27,835 research outputs found
Classification Methodology for Architectures in Information Systems: A Statistical Converging Technique
Architectures are critical to the Information System (IS) domain because they represent funda- mental structures and interactions of systems. Since analysing architecture similarities is chal- lenging and time-consuming even in one domain, IS architecture classifications are paramount to understanding architectural complexity. However, classification approaches used in existing research commonly rely on manual interventions, and thus architectural classification reliability is hampered. We propose a novel methodology based on component modelling and applica- tion of a statistical converging technique, which ensures reliable IS architectural classification and minimises subjective interventions. We demonstrate the methodology by classifying data warehouse architectures
On-line transformer condition monitoring through diagnostics and anomaly detection
This paper describes the end-to-end components of an on-line system for diagnostics and anomaly detection. The system provides condition monitoring capabilities for two in- service transmission transformers in the UK. These transformers are nearing the end of their design life, and it is hoped that intensive monitoring will enable them to stay in service for longer. The paper discusses the requirements on a system for interpreting data from the sensors installed on site, as well as describing the operation of specific diagnostic and anomaly detection techniques employed. The system is deployed on a substation computer, collecting and interpreting site data on-line
Using Ontologies for the Design of Data Warehouses
Obtaining an implementation of a data warehouse is a complex task that forces
designers to acquire wide knowledge of the domain, thus requiring a high level
of expertise and becoming it a prone-to-fail task. Based on our experience, we
have detected a set of situations we have faced up with in real-world projects
in which we believe that the use of ontologies will improve several aspects of
the design of data warehouses. The aim of this article is to describe several
shortcomings of current data warehouse design approaches and discuss the
benefit of using ontologies to overcome them. This work is a starting point for
discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure
Adoption of standard ERP solution in health care sector: is SAP ERP all-in-one capable to meet specific requirements?
Objective of this experience report is to address specific issues regarding standard SAP ERP implementation in a medical institution. Target Company is a state owned health care institution from Bosnia and Herzegovina. Report will treat selected issues which could trouble standard SAP ERP implementation trough predefined ERP implementation methodology for SAP ERP. This report presents observations/ remarks based on experience of authors in particular SAP ERP implementation project in health care institution. Authorâs goal is to provide useful insight into âreal lifeâ standard ERP implementation and problems that arise. Also, it should provide useful information for all stakeholders involved in the process of ERP implementation in public health care sector
Integrating E-Commerce and Data Mining: Architecture and Challenges
We show that the e-commerce domain can provide all the right ingredients for
successful data mining and claim that it is a killer domain for data mining. We
describe an integrated architecture, based on our expe-rience at Blue Martini
Software, for supporting this integration. The architecture can dramatically
reduce the pre-processing, cleaning, and data understanding effort often
documented to take 80% of the time in knowledge discovery projects. We
emphasize the need for data collection at the application server layer (not the
web server) in order to support logging of data and metadata that is essential
to the discovery process. We describe the data transformation bridges required
from the transaction processing systems and customer event streams (e.g.,
clickstreams) to the data warehouse. We detail the mining workbench, which
needs to provide multiple views of the data through reporting, data mining
algorithms, visualization, and OLAP. We con-clude with a set of challenges.Comment: KDD workshop: WebKDD 200
Business intelligence systems and user's parameters: an application to a documents' database
This article presents earlier results of our research works in the area of
modeling Business Intelligence Systems. The basic idea of this research area is
presented first. We then show the necessity of including certain users'
parameters in Information systems that are used in Business Intelligence
systems in order to integrate a better response from such systems. We
identified two main types of attributes that can be missing from a base and we
showed why they needed to be included. A user model that is based on a
cognitive user evolution is presented. This model when used together with a
good definition of the information needs of the user (decision maker) will
accelerate his decision making process
- âŠ