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Abstract Announcement for International Journal of Intelligent Information
Technologies (IJIIT) 11(2)
The contents of the latest issue of:
International Journal of Intelligent Information Technologies (IJIIT)
Volume 11, Issue 2, April - June 2015
Published: Quarterly in Print and Electronically
ISSN: 1548-3657; EISSN: 1548-3665;
Published by IGI Global Publishing, Hershey, USA
www.igi-global.com/ijiit
<http://www.igi-global.com/journal/international-journal-intelligent-informa
tion-technologies/1089>
Editor(s)-in-Chief: Vijayan Sugumaran (Oakland University, USA)
Note: There are no submission or acceptance fees for manuscripts submitted
to the International Journal of Intelligent Information Technologies
(IJIIT). All manuscripts are accepted based on a double-blind peer review
editorial process.
ARTICLE 1
Building Data Warehouses Using Automation
Nayem Rahman (Intel Corporation, Hillsboro, OR, USA), Dale Rutz (Intel
Corporation, Santa Clara, CA, USA)
Software development is a complex endeavor. While significant benefits can
be achieved, the process is often laborious, time consuming and error prone
requiring multiple iterations in order to achieve the desired result. Issues
arise for numerous reasons - coding defects, unclear requirements, migration
challenges, lack of convention, and inadequate testing to name a few. When
convention and automation are introduced into the software development
lifecycle there are significantly fewer opportunities for failure.
Automation also allows for shorter development windows. Generally there are
fewer errors throughout testing, with the bulk of those being found in unit
and functional testing, far before the users get involved in systems
acceptance testing. A data warehouse consists of multiple subject areas in
which many tasks are common and should be automated for the sake of
efficiency and enforcing convention. This article discusses a set of tools
that can be used to automate writing data warehouse objects. The article
also provides statistics of time saved using automation.
To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/building-data-warehouses-using-automation/135903
<http://www.igi-global.com/article/building-data-warehouses-using-automation
/135903>
To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=135903
<http://www.igi-global.com/viewtitlesample.aspx?id=135903>
ARTICLE 2
An Ontology Based Framework for Intelligent Web Based e-Learning
B. Senthilnayaki (Department of Information Science and Technology, Anna
University, Chennai, India), K. Venkatalakshmi (Department of Electronic and
Communication Engineering, Anna University, Chennai, India), A. Kannan
(Department of Information Science and Technology, Anna University, Chennai,
India)
E-Learning is a fast, just-in-time, and non-linear learning process, which
is now widely applied in distributed and dynamic environments such as the
World Wide Web. Ontology plays an important role in capturing and
disseminating the real world knowledge for effective human computer
interactions. However, engineering of domain ontologies is very labor
intensive and time consuming. Some machine learning methods have been
explored for automatic or semi-automatic discovery of domain ontologies.
Nevertheless, both the accuracy and the computational efficiency of these
methods need to be improved. While constructing large scale ontology for
real-world applications such as e-learning, the ability to monitor the
progress of students' learning performance is a critical issue. In this
paper, a system is proposed for analyzing students' knowledge level obtained
using Kolb's classification based on the students level of understanding and
their learning style using cluster analysis. This system uses fuzzy logic
and clustering algorithms to arrange their documents according to the level
of their performance. Moreover, a new domain ontology discovery method is
proposed uses contextual information of the knowledge sources from the
e-Learning domain. This proposed system constructs ontology to provide an
effective assistance in e-Learning. The proposed ontology discovery method
has been empirically tested in an e-Learning environment for teaching the
subject Database Management Systems. The salient contributions of this paper
are the use of Jaccard Similarity measure and K-Means clustering algorithm
for clustering of learners and the use of ontology for concept understanding
and learning style identification. This helps in adaptive e-learning by
providing suitable suggestions for decision making and it uses decision
rules for providing intelligent e-Learning.
To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/an-ontology-based-framework-for-intelligent-web-b
ased-e-learning/135904
<http://www.igi-global.com/article/an-ontology-based-framework-for-intellige
nt-web-based-e-learning/135904>
To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=135904
<http://www.igi-global.com/viewtitlesample.aspx?id=135904>
ARTICLE 3
Streamlined Alarms for Intrusion Recognition System
V. Dhanakoti (Department of Computer Science and Engineering, SRM Valliammai
Engineering College, Chennai, India), R. Nedunchezhian (Department of
Computer Science and Engineering, KIT - Kalaignarkarunanidhi Institute of
Technology, Coimbatore, India)
A serious blow to the security of World Wide Web is the escalation in
synchronized system assaults like Hoax, Blended Threats, Worms, IP Scanning,
Trojan Horses, Denial of Service (DOS) and Sniffer assaults. It might not be
a wonder that by allowing all the contestants in Intrusion Recognition
Systems (IRS) sharing doubtful intellect with one another in order to shape
a worldwide view of the existing risks. Since existing Collective Intrusion
Recognition System (CIRS) algorithms are not capable of calculating complex
attacks in a timely manner, a rationalized multilayered red alarm connection
for collective intrusion recognition intelligent algorithm was built for
CIRS to tackle these confronts. A multilayered red alarm connection grouping
algorithm is used to mine the important intrusion prototypes from unrefined
intrusion alarms. Twin phase association algorithms are modified and used,
so that it groups alarm at every IRS, before exposing important alarm
prototypes to a world wide web.
To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/streamlined-alarms-for-intrusion-recognition-syst
em/135905
<http://www.igi-global.com/article/streamlined-alarms-for-intrusion-recognit
ion-system/135905>
To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=135905
<http://www.igi-global.com/viewtitlesample.aspx?id=135905>
ARTICLE 4
Complex Event Refinement by Statistical Augmentation Model
Ravi Pathak (Department of Electronics Engineering, Madras Institute of
Technology, Chennai, India), V. Vaidehi (Department of Electronics
Engineering, Madras Institute of Technology, Chennai, India)
The uncertainty of decision making in event hierarchies of CEP can be due to
unreliable data sources, lack of conformance that the event which is
reported has actually occurred. Also the Complex Event models which are used
to define complex events are inaccurate. When the uncertain event is used
for deriving complex event, it propagates its uncertainty to a higher level
of event hierarchy and causes uncertainty in reasoning. This paper proposes
an event refinement model based on statistical approach to augment the
events to minimize the error due to uncertainty for better decision making.
The proposed augmented CEP (a-CEP) is found to perform better in terms of
reduction in false alarm for continuous monitoring of patient in a remote
health care application. The proposed model is implemented on Drools Fusion
CEP Engine using Java and it is found that the proposed a-CEP gives better
results in terms of accuracy.
To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/complex-event-refinement-by-statistical-augmentat
ion-model/135906
<http://www.igi-global.com/article/complex-event-refinement-by-statistical-a
ugmentation-model/135906>
To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=135906
<http://www.igi-global.com/viewtitlesample.aspx?id=135906>
_____
For full copies of the above articles, check for this issue of the
International Journal of Intelligent Information Technologies (IJIIT) in
your institution's library. This journal is also included in the IGI Global
aggregated "InfoSci-Journals" database: www.igi-global.com/isj
<http://www.igi-global.com/e-resources/infosci-databases/infosci-journals/>
.
_____
CALL FOR PAPERS
Mission of IJIIT:
The advent of the World Wide Web has sparked renewed interest in the area of
intelligent information technologies. There is a growing interest in
developing intelligent technologies that enable users to accomplish complex
tasks in web-centric environments with relative ease, utilizing such
technologies as intelligent agents, distributed computing in heterogeneous
environments, and computer supported collaborative work. The mission of the
International Journal of Intelligent Information Technologies (IJIIT) is to
bring together researchers in related fields such as information systems,
distributed AI, intelligent agents, and collaborative work, to explore and
discuss various aspects of design and development of intelligent
technologies. This journal provides a forum for academics and practitioners
to explore research issues related to not only the design, implementation
and deployment of intelligent systems and technologies, but also economic
issues and organizational impact. Papers related to all aspects of
intelligent systems including theoretical work on agent and multi-agent
systems as well as case studies offering insights into agent-based problem
solving with empirical or simulation based evidence are welcome.
Indices of IJIIT:
* ACM Digital Library
* Australian Business Deans Council (ABDC)
* Bacon's Media Directory
* Burrelle's Media Directory
* Cabell's Directories
* Compendex (Elsevier Engineering Index)
* CSA Illumina
* DBLP
* DEST Register of Refereed Journals
* Gale Directory of Publications & Broadcast Media
* GetCited
* Google Scholar
* INSPEC
* JournalTOCs
* Library & Information Science Abstracts (LISA)
* MediaFinder
* Norwegian Social Science Data Services (NSD)
* SCOPUS
* The Index of Information Systems Journals
* The Standard Periodical Directory
* Thomson Reuters
* Ulrich's Periodicals Directory
* Web of Science
Coverage of IJIIT:
The International Journal of Intelligent Information Technologies (IJIIT)
encourages quality research dealing with (but not limited to) the following
topics:
* Agent-based auction, contracting, negotiation, and ecommerce
* Agent-based control and supply chain
* Agent-based simulation and application integration
* Cooperative and collaborative systems
* Distributed intelligent systems and technologies
* Human-agent interaction and experimental evaluation
* Implementation, deployment, diffusion, and organizational impact
* Integrating business intelligence from internal and external sources
* Intelligent agent and multi-agent systems in various domains
* Intelligent decision support systems
* Intelligent information retrieval and business intelligence
* Intelligent information systems development using design science
principles
* Intelligent Web mining and knowledge discovery systems
* Manufacturing information systems
* Models, architectures and behavior models for agent-oriented information
systems
* Multimedia information processing
* Privacy, security, and trust issues
* Reasoning, learning and adaptive systems
* Semantic Web, Web services, and ontologies
Interested authors should consult the journal's manuscript submission
guidelines
www.igi-global.com/calls-for-papers/international-journal-intelligent-inform
ation-technologies/1089
<http://www.igi-global.com/calls-for-papers/international-journal-intelligen
t-information-technologies/1089>
=========================================
Vijayan Sugumaran, Ph.D.
Professor of Management Information Systems
Chair, Department of Decision and Information Sciences
School of Business Administration
Oakland University
Rochester, MI 48309
Phone: 248-370-4649
Fax: 248-370-4275
Email: <mailto:sugumara@oakland.edu> sugumara@oakland.edu
=========================================
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