Software as a service

About: Software as a service is a research topic. Over the lifetime, 8514 publications have been published within this topic receiving 136177 citations. The topic is also known as: Service as a Software Substitute & SaaSS.

In-page installer

Abstract: A method of notifying a user about the existence of relevant software and facilitating the installation of such software using a browser. A user's interactions with the browser are monitored to determine a context for a given browsing session, and it is determined whether software relevant to the context is available. If such software is available, it is recommended to the user, and if the user wishes to install the software, the installation can be performed via the browser. The software can be recommended to the user through a variety of means, including incorporating the recommendation in a static web page, incorporating the recommendation in a dynamic web page, and delivering the recommendation as part of advertising content. The recommendation may include a link to installation scripts or the like which facilitate the installation of the software by the browser.

Characterizing user behavior via intelligent identity analytics

Abstract: Methods, devices, and systems are provided to rapidly detect and prevent cyber-attacks that are enabled by either misuse of identity credentials or weaknesses within the identity credential lifecycle. An Identity Analytics and Intelligence Engine provides an automated process for the collection, exchange, analysis, correlation, and reporting of identity credential lifecycle data. The Identity Analytics and Intelligence Engine may be implemented as a Software as a Service (SaaS) capability. The Identity Analytics and Intelligence Engine applies Semantic Web concepts/technologies and graph databases to automatically capture the identity credential lifecycle data along with the associated data exchanges within one or more Trust Frameworks.

Efficient deployment of predictive analytics through open standards and cloud computing

Abstract: Over the past decade, we have seen tremendous interest in the application of data mining and statistical algorithms, first in research and science and, more recently, across various industries. This has translated into the development of a myriad of solutions by the data mining community that today impact scientific and business applications alike. However, even in this scenario, interoperability and open standards still lack broader adoption among data miners and modelers.In this article we highlight the use of the Predictive Model Markup Language (PMML) standard, which allows for models to be easily exchanged between analytic applications. With a focus on interoperability and PMML, we also discuss here emerging trends in cloud computing and Software as a Service, which have already started to play a critical role in promoting a more effective implementation and widespread application of predictive models.As an illustration of how the benefits of open standards and cloud computing can be combined, we describe a predictive analytics scoring engine platform that leverages these elements to deliver an efficient deployment process for statistical models.

Cloud computing (SaaS) adoption as a strategic technology: results of an empirical study

Abstract: The present study empirically analyzes the factors that determine the adoption of cloud computing (SaaS model) in firms where this strategy is considered strategic for executing their activity. A research model has been developed to evaluate the factors that influence the intention of using cloud computing that combines the variables found in the technology acceptance model (TAM) with other external variables such as top management support, training, communication, organization size, and technological complexity. Data compiled from 150 companies in Andalusia (Spain) are used to test the formulated hypotheses. The results of this study reflect what critical factors should be considered and how they are interrelated. They also show the organizational demands that must be considered by those companies wishing to implement a real management model adopted to the digital economy, especially those related to cloud computing.

Cloud Computing for Standard ERP Systems: Reference Framework and Research Agenda

Abstract: Cloud Computing is a topic that has gained momentum in the last years. Current studies show that an increasing number of companies is evaluating the promised advantages and considering making use of cloud services. In this paper we investigate the phenomenon of cloud computing and its importance for the operation of ERP systems. We argue that the phenomenon of cloud computing could lead to a decisive change in the way business software is deployed in companies. Our reference framework contains three levels (IaaS, PaaS, SaaS) and clarifies the meaning of public, private and hybrid clouds. The three levels of cloud computing and their impact on ERP systems operation are discussed. From the literature we identify areas for future research and propose a research agenda.