Information Systems Architecture and Technology

Wrocław University of Technology Information Systems Architecture and Technology Intelligent Information Systems, Knowledge Discovery, Big Data and High Performance Computing Editors Leszek Borzemski Adam Grzech Jerzy Świątek Zofia Wilimowska Wrocław 2013 Publication partly supported by Faculty of Computer Science and Management Wrocław University of Technology Project editor Arkadiusz GÓRSKI The book has been printed in the camera ready form All rights reserved. no part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior permission in writting of the Publisher. © Copyright by Oficyna Wydawnicza Politechniki Wrocławskiej, Wrocław 2013 OFICynA WydawnICzA POlITEChnIKI WROCławskiej Wybrzeże Wyspiańskiego 27, 50-370 Wrocław http://www.oficyna.pwr.wroc.pl; e-mail: [email protected] [email protected] ISBn 978-83-7493-800-6 CONTENTS Introduction ......................................................................................................................... 5 PART 1: INTELLIGENT INFORMATION SYSTEMS AND KNOWLEDGE DISCOVERY 1. Norbert BOLEŃSKI, Edward SZCZERBICKI A Concept of Using Knowledge Models to Secure Intellectual Capital in Enter- prise .................................................................................................................... 13 2. Dominik WIĘCEK, Radosław Piotr KATARZYNIAK Modal Equivalences as Linguistic Summarization of Data Resources ........................ 23 3. Grzegorz SKORUPA, Radosław KATARZYNIAK, Łukasz MODLIŃSKI, Mariusz MULKA Multi-Agent Platform for Fuzzy Structures Integration Task ...................................... 33 4. Grzegorz SKORUPA, Jan JAKUBIK, Bartosz FIDRYSIAK A Consensus Method for Integration of Knowledge Expressed in Form of Modal Formulas ...................................................................................................................... 43 5. Dominik WIĘCEK, Aleksander ŚWIĄTKOWSKI, Łukasz LEŚNICZEK Multi-Agent Framework for Inconsistent Sensor Data Integration ............................. 53 6. Wojciech FRYS, Krzysztof JUSZCZYSZYN Generation of Scale-Free Network Graphs with Given Motif Distribution ................. 63 PART 2: ARTIFICIAL INTELLIGENCE AND MULTIAGENT SYSTEMS 7. Grzegorz POPEK Similarity of Rough Sets and Its Application to Knowledge Processing ..................... 75 8. Wojciech LORKIEWICZ Measuring the Collective Alignment of Individual Naming Conventions .................. 85 9. Adam CZARNECKI, Tomasz SITEK Ontologies vs. Rules – Comparison of Methods of Knowledge Representation Based on the Example of It Services Management ................................................................ 99 10. Grzegorz BLINOWSKI, Henryk RYBIŃSKI, Tomasz RAMSZA, Tomasz KUSTRA Αlpha-ISIS – Web- and Cloud-Oriented Information Storage and Retrieval Environment ................................................................................................................ 111 4 11. Grzegorz POPEK, Michał ADAMSKI, Łukasz BURDKA A Multiagent System for Consensus-Based Integration of Semi-Hierarchical Partitions ............................................................................................................. 123 PART 3: BIG DATA AND HIGH PERFORMANCE COMPUTING 12. Kamil KSIĄŻEK, Piotr SAPIECHA Using Graphics Processing Unit to Accelerate Database Query Execution ................ 135 13. Dariusz BANASIAK, Jarosław MIERZWA, Antoni STERNA Detection and Correction of Errors in Polish Based on Dependency Grammar .......... 145 14. Jan KWIATKOWSKI, Maciej DZIK Parallel Distributed Computing Using JavaScript ....................................................... 155 15. Zbigniew BUCHALSKI An Heuristic Procedure of Tasks Scheduling in Parallel Machines System ................ 165 16. Michal GORAWSKI Load Balancing in Data Warehouse – Evolution and Perspectives ............................. 175 17. Piotr KOSZULIŃSKI, Ziemowit NOWAK ASvis: Web-Based Large Graph Search Engine and Visualizer ................................. 187 18. Jacek CISŁO, Dariusz KONIECZNY Development and Testing Performance of Computing Cluster Consisting of Networked Graphics Cards ............................................................................................................ 197 INTRODUCTION Intelligent Information Systems, Knowledge Discovery, Big Data and High Perform- ance Computing are key challenges in today’s IT research and development. New IT developments and design paradigms in these domains are very crucial in business be- cause they provide pioneering ways to boost business performance to be more competi- tive on the market. The advance of Intelligent Information Systems (IIS) runs especially in the Internet based environments where new concepts, models, services and application are develop- ing every day. In this book we present issues related to different aspects of IISs, including characterization of the new architectures, use of artificial intelligence in tackling challenging problems, knowledge discovery and data mining as well as the Big Data and high performance computing issues. This book consists of chapters presenting a balanced coverage of emerging IIS problems concerning: Part 1. Intelligent Information Systems and Knowledge Discovery Part 2. Artificial Intelligence and Multiagent Systems Part 3. Big Data and High Performance Computing PART 1: INTELLIGENT INFORMATION SYSTEMS AND KNOWLEDGE DISCOVERY Chapter 1 presents a concept of using knowledge models to secure intellectual capital in enterprise based on Decisional DNA that will allow the company to accumulate knowledge and protect its’ previously gained intellectual capital. Decisional DNA is a domain-independent and flexible knowledge representation structure. Its main features of acquiring and storing experiential knowledge of formal decisional events are used to deal with unexpected situations, especially, convert unstructured data into well- structured knowledge, including, information from websites. This work focuses on tools based on SOEKS (Set of Experience Knowledge Structure) and Decisional DNA that will allow the company to accumulate knowledge and protect its’ previously gained intellectual capital. They will be also designed to enable delegating duties to less experi- enced employees by providing them with an instrument that will allow them to inde- pendently perform more complicated tasks. 6 Introduction Chapter 2 describes a user-centric approach to the extraction of modal equivalences as linguistic summarizations of huge amounts of data. The user orientation is realized by use of semi-natural language statements. The approach follows from an original proposal formulated in a series of previous works in which modal literals, modal conjunctions, modal inclusive and exclusive alternatives as well as modal conditionals were used to capture the result of knowledge extraction from relational data repositories. The originality of this approach follows from the fact that the ex- isting data resources to be summarized are treated as empirical knowledge bases developed by autonomous systems (regardless from their actual nature) and prag- matically interpreted as dialogue systems. These dialogue systems are assumed to be equipped with semi-natural language processing modules producing narrow class of semi-natural language statements being commonsense interpretations of the above mentioned modal formulas. Chapter 3 presents an approach to integrating fuzzy structures. There is introduced a multi-agent system with observer agents and one main agent. Observer agents in- form main agent about observed objects using linguistic values. Main agent’s task is to integrate gathered data and propose a few mutually exclusive solutions if data is inconsistent. Two strategies for validating data consistency based on Silhouette and GAP Statistics are proposed. Integration process is performed using consensus based method. A prototype platform was implemented and obtained results are presented. Chapter 4 demonstrates an approach to the problem of integration of knowledge expressed in form of modal formulas with operators for possibility, belief and certainty. The authors assume that an agent is collecting messages describing properties of an external object from a group of other agents in order to create his own prepositional attitude. The language of communication allows sentences in form OP(p), where OP is a modal operator of possibility, belief or certainty, and p is logical conjunction, alternative or exclusive alternative of two prepositional variables. The receiving agent collects the knowledge using a form of internal representation. A simple consensus method is applied in order to integrate the gathered knowledge, and the resulting consensus is sub- sequently used to create a set of sentences that can be communicated by the agent, ac- cording to the rules described in works concerning the problem of grounding modalities. A simple framework for testing this algorithm was developed. Sample results of integration are presented. Chapter 5 deals with the multi-agent framework for inconsistent sensor data integration. Data is integrating into a consistent set of easily accessible and manageable records. The main process is based on consensus algorithm which converts data using summation minimization. Principal agent not only integrates data, but also checks whether the level of consistency in the data set is acceptable or not and may propose alternative solutions with higher level

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