-------- Forwarded Message -------- Subject: [AISWorld] Contents of IJIIT 15(2) - International Journal of Intelligent Information Technologies (IJIIT) Date: Tue, 12 Mar 2019 12:23:28 -0400 From: Vijayan Sugumaran sugumara@oakland.edu To: aisworld@lists.aisnet.org

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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