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Articles 181 - 186 of 186
Full-Text Articles in Physical Sciences and Mathematics
Business Intelligence And Analytics: Research Directions, Ee Peng Lim, Hsinchun Chen, Guoqing Chen
Business Intelligence And Analytics: Research Directions, Ee Peng Lim, Hsinchun Chen, Guoqing Chen
Research Collection School Of Computing and Information Systems
Business intelligence and analytics (BIA) is about the development of technologies, systems, practices, and applications to analyze critical business data so as to gain new insights about business and markets. The new insights can be used for improving products and services, achieving better operational efficiency, and fostering customer relationships. In this article, we will categorize BIA research activities into three broad research directions: (a) big data analytics, (b) text analytics, and (c) network analytics. The article aims to review the state-of-the-art techniques and models and to summarize their use in BIA applications. For each research direction, we will also determine …
Reducing Barriers To Wesleyan Thought: Olivet Nazarene University And The Wesleyan Holiness Library, Craighton T. Hippenhammer
Reducing Barriers To Wesleyan Thought: Olivet Nazarene University And The Wesleyan Holiness Library, Craighton T. Hippenhammer
Faculty Scholarship – Library Science
Olivet Nazarene University’s recent move to start publishing academic scholarship in a digital institutional repository, Digital Commons, is a smart move to not only highlight and preserve Olivet scholarship, but also to support the worldwide open access movement that is widely expected to rescue the current failing model of academic publishing. The traditional methods for publishing faculty scholarship have been inadequate for some time, and the financial structures that sustain them are collapsing due to skyrocketing journal prices. What faculty members want most for their research is that it be as accessible, available and useful to other researchers and to …
Knowledge As A Service Framework For Disaster Data Management, Katarina Grolinger, Emna Mezghani, Miriam Am Capretz, Ernesto Exposito
Knowledge As A Service Framework For Disaster Data Management, Katarina Grolinger, Emna Mezghani, Miriam Am Capretz, Ernesto Exposito
Electrical and Computer Engineering Publications
Each year, a number of natural disasters strike across the globe, killing hundreds and causing billions of dollars in property and infrastructure damage. Minimizing the impact of disasters is imperative in today’s society. As the capabilities of software and hardware evolve, so does the role of information and communication technology in disaster mitigation, preparation, response, and recovery. A large quantity of disaster-related data is available, including response plans, records of previous incidents, simulation data, social media data, and Web sites. However, current data management solutions offer few or no integration capabilities. Moreover, recent advances in cloud computing, big data, and …
Engagingness And Responsiveness Behavior Models On The Enron Email Network And Its Application To Email Reply Order Prediction, Byung-Won On, Ee Peng Lim, Jing Jiang, Loo Nin Teow
Engagingness And Responsiveness Behavior Models On The Enron Email Network And Its Application To Email Reply Order Prediction, Byung-Won On, Ee Peng Lim, Jing Jiang, Loo Nin Teow
Research Collection School Of Computing and Information Systems
In email networks, user behaviors affect the way emails are sent and replied. While knowing these user behaviors can help to create more intelligent email services, there has not been much research into mining these behaviors. In this paper, we investigate user engagingness and responsiveness as two interaction behaviors that give us useful insights into how users email one another. Engaging users are those who can effectively solicit responses from other users. Responsive users are those who are willing to respond to other users. By modeling such behaviors, we are able to mine them and to identify engaging or responsive …
The Problem Of Semantics In The Metadata Mess, Veronika Margaret Megler, David Maier
The Problem Of Semantics In The Metadata Mess, Veronika Margaret Megler, David Maier
Computer Science Faculty Publications and Presentations
This presentation addresses problems related to the volume of available scientific data, and its accessibility or inaccessibility to researchers who seek it. Topics addressed include metadata and reducing semantic diversity, especially as they refer to geospatial and other architectures
Taming The Metadata Mess, Veronika Margaret Megler
Taming The Metadata Mess, Veronika Margaret Megler
Computer Science Faculty Publications and Presentations
The rapid growth of scientific data shows no sign of abating. This growth has led to a new problem: with so much scientific data at hand, stored in thousands of datasets, how can scientists find the datasets most relevant to their research interests? We have addressed this problem by adapting Information Retrieval techniques, developed for searching text documents, into the world of (primarily numeric) scientific data. We propose an approach that uses a blend of automated and “semi-curated” methods to extract metadata from large archives of scientific data, then evaluates ranked searches over this metadata. We describe a challenge identified …