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Using Domain Knowledge in Initial Stages of KDD : Optimization of Compound Object Processing

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
We present a set of guidelines for improving quality and efficiency in initial steps of the KDD process by utilizing various kinds of domain knowledge. We discuss how such knowledge may be used to the advantage of system developer and what kinds of improvements can be achieved. We focus on systems that incorporate creation and processing of compound data objects within the RDBMS framework. These basic considerations are illustrated with several examples of implemented database solutions.
Wydawca
Rocznik
Strony
341--364
Opis fizyczny
Bibliogr. 27 poz., rys., tab.
Twórcy
autor
  • Institute of Mathematics, The University of Warsaw Warsaw, Poland
  • Systems Research Institute, Polish Academy of Sciences and Dituel Sp. z o.o. Warsaw, Poland
autor
  • Section of Computer Science, The Main School of Fire Service Warsaw, Poland
autor
  • Section of Computer Science, The Main School of Fire Service Warsaw, Poland
Bibliografia
  • [1] Jeff Beck and Ed Sequeira. PubMed Central (PMC): An archive for literature from life sciences journals. In J. McEntyre and J. Ostell, editors, The NCBI Handbook, chapter 9. National Center for Biotechnology Information, Bethesda, 2003.
  • [2] Robert Bembenik, Łukasz Skonieczny, Henryk Rybi´nski, and Marek Niezgódka, editors. Intelligent Tools for Building a Scientific Information Platform, volume 390 of Studies in Computational Intelligence. Springer, Berlin / Heidelberg, 2012.
  • [3] Sagarmay Deb. Multimedia Systems and Content-Based Image Retrieval. ITPro collection. IGI Global, 2004.
  • [4] Andrew Eisenberg, Jim Melton, Krishna Kulkarni, Jan-Eike Michels, and Fred Zemke. SQL:2003 has been published. SIGMOD Rec., 33(1):119–126, March 2004.
  • [5] Paul Elzinga, Jonas Poelmans, Stijn Viaene, Guido Dedene, and Shanti Morsing. Terrorist threat assessment with formal concept analysis. In Intelligence and Security Informatics (ISI), 2010 IEEE International Conference on, pages 77–82. IEEE, 2010.
  • [6] Usama M. Fayyad, Gregory Piatetsky-Shapiro, and Padhraic Smyth. From data mining to knowledge discovery: An overview. In Advances in Knowledge Discovery and Data Mining, pages 1–34. 1996.
  • [7] Evgeniy Gabrilovich and Shaul Markovitch. Computing semantic relatedness using Wikipedia-based explicit semantic analysis. In Proceedings of the 20th International Joint Conference on Artificial Intelligence, pages 6–12, 2007.
  • [8] Andrzej Janusz, Wojciech Świeboda, Adam Krasuski, and Hung Son Nguyen. Interactive document indexing method based on explicit semantic analysis. In Proceedings of the Joint Rough Sets Symposium (JRS 2012), Chengdu, China, August 17-20, 2012, Lecture Notes in Computer Science. Springer, 2012.
  • [9] Marcin Kowalski, Dominik ´ Sle¸zak, Krzysztof Stencel, Przemysław Pardel, Marek Grzegorowski, and Michał Kijowski. RDBMS model for scientific articles analytics. In Bembenik et al. [2], chapter 4, pages 49–60.
  • [10] Adam Krasuski, Karol Kreński, and Stanisław Łazowy. A method for estimating the efficiency of commanding in the state fire service of Poland. Fire Technology, 48(4):795–805, 2012.
  • [11] Adam Krasuski, Karol Kreński, Piotr Wasilewski, and Stanisław Łazowy. Granular approach in knowledge discovery - real time blockage management in fire service. In Tian rui Li, Hung Son Nguyen, Guoyin Wang, Jerzy W. Grzymala-Busse, Ryszard Janicki, Aboul Ella Hassanien, and Hong Yu, editors, RSKT, volume 7414 of Lecture Notes in Computer Science, pages 416–421. Springer, 2012.
  • [12] Adam Krasuski, Dominik Ślęzak, Karol Kreński, and Stanisław Łazowy. Granular knowledge discovery framework. In New Trends in Databases and Information Systems, volume 185 of Advances in Intelligent Systems and Computing, pages 109–118. Springer, 2013.
  • [13] Adam Krasuski and Marcin Szczuka. Knowledge driven query sharding. In Louchka Popova-Zeugmann, editor, CS&P 2012, volume 225 of Informatik Berichte, pages 182–190, Berlin, Germany, 2012. Humboldt Univeristät zu Berlin.
  • [14] Sebastian Michel, Peter Triantafillou, and Gerhard Weikum. KLEE: a framework for distributed top-k query algorithms. In Proceedings of the 31st international conference on Very large data bases, VLDB ’05, pages 637–648. VLDB Endowment, 2005.
  • [15] Anh Linh Nguyen and Hung Son Nguyen. On designing the SONCA system. In Bembenik et al. [2], chapter 2, pages 9–35.
  • [16] Hung Son Nguyen, Dominik Ślęzak, Andrzej Skowron, and Jan Bazan. Semantic search and analytics over large repository of scientific articles. In Bembenik et al. [2], chapter 1, pages 1–8.
  • [17] Victor Pankratius and Martin Heneka. Parallel SQL query auto-tuning on multicore. Karlsruhe Reports in Informatics 2011-5, Karlsruhe Institute of Technology, Faculty of Informatics, 2011.
  • [18] Witold Pedrycz, Andrzej Skowron, and Vladik Kreinovich, editors. Handbook of Granular Computing. John Wiley & Sons, 2008.
  • [19] Jonas Poelmans, Paul Elzinga, Stijn Viaene, and Guido Dedene. An exploration into the power of formal concept analysis for domestic violence analysis. In Petra Perner, editor, ICDM, volume 5077 of Lecture Notes in Computer Science, pages 404–416. Springer, 2008.
  • [20] Andrzej Skowron. Discovery of processes and their interactions from data and domain knowledge. In Piotr Jedrzejowicz, Ngoc Thanh Nguyen, Robert J. Howlett, and Lakhmi C. Jain, editors, KES-AMSTA (1), volume 6070 of Lecture Notes in Computer Science, pages 12–21. Springer, 2010.
  • [21] Dominik Ślęzak and Victoria Eastwood. Data warehouse technology by in fobright. In Ugur Çetintemel, Stanley B. Zdonik, Donald Kossmann, and Nesime Tatbul, editors, SIGMOD Conference, pages 841–846. ACM, 2009.
  • [22] Dominik Ślęzak, Andrzej Janusz, Wojciech ´Świeboda, Hung Son Nguyen, Jan G. Bazan, and Andrzej Skowron. Semantic analytics of PubMed content. In Andreas Holzinger and Klaus-Martin Simonic, editors, Information Quality in e-Health - 7th Conference of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society, USAB 2011, Graz, Austria, November 25-26, 2011. Proceedings, volume 7058 of Lecture Notes in Computer Science, pages 63–74. Springer, 2011.
  • [23] Dominik Ślęzak and Łukasz Sosnowski. Sql-based compound object comparators: A case study of images stored in ice. In Tai-Hoon Kim, Haeng-Kon Kim, Muhammad Khurram Khan, Kiumi Akingbehin, Wai-Chi Fang, and Dominik Ślęzak, editors, Advances in Software Engineering - International Conference, FGITASEA 2010. Proceedings, volume 117 of Communications in Computer and Information Science, pages 303–316. Springer, 2010.
  • [24] Łukasz Sosnowski. Identification of compound objects using comparators. In A. Myśliński, editor, Information technology theory and application, volume 2, pages 114–135. IBS PAN, 2012. In Polish.
  • [25] Łukasz Sosnowski and Dominik Ślęzak. Comparators for compound object identification. In Sergei O. Kuznetsov, Dominik Slezak, Daryl H. Hepting, and Boris Mirkin, editors, RSFDGrC 2011. Proceedings, volume 6743 of Lecture Notes in Computer Science, pages 342–349. Springer, 2011.
  • [26] Łukasz Sosnowski and Dominik Ślęzak. RDBMS framework for contour identication. In Marcin Szczuka, Ludwik Czaja, Andrzej Skowron, and Magdalena Kacprzak, editors, CS&P 2011, pages 487–498, Pułtusk, Poland, 2011. Białystok University of Technology. Electronic edition.
  • [27] Yingxu Wang, Witold Kinsner, James A. Anderson, Du Zhang, Yiyu Yao, Phillip C.-Y. Sheu, Jeffrey J. P. Tsai, Witold Pedrycz, Jean-Claude Latombe, Lotfi A. Zadeh, Dilip Patel, and Christine W. Chan. A doctrine of Cognitive Informatics (CI). Fundamenta Informaticae, 90(3):203–228,
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-19f0d11b-8aaf-4dd1-9528-21c86cd2220d
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