-------- Weitergeleitete Nachricht -------- Betreff: [AISWorld] Content Alert - International Journal of Intelligent Information Technologies, Vol. 13, No. 1 Datum: Tue, 10 Jan 2017 15:21:53 -0500 Von: Vijayan Sugumaran sugumara@oakland.edu An: aisworld@lists.aisnet.org

The contents of the latest issue of: International Journal of Intelligent Information Technologies (IJIIT) Volume 13, Issue 1, January - March 2017 Indexed by: Compendex (Elsevier Engineering Index), INSPEC, SCOPUS 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-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

Influential Researcher Identification in Academic Network Using Rough Set Based Selection of Time-Weighted Academic and Social Network Features

Manju G. (Anna University, Department of Computer Science, Tamil Nadu, India), Kavitha V. (Anna University, Department of Computer Science, Tamil Nadu, India), Geetha T.V. (Anna University, Department of Computer Science, Tamil Nadu, India)

Researchers entering into a new research area are interested in knowing the current research trends, popular publications and influential (popular) researchers in that area in order to initiate their research. In this work, we attempt to determine the influential researcher for a specific topic. The active participation of the researchers in both the academic and social network activities signifies the researchers' influence level across time. The content and frequency of social interaction to a researcher reflects his or her influence. In our system, appropriate time-based social and academic features are selected using entropy based feature selection approach of rough set theory. A three layer model comprising semantically related concepts, researcher and social relations is developed based on the appropriate (influential) features. The researchers' topic trajectories are identified and recommended using Spreading activation algorithm. To cope up with the scalable academic network, map reduce paradigm has been employed in the spreading activation algorithm.

To obtain a copy of the entire article, click on the link below. www.igi-global.com/article/influential-researcher-identification-in-academic -network-using-rough-set-based-selection-of-time-weighted-academic-and-socia l-network-features/175326 http://www.igi-global.com/article/influential-researcher-identification-in- academic-network-using-rough-set-based-selection-of-time-weighted-academic-a nd-social-network-features/175326

To read a PDF sample of this article, click on the link below. www.igi-global.com/viewtitlesample.aspx?id=175326 http://www.igi-global.com/viewtitlesample.aspx?id=175326

ARTICLE 2

Materialized View Selection using Artificial Bee Colony Optimization

Biri Arun (Jawaharlal Nehru University, School of Computer and Systems Sciences, New Delhi, India), T.V. Vijay Kumar (Jawaharlal Nehru University, School of Computer and Systems Sciences, New Delhi, India)

Data warehouse is an essential component of almost every modern enterprise information system. It stores huge amount of subject-oriented, time-stamped, non-volatile and integrated data. It is highly required of the system to respond to complex online analytical queries posed against its data warehouse in seconds for efficient decision making. Optimization of online analytical query processing (OLAP) could substantially minimize delays in query response time. Materialized view is an efficient and effective OLAP query optimization technique to minimize query response time. Selecting a set of such appropriate views for materialization is referred to as view selection, which is a nontrivial task. In this regard, an Artificial Bee Colony (ABC) based view selection algorithm (ABCVSA), which has been adapted by incorporating N-point and GBFS based N-point random insertion operations, to select Top-K views from a multidimensional lattice is proposed. Experimental results show that ABCVSA performs better than the most fundamental view selection algorithm HRUA. Thus, the views selected using ABCVSA on materialization would reduce the query response time of OLAP queries and thereby aid analysts in arriving at strategic business decisions in an effective manner.

To obtain a copy of the entire article, click on the link below. www.igi-global.com/article/materialized-view-selection-using-artificial-bee- colony-optimization/175327 http://www.igi-global.com/article/materialized-view-selection-using-artific ial-bee-colony-optimization/175327

To read a PDF sample of this article, click on the link below. www.igi-global.com/viewtitlesample.aspx?id=175327 http://www.igi-global.com/viewtitlesample.aspx?id=175327

ARTICLE 3

Fuzzy Rule Based Environment Monitoring System for Weather Controlled Laboratories using Arduino

S. Sasirekha (SSN College of Engineering, Department of Information Technology, Chennai, India), S. Swamynathan (Anna University, Department of Information Science and Technology, Chennai, India)

Weather controlled laboratories such as blood banks, plasma centers, biomedical, research, pharmacy and healthcare always require a portable, low cost and web-based centralized wireless monitoring system. However, it has become more stringent to monitor various weather controlling devices of these laboratories in order to reduce the risk of non-compliance with accreditation requirements. In literature, it is inferred that the majority of existing event detection approaches relies only on precise value to specify event thresholds, but those values cannot adequately handle the imprecise sensor reading. Therefore, in this work, one of the soft computing technologies, fuzzy logic is adopted to demonstrate that fuzzy rule based value significantly improves the accuracy of event detection. The prototype built is tested in a physical laboratory as a personal mobile weather station for monitoring and analyzing the environmental conditions using fuzzy simulated values.

To obtain a copy of the entire article, click on the link below. www.igi-global.com/article/fuzzy-rule-based-environment-monitoring-system-fo r-weather-controlled-laboratories-using-arduino/175328 http://www.igi-global.com/article/fuzzy-rule-based-environment-monitoring-s ystem-for-weather-controlled-laboratories-using-arduino/175328

To read a PDF sample of this article, click on the link below. www.igi-global.com/viewtitlesample.aspx?id=175328 http://www.igi-global.com/viewtitlesample.aspx?id=175328

ARTICLE 4

A Model for Text Summarization

Rasim M. Alguliyev (Azerbaijan National Academy of Sciences, Institute of Information Technology, Baku, Azerbaijan), Ramiz M. Aliguliyev (Azerbaijan National Academy of Sciences, Institute of Information Technology, Baku, Azerbaijan), Nijat R. Isazade (Azerbaijan National Academy of Sciences, Institute of Information Technology, Baku, Azerbaijan), Asad Abdi (University of Malaya, Department of Artificial Intelligence, Kuala Lumpur, Malaysia), Norisma Idris (University of Malaya, Department of Artificial Intelligence, Kuala Lumpur, Malaysia)

Text summarization is a process for creating a concise version of document(s) preserving its main content. In this paper, to cover all topics and reduce redundancy in summaries, a two-stage sentences selection method for text summarization is proposed. At the first stage, to discover all topics the sentences set is clustered by using k-means method. At the second stage, optimum selection of sentences is proposed. From each cluster the salient sentences are selected according to their contribution to the topic (cluster) and their proximity to other sentences in cluster to avoid redundancy in summaries until the appointed summary length is reached. Sentence selection is modeled as an optimization problem. In this study, to solve the optimization problem an adaptive differential evolution with novel mutation strategy is employed. With a test on benchmark DUC2001 and DUC2002 data sets, the ROUGE value of summaries got by the proposed approach demonstrated its validity, compared to the traditional methods of sentence selection and the top three performing systems for DUC2001 and DUC2002.

To obtain a copy of the entire article, click on the link below. www.igi-global.com/article/a-model-for-text-summarization/175329 http://www.igi-global.com/article/a-model-for-text-summarization/175329

To read a PDF sample of this article, click on the link below. www.igi-global.com/viewtitlesample.aspx?id=175329 http://www.igi-global.com/viewtitlesample.aspx?id=175329

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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: www.igi-global.com/isj http://www.igi-global.com/e-resources/infosci-databases/infosci-journals/ .

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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 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

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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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