LEADER 04590nam 22006255 450 001 9910483632703321 005 20251113202025.0 010 $a3-030-36056-3 024 7 $a10.1007/978-3-030-36056-6 035 $a(CKB)4940000000149981 035 $a(MiAaPQ)EBC5989314 035 $a(DE-He213)978-3-030-36056-6 035 $a(PPN)243767226 035 $a(EXLCZ)994940000000149981 100 $a20191204d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRecent Advances on Soft Computing and Data Mining $eProceedings of the Fourth International Conference on Soft Computing and Data Mining (SCDM 2020), Melaka, Malaysia, January 22??23, 2020 /$fedited by Rozaida Ghazali, Nazri Mohd Nawi, Mustafa Mat Deris, Jemal H. Abawajy 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (491 pages) 225 1 $aAdvances in Intelligent Systems and Computing,$x2194-5365 ;$v978 300 $aIncludes index. 311 08$a3-030-36055-5 327 $aChapter 1: An Enhanced Model for Digital Reference Services (MDRS) -- Chapter 2: Fuzzy Random Based Mean Variance Model For Agricultural Production Planning -- Chapter 3: Residual Neural Network vs Local Binary Convolutional Neural Networks for Bilingual Handwritten Digit Recognition -- Chapter 4: Incorporating the Markov Chain Model in WBSN for Improving Patients? Remote Monitoring Systems -- Chapter 5: Designing Deep Neural Network with Chicken Swarm Optimization for Violence Video Classification using VSD2014 Dataset -- Chapter 6: Header Based Email Spam Detection Framework Using Support Vector Machine (SVM) Technique -- Chapter 7: A Mechanism to Support Agile Frameworks Enhancing Reliability Assessment for SCS Development: A Case Study of Medical Surgery Departments -- Chapter 8: Link Bandwidth Recommendation for Indonesian E-Health Grid -- Chapter 9: Investigating the Optimal Parameterization of Deep Neural Network and Synthetic DataWorkflow for Imbalance Liver Disorder Dataset Classification -- Chapter 10: Genetic Algorithm Based Parallel K-Means Data Clustering Algorithm Using MapReduce Programming Paradigm on Hadoop Environment (GAPKCA) -- Chapter 11: Android Botnet Detection by Classification Techniques. 330 $aThis book provides an introduction to data science and offers a practical overview of the concepts and techniques that readers need to get the most out of their large-scale data mining projects and research studies. It discusses data-analytical thinking, which is essential to extract useful knowledge and obtain commercial value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad interdisciplinary range of scientific methods and processes. The book provides readers with sufficient knowledge to tackle a wide range of issues in complex systems, bringing together the scopes that integrate soft computing and data mining in various combinations of applications and practices, since to thrive in these data-driven ecosystems, researchers, data analysts and practitioners must understand the design choice and options of these approaches. This book helps readers to solve complex benchmark problems and to better appreciate the concepts, tools and techniques used. 410 0$aAdvances in Intelligent Systems and Computing,$x2194-5365 ;$v978 606 $aComputational intelligence 606 $aEngineering$xData processing 606 $aArtificial intelligence 606 $aComputational Intelligence 606 $aData Engineering 606 $aArtificial Intelligence 615 0$aComputational intelligence. 615 0$aEngineering$xData processing. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aData Engineering. 615 24$aArtificial Intelligence. 676 $a006.3 676 $a006.3 702 $aGhazali$b Rozaida$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aNawi$b Nazri Mohd$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aDeris$b Mustafa Mat$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aAbawajy$b Jemal H$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483632703321 996 $aRecent Advances on Soft Computing and Data Mining$91933393 997 $aUNINA