-------- Forwarded Message --------
The contents of the latest issue of:
International Journal of Intelligent Information Technologies
(IJIIT)
Volume 15, Issue 2, April - June 2019
Indexed by: Compendex (Elsevier Engineering Index), INSPEC,
SCOPUS, Web of
Science Emerging Sources Citation Index (ESCI)
For a complete list of indexing and abstracting services that
include this
journal, please reference the bottom of this announcement.
Published: Quarterly in Print and Electronically
ISSN: 1548-3657; EISSN: 1548-3665; Published by IGI Global
Publishing, Hershey, USA
www.igi-global.com/ijiit
<
https://www.igi-global.com/journal/international-journal-intelligent-inform
ation-technologies/1089>
Editor-in-Chief: Vijayan Sugumaran (Oakland University, USA)
Note: The International Journal of Intelligent Information
Technologies
(IJIIT) has an Open Access option, which allows individuals and
institutions
unrestricted access to its published content. Unlike traditional
subscription-based publishing models, open access content is
available
without having to purchase or subscribe to the journal in which
the content
is published. All IGI Global manuscripts are accepted based on a
double-blind peer review editorial process.
ARTICLE 1
Automatic Folder Allocation System for Electronic Text Document
Repositories
Using Enhanced Bayesian Classification Approach
Wou Onn Choo (Faulty of Information Technology and Sciences, INTI
International University, Nilai, Malaysia), Lam Hong Lee (School
of
Computing, Faculty of Science and Technology, Quest International
University
Perak, Ipoh, Malaysia), Yen Pei Tay (School of Computing, Faculty
of Science
and Technology, Quest International University Perak, Ipoh,
Malaysia), Khang
Wen Goh (School of Computing, Faculty of Science and Technology,
Quest
International University Perak, Ipoh, Malaysia), Dino Isa
(Department of
Electrical and Electronic Engineering, Faculty of Engineering, The
University of Nottingham, Semenyih, Malaysia), Suliman Mohamed
Fati (INTI
International University, Nilai, Malaysia)
This article proposes a system equipped with the enhanced Bayesian
classification techniques to automatically assign folders to store
electronic text documents. Despite computer technology
advancements in the
information age where electronic text files are so pervasive in
information
exchange, almost every single document created or downloaded from
the
Internet requires manual classification by the users before being
deposited
into a folder in a computer. Not only does such a tedious task
cause
inconvenience to users, the time taken to repeatedly classify and
allocate a
folder for each text document impedes productivity, especially
when dealing
with a huge number of files and deep layers of folders. In order
to overcome
this, a prototype system is built to evaluate the performance of
the
enhanced Bayesian text classifier for automatic folder allocation,
by
categorizing text documents based on the existing types of text
documents
and folders present in user's hard drive. In this article, the
authors
deploy a High Relevance Keyword Extraction (HRKE) technique and an
Automatic
Computed Document Dependent (ACDD) Weighting Factor technique to a
Bayesian
classifier in order to obtain better classification accuracy,
while
maintaining the low training cost and simple classifying processes
using the
conventional Bayesian approach.
To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/automatic-folder-allocation-system-for-electronic
-text-document-repositories-using-enhanced-bayesian-classification-approach/
225066
<
https://www.igi-global.com/article/automatic-folder-allocation-system-for-e
lectronic-text-document-repositories-using-enhanced-bayesian-classification-
approach/225066>
To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=225066
<https://www.igi-global.com/viewtitlesample.aspx?id=225066>
ARTICLE 2
Modeling of Agent-Based Complex Network to Detect the Trust of
Investors in
P2P Platform
Yuwei Yan (School of Economics and Management, Taishan University,
Taian,
China), Jian Zhang (Personnel Department of Taishan University,
Taian,
China), Xiaomeng Ma (Post-Doctoral Scientific Research
Workstation, China
Merchants Bank, Shenzhen China)
Due to the lopsided nature of investor investment-related model
research
under the traditional P2P environment, and in order to improve the
research
effect, this study proposes an agent-based complex network testing
investor
trust model. This model is based on interest trust, and combines
with the
Bayesian method to effectively evaluate the model trust, and
builds a
multi-steady-state agent system based on this. At the same time,
it
effectively analyzes the evolutionary mechanism of the system, and
validates
the model's application in combination with comparative
experiments. The
research shows that the model can effectively improve the success
rate of
executing tasks and shorten the distance between cooperative
agents, thus
ensuring the reliability of the selection of cooperative objects
and
providing theoretical reference for subsequent related research.
To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/modeling-of-agent-based-complex-network-to-detect
-the-trust-of-investors-in-p2p-platform/225067
<
https://www.igi-global.com/article/modeling-of-agent-based-complex-network-
to-detect-the-trust-of-investors-in-p2p-platform/225067>
To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=225067
<https://www.igi-global.com/viewtitlesample.aspx?id=225067>
ARTICLE 3
Reasoning Temporally Attributed Spatial Entity Knowledge Towards
Qualitative
Inference of Geographic Process
Jayanthi Ganapathy (Anna University, Chennai, India), Uma V.
(Pondicherry
University, Puducherry, India)
Knowledge discovery with geo-spatial information processing is of
prime
importance in geomorphology. The temporal characteristics of
evolving
geographic features result in geo-spatial events that occur at a
specific
geographic location. Those events when consecutively occur result
in a
geo-spatial process that causes a phenomenal change over the
period of time.
Event and process are essential constituents in geo-spatial
dynamism. The
geo-spatial data acquired by remote sensing technology is the
source of
input for knowledge discovery of geographic features. This article
performs
qualitative inference of geographic process by identifying events
causing
geo-spatial deformation over time. The evolving geographic
features and
their types have association with spatial and temporal factors.
Event
calculus-based spatial knowledge formalism allows reasoning over
intervals
of time. Hence, representation of Event Attributed Spatial Entity
(EASE)
Knowledge is proposed. Logical event-based queries are evaluated
on the
formal representation of EASE Knowledge Base. Event-based queries
are
executed on the proposed knowledge base and when experimented on,
real data
sets yielded comprehensive results. Further, the significance of
EASE-based
spatio-temporal reasoning is proved by evaluating with respect to
query
processing time and accuracy. The enhancement of EASE with a
direction for
further development to explore its significance towards prediction
is
discussed towards the end.
To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/reasoning-temporally-attributed-spatial-entity-kn
owledge-towards-qualitative-inference-of-geographic-process/225068
<
https://www.igi-global.com/article/reasoning-temporally-attributed-spatial-
entity-knowledge-towards-qualitative-inference-of-geographic-process/225068>
To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=225068
<https://www.igi-global.com/viewtitlesample.aspx?id=225068>
ARTICLE 4
Evolutionary Game Model of Information Sharing Behavior in Supply
Chain
Network With Agent-Based Simulation
Jian Tan (Guizhou University of Finance and Economics, Guiyang,
China),
Guoqiang Jiang (Guizhou University of Finance and Economics,
Guiyang,
China), Zuogong Wang (Henan University, Kaifeng, China)
In the supply chain network, information sharing between
enterprises can
produce synergistic effect and improve the benefits. In this
article,
evolutionary game theory is used to analyse the evolution process
of the
information sharing behaviour between supply chain network
enterprises with
different penalties and information sharing risk costs. Analysis
and
agent-based simulation results show that when the amount of
information
between enterprises in supply chain networks is very large, it is
difficult
to form a sharing of cooperation; increase penalties, control cost
sharing
risk can increase the probability of supply chain information
sharing
network and shorten the time for information sharing.
To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/evolutionary-game-model-of-information-sharing-be
havior-in-supply-chain-network-with-agent-based-simulation/225069
<
https://www.igi-global.com/article/evolutionary-game-model-of-information-s
haring-behavior-in-supply-chain-network-with-agent-based-simulation/225069>
To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=225069
<https://www.igi-global.com/viewtitlesample.aspx?id=225069>
ARTICLE 5
Research on Multi-Source Data Integration Based on Ontology and
Karma
Modeling
Hongyan Yun (College of Computer Science and Technology, Qingdao
University,
Qingdao, China), Ying He (School of Electronic Information,
Qingdao
University, Qingdao, China), Li Lin (College of Computer Science
and
Technology, Qingdao University, Qingdao, China), Xiaohong Wang
(Qilu
University of Technology, Shandong Academy of Science, Shandong
Computer
Science Center, Shandong, China)
The purpose of data integration is that integrates multi-source
heterogeneous data. Ontology solves semantic describing of
multi-source
heterogeneous data. The authors propose a practical approach based
on
ontology modeling and an information toolkit named Karma modeling
for fast
data integration, and demonstrate an application example in
detail. Armed
Conflict Location & Event Data Project (ACLED) is a publicly
available
conflict event dataset designed for disaggregated conflict
analysis and
crisis mapping. The authors analyzed the ACLED dataset and domain
knowledge
to build an Armed Conflict Event ontology, then constructed Karma
models to
integrate ACLED datasets and publish RDF data. Through SPARQL
query to check
the correctness of published RDF data. Authors design and
developed an ACLED
Query System based on Jena API, Canvas JS, and Baidu API, etc.
technologies,
which provides convenience for governments and researches to
analyze
regional conflict events and crisis early warning, and it verifies
the
validity of constructed ontology and the correctness of Karma
modeling.
To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/research-on-multi-source-data-integration-based-o
n-ontology-and-karma-modeling/225070
<
https://www.igi-global.com/article/research-on-multi-source-data-integratio
n-based-on-ontology-and-karma-modeling/225070>
To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=225070
<https://www.igi-global.com/viewtitlesample.aspx?id=225070>
_____
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
<https://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
* Ulrich's Periodicals Directory
* Web of Science
* Web of Science Emerging Sources Citation Index (ESCI)
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
Co-Director, Center for Data Science and Big Data Analytics
School of Business Administration
Oakland University
Rochester, MI 48309
Phone: 248-370-4649
Fax: 248-370-4275
Email:
sugumara@oakland.edu <mailto:sugumara@oakland.edu>
=============================================
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