals and 8 conferences are reviewed. This study contributes to the BI&A research in three ways. This is the first systematic mapping study focused on BI&A diffusion stages. It contributes to see how BI&A stages have been analyzed (theories used, data collection methods, analysis methods and publication source). Finally, it observes that little attention has been given to BI&A post-adoption stages and proposes future research line on this area.publishersversionpublishe

High Prediction Accuracy and Low Error for ERP User Satisfaction by Hybrid of ANFIS and KNN Classification

The incoming era is becoming more friendly and dependent on Information Technology. Enterprise Resource Planning (ERP) Systems are one of the most widely used latest examples of Information Systems (IS) technology. They provide a single window system to the organizations by integrating the whole functions of them. Today, all enterprises are rapidly adopted ERP systems. But, their adoption and implementation is not being without any problem. The implementation process of ERP is also a very challenging, time consuming and costly task. Therefore, instead of many efforts if the implementation process is failed. Then it will be a big failure for the organization. Hence, to overcome this failure and increase the success rate of ERP projects we need to develop a robust, reliable and accurate predictor. This will help us to redirect the projects far better in advance. The success of ERP systems depends on many factors. US is one of the important factor among them. Hence, we develop an efficient predictor of US using hybrid of ANFIS and KNN. We were used this method first time in literature related to prediction of US in ERP. The Hybrid method increases the prediction accuracy more comparatively than previous reported techniques ANN, ANFIS and KNN. The RMSE using Hybrid method is 0.167629 and for KNN, ANFIS and ANN is 0.5, 0.486185, and 0.590329 respectively

Ontology engineering for simulation component reuse

Commercial-off-the-shelf (COTS) simulation packages (CSPs) are widely used in industry, although they have yet to operate across organizational boundaries. Reuse across organizations is restricted by the same semantic issues that restrict the inter-organizational use of web services. The current representations of web components are predominantly syntactic in nature lacking the fundamental semantic underpinning required to support discovery on the emerging semantic web. Semantic models, in the form of ontology, utilized by web service discovery and deployment architectures provide one approach to support simulation model reuse. Semantic interoperation is achieved through the use of simulation component ontologies to identify required components at varying levels of granularity (including both abstract and specialized components). Selected simulation components are loaded into a CSP, modified according to the requirements of the new model and executed. The paper presents the development of an ontology, connector software and web service discovery architecture. The ontology is extracted from simulation scenarios involving airport, restaurant and kitchen service suppliers. The ontology engineering framework and discovery architecture provide a novel approach to inter-organizational simulation, adopting a less intrusive interface between participants. Although specific to CSPs the work has wider implications for the simulation community

A Conceptual Model to Measure ERP User-Value

The critical factors in the onward and upward phase that maximize the value o the enterprise resource planning (ERP) system from the user’s point of view remain unidentified. A recent study of a public sector organization in the state of Colorado showed that the users’ perspectives regarding the benefits of an ERP system are unrecognized, as well as how the users of the ERP system view the ERP benefits post-implementation. The purpose of this study is to determine the factors that maximize the value of the implemented ERP system in the onward and upward phase postimplementation from the user’s point of view (ERP user value), and how these factors affect the ERP user productivity, effectiveness, and internal efficiency which are major issues for management. A proposed conceptual structural model, based on the Technology-Organization-Environment (TOE) framework, is presented. It is posited that the conceptual model can be used to predict the post-implementation factors from the ERP user’s point of view and measure their impact on the overall ERP benefits for the organization. The research question, hypotheses, and current state of research are presented and discussed

Evaluating demand driven MRP: a case based simulated study

This study evaluates the assumption underpinning Material Requirements Planning (MRP), buffer management and DDMRP before analysing the case company and evaluating the potential benefits, utilizing simulated data from the existing ERP system. The purpose of this research is to evaluate DDMRP in the context of improving the performance of a printing ink manufacturing company. The main issues the company is facing using a traditional MRP system include poor due-date performance, stock levels not corresponding to the actual market needs and overall system instability leading to inefficiencies. The findings indicate the potential of DDMRP to improve system stability and product availability

I SEE NO FUN IN ENTERPRISE SYSTEMS: AN EXPLORATORY STUDY ON THE FIRST IMPRESSION USABILITY AND USER EXPERIENCE

Technology acceptance is crucial, if newly implemented enterprise systems (ES) in a company are to succeed. This is often addressed by end-user training during the implementation project. Perceived enjoyment and positive user experience (UX) have gained significant importance as technology acceptance factors. Yet, research on the design of such trainings is scarce, and literature with focus on perceived UX of ES even more so. This is in contrast to findings from other contexts which show that perceived UX may heavily impact user attitudes and learning motivation. As a first endavour in this direction, this paper presents an exploratory pre-study on first impressions of main operating ES with regard to expected usability and UX. Results show that ES are rated low, especially when compared to a universal UX benchmark. We discuss how more positive first impressions may positively impact motivation to learn the system, which will be investigated in a follow-up study