[AISWorld] Contents of the latest issue of IJIIT 7(4)

Tue Nov 1 04:43:00 EDT 2011

The contents of the latest issue of:

International Journal of Intelligent Information Technologies (IJIIT)

Official Publication of the Information Resources Management Association

Volume 7, Issue 4, October-December 2011

Published: Quarterly in Print and Electronically

ISSN: 1548-3657 EISSN: 1548-3665

Published by IGI Publishing, Hershey-New York, USA

www.igi-global.com/ijiit

Editor-in-Chief: Vijayan Sugumaran, Oakland University, USA

PAPER ONE

Towards a Possibilistic Information Retrieval System Using Semantic Query
Expansion

Bilel Elayeb, ENSI Manouba University, Tunisia

Ibrahim Bounhas, Faculty of Sciences of Tunis, Tunisia

Oussama Ben Khiroun, ENSI Manouba University, Tunisia

Fabrice Evrard, Informatics Research Institute of Toulouse (IRIT), France

Narjès Bellamine-BenSaoud, ENSI Manouba University, Tunisia

This paper presents a new possibilistic information retrieval system using
semantic query expansion. The work is involved in query expansion strategies
based on external linguistic resources. In this case, the authors exploited
the French dictionary “Le Grand Robert”. First, they model the dictionary as
a graph and compute similarities between query terms by exploiting the
circuits in the graph. Second, the possibility theory is used by taking
advantage of a double relevance measure (possibility and necessity) between
the articles of the dictionary and query terms. Third, these two approaches
are combined by using two different aggregation methods. The authors also
benefit from an existing approach for reweighting query terms in the
possibilistic matching model to improve the expansion process. In order to
assess and compare the approaches, the authors performed experiments on the
standard ‘LeMonde94’ test collection.

To obtain a copy of the entire article, click on the link below.

http://www.igi-global.com/article/towards-possibilistic-information-retrieva
l-system/60655

To read a PDF sample of this article, click on the link below.

http://www.igi-global.com/viewtitlesample.aspx?id=60655

PAPER TWO

Effective Fuzzy Ontology Based Distributed Document Using Non-Dominated
Ranked Genetic Algorithm

M. Thangamani, Kongu Engineering College, India

P. Thangaraj, Bannari Amman Institute of Technology, India

The increase in the number of documents has aggravated the difficulty of
classifying those documents according to specific needs. Clustering analysis
in a distributed environment is a thrust area in artificial intelligence and
data mining. Its fundamental task is to utilize characters to compute the
degree of related corresponding relationship between objects and to
accomplish automatic classification without earlier knowledge. Document
clustering utilizes clustering technique to gather the documents of high
resemblance collectively by computing the documents resemblance. Recent
studies have shown that ontologies are useful in improving the performance
of document clustering. Ontology is concerned with the conceptualization of
a domain into an individual identifiable format and machine-readable format
containing entities, attributes, relationships, and axioms. By analyzing
types of techniques for document clustering, a better clustering technique
depending on Genetic Algorithm (GA) is determined. Non-Dominated Ranked
Genetic Algorithm (NRGA) is used in this paper for clustering, which has the
capability of providing a better classification result. The experiment is
conducted in 20 newsgroups data set for evaluating the proposed technique.
The result shows that the proposed approach is very effective in clustering
the documents in the distributed environment.

To obtain a copy of the entire article, click on the link below.

http://www.igi-global.com/article/effective-fuzzy-ontology-based-distributed
/60656

To read a PDF sample of this article, click on the link below.

http://www.igi-global.com/viewtitlesample.aspx?id=60656

PAPER THREE

A Dynamically Optimized Fluctuation Smoothing Rule for Scheduling Jobs in a
Wafer Fabrication Factory

Toly Chen, Feng Chia University, Taiwan

This paper presents a dynamically optimized fluctuation smoothing rule to
improve the performance of scheduling jobs in a wafer fabrication factory.
The rule has been modified from the four-factor bi-criteria nonlinear
fluctuation smoothing (4f-biNFS) rule, by dynamically adjusting factors.
Some properties of the dynamically optimized fluctuation smoothing rule were
also discussed theoretically. In addition, production simulation was also
applied to generate some test data for evaluating the effectiveness of the
proposed methodology. According to the experimental results, the proposed
methodology was better than some existing approaches to reduce the average
cycle time and cycle time standard deviation. The results also showed that
it was possible to improve the performance of one without sacrificing the
other performance metrics.

To obtain a copy of the entire article, click on the link below.

http://www.igi-global.com/article/dynamically-optimized-fluctuation-smoothin
g-rule/60657

To read a PDF sample of this article, click on the link below.

http://www.igi-global.com/viewtitlesample.aspx?id=60657

PAPER FOUR

A Heuristic Method for Learning Path Sequencing for Intelligent Tutoring
System (ITS) in E-Learning

Sami A. M. Al-Radaei, IT BHU, India

R. B. Mishra, IT BHU, India

Course sequencing is one of the vital aspects in an Intelligent Tutoring
System (ITS) for e-learning to generate the dynamic and individual learning
path for each learner. Many researchers used different methods like Genetic
Algorithm, Artificial Neural Network, and TF-IDF (Term Frequency- Inverse
Document Frequency) in E-leaning systems to find the adaptive course
sequencing by obtaining the relation between the courseware. In this paper,
heuristic semantic values are assigned to the keywords in the courseware
based on the importance of the keyword. These values are used to find the
relationship between courseware based on the different semantic values in
them. The dynamic learning path sequencing is then generated. A comparison
is made in two other important methods of course sequencing using TF-IDF and
Vector Space Model (VSM) respectively, the method produces more or less same
sequencing path in comparison to the two other methods. This method has been
implemented using Eclipse IDE for java programming, MySQL as database, and
Tomcat as web server.

To obtain a copy of the entire article, click on the link below.

http://www.igi-global.com/article/heuristic-method-learning-path-sequencing/
60658

To read a PDF sample of this article, click on the link below.

http://www.igi-global.com/viewtitlesample.aspx?id=60658

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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:
http://www.igi-global.com/EResources/InfoSciJournals.aspx.
*****************************************************

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.

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/ijiit.

All inquiries and submissions should be sent to:

Editor-in-Chief: Dr. Vijayan Sugumaran at sugumara at oakland.edu
<mailto:%20sugumara at oakland.edu> 

=======================================
Vijayan Sugumaran, Ph.D.

Professor of Management Information Systems

Department of Decision and Information Sciences

School of Business Administration

Oakland University

Rochester, MI 48309

Phone: +1 248 370 2831

Fax: +1 248 370 4275

Email: sugumara at oakland.edu

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