07468nam 22006615 450 99646559400331620220519141456.03-642-53917-310.1007/978-3-642-53917-6(CKB)3710000000078898(DE-He213)978-3-642-53917-6(SSID)ssj0001090076(PQKBManifestationID)11589330(PQKBTitleCode)TC0001090076(PQKBWorkID)11126848(PQKB)10682934(MiAaPQ)EBC3093495(PPN)176118381(EXLCZ)99371000000007889820131216d2013 u| 0engurnn#008mamaatxtrdacontentcrdamediacrrdacarrierAdvanced Data Mining and Applications[electronic resource] 9th International Conference, ADMA 2013, Hangzhou, China, December 14-16, 2013, Proceedings, Part II /edited by Hiroshi Motoda, Zhaohui Wu, Longbing Cao, Osmar Zaiane, Min Yao, Wei Wang1st ed. 2013.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2013.1 online resource (XXII, 538 p. 163 illus.)Lecture Notes in Artificial Intelligence ;8347Bibliographic Level Mode of Issuance: Monograph3-642-53916-5 Clustering -- Semi-Supervised Clustering Ensemble Evolved by Genetic Algorithm for Web Video Categorization -- A Scalable Approach for General Correlation Clustering -- A fast spectral clustering method based on growing vector quantization for large data sets -- A Novel Deterministic Sampling Technique to Speedup Clustering Algorithms -- Software Clustering using Automated Feature Subset Selection -- The Use of Transfer Algorithm for Clustering Categorical Data -- eDARA: Ensembles DARA -- Efficient mining maximal variant and low usage rate biclusters without candidate maintenance in real function-resource matrix: the DeCluster algorithm -- Association Rule Mining -- MEIT: Memory Efficient Itemset Tree for Targeted Association Rule Mining -- Pattern Mining -- Mining Frequent Patterns in Print Logs with Semantically Alternative Labels -- Minimising K-Dominating Set in Arbitrary Network Graphs -- Regression -- Logistic Regression Bias Correction for Large Scale Data with Rare Events -- An Automatical Moderating System for FML using Hashing Regression -- Batch-to-Batch Iterative Learning Control Based on Kernel Independent Component Regression Model -- Prediction -- Deep Architecture for Traffic Flow Prediction -- Compact Prediction Tree: A Lossless Model for Accurate Sequence Prediction -- Generalization of Malaria Incidence Prediction Models by Correcting Sample Selection Bias -- Protein Interaction Hot Spots Prediction using LS-SVM within the Bayesian Interpretation -- Predicting the survival status of cancer patients with Traditional Chinese Medicine Symptom Variation using Logistic Regression Model -- Feature Extraction -- Exploiting Multiple Features for Learning to Rank in Expert Finding -- Convolution Neural Network for Relation Extraction -- Extracting Fuzzy Rules from Hierarchical Heterogeneous Neural Networks for Cardiovascular Diseases Diagnosis -- kDMI: A Novel Method for Missing Values Imputation Using Two Levels of Horizontal Partitioning in a Data set -- Identification -- Traffic Session Identification based on Statistical Language Model -- Role Identification Based on the Information Dependency Complexity -- Detecting Professional Spam Reviewers -- Chinese Comparative Sentence Identification Based on the Combination of Rules and Statistics -- Privacy Preservation -- Utility Enhancement for Privacy Preserving Health Data Publishing -- Optimizing Placement of Mix Zones to Preserve Users' Privacy for Continuous Query Services in Road Networks -- Applications -- Comparison of Cutoff Strategies for Geometrical Features in Machine Learning-based Scoring Functions -- Bichromatic Reverse Ranking Query in Two Dimensions -- Passive Aggressive Algorithm for Online Portfolio Selection with Piecewise Loss Function -- Mining Item Popularity for Recommender Systems -- Exploring an Ichthyoplankton Database from a Freshwater Reservoir in Legal Amazon -- A Pre-initialization Stage of Population-based Bio-inspired Metaheuristics for Handling Expensive Optimization Problems -- A Hybrid-sorting Semantic Matching Method -- Improving Few Occurrence Feature Performance in Distant Supervision for Relation Extraction -- Cluster Labeling Extraction and Ranking Feature Selection for High Quality XML Pseudo Relevance Feedback Fragments Set -- Informed Weighted Random Projection for Dimension Reduction -- Protocol Specification Inference Based on Keywords Identification -- An Adaptive Collaborative Filtering Algorithm Based on Multiple Features -- Machine Learning -- Ensemble of Unsupervised and Supervised Models with Different Label Spaces -- Cost-sensitive Extreme Learning Machine -- Multi-objective Optimization for Overlapping Community Detection -- Endmember Extraction by Exemplar Finder -- EEG-Based User Authentication in Multilevel Security Systems -- A new fuzzy extreme learning machine for regression problems with outliers or noises.The two-volume set LNAI 8346 and 8347 constitutes the thoroughly refereed proceedings of the 9th International Conference on Advanced Data Mining and Applications, ADMA 2013, held in Hangzhou, China, in December 2013. The 32 regular papers and 64 short papers presented in these two volumes were carefully reviewed and selected from 222 submissions. The papers included in these two volumes cover the following topics: opinion mining, behavior mining, data stream mining, sequential data mining, web mining, image mining, text mining, social network mining, classification, clustering, association rule mining, pattern mining, regression, predication, feature extraction, identification, privacy preservation, applications, and machine learning.Lecture Notes in Artificial Intelligence ;8347Artificial intelligenceData miningInformation storage and retrievalArtificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Data Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Information Storage and Retrievalhttps://scigraph.springernature.com/ontologies/product-market-codes/I18032Artificial intelligence.Data mining.Information storage and retrieval.Artificial Intelligence.Data Mining and Knowledge Discovery.Information Storage and Retrieval.006.3Motoda Hiroshiedthttp://id.loc.gov/vocabulary/relators/edtWu Zhaohuiedthttp://id.loc.gov/vocabulary/relators/edtCao Longbingedthttp://id.loc.gov/vocabulary/relators/edtZaiane Osmaredthttp://id.loc.gov/vocabulary/relators/edtYao Minedthttp://id.loc.gov/vocabulary/relators/edtWang Wei1973-edthttp://id.loc.gov/vocabulary/relators/edtBOOK996465594003316Advanced Data Mining and Applications771989UNISA04321nam 22004695 450 991025466000332120200629202543.03-319-55895-110.1007/978-3-319-55895-0(DE-He213)978-3-319-55895-0(MiAaPQ)EBC5595714(PPN)201474735(CKB)4340000000062183(EXLCZ)99434000000006218320170502d2017 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierModern Meta-Analysis Review and Update of Methodologies /by Ton J. Cleophas, Aeilko H. Zwinderman1st ed. 2017.Cham :Springer International Publishing :Imprint: Springer,2017.1 online resource (XVI, 314 p. 246 illus., 63 illus. in color.) 3-319-55894-3 Includes bibliographical references and index.Preface -- Meta-Analysis in a Nutshell -- Mathematical Fram-ework -- Meta-Analysis and the Scientific Method -- Meta-Analysis and Random Effects Analysis -- Meta-Analysis Software Programs -- Meta-Analysis of Randomized Controlled Trials -- Meta-Analysis of Observational plus Randomized Studies -- Meta-Analysis of Observational Studies -- Meta-Regression -- Meta-Analysis of Diagnostic Studies -- Meta-Meta-Analyses -- Network Meta-Analysis -- Random Intercepts Meta-Analysis -- Probit Regression -- Meta-Analysis with General Loglinear Models -- Meta-Analysis with Variance Components -- Ensembled Correlation Coefficients -- Ensembled Accuracies -- Meta-Analyses with Multivariate Assessments -- Transforming Odds Ratios into Correlation Coefficients -- Meta-Analyses with Direct and Indirect Comparisons -- Contrast Coefficients Meta-Analysis -- Meta-Analysis with Evolutionary Operations.-.Modern meta-analyses do more than combine the effect sizes of a series of similar studies. Meta-analyses are currently increasingly applied for any analysis beyond the primary analysis of studies, and for the analysis of big data. This 26-chapter book was written for nonmathematical professionals of medical and health care, in the first place, but, in addition, for anyone involved in any field involving scientific research. The authors have published over twenty innovative meta-analyses from the turn of the century till now. This edition will review the current state of the art, and will use for that purpose the methodological aspects of the authors' own publications, in addition to other relevant methodological issues from the literature. Are there alternative works in the field? Yes, there are, particularly in the field of psychology. Psychologists have invented meta-analyses in 1970, and have continuously updated methodologies. Although very interesting, their work, just like the whole discipline of psychology, is rather explorative in nature, and so is their focus to meta-analysis. Then, there is the field of epidemiologists. Many of them are from the school of angry young men, who publish shocking news all the time, and JAMA and other publishers are happy to publish it. The reality is, of course, that things are usually not as bad as they seem. Finally, some textbooks, written by professional statisticians, tend to use software programs with miserable menu programs and requiring lots of syntax to be learnt. This is prohibitive to clinical and other health professionals. The current edition is the first textbook in the field of meta-analysis entirely written by two clinical scientists, and it consists of many data examples and step by step analyses, mostly from the authors' own clinical research. .MedicineMedicine/Public Health, generalhttps://scigraph.springernature.com/ontologies/product-market-codes/H00007Medicine.Medicine/Public Health, general.610.72Cleophas Ton Jauthttp://id.loc.gov/vocabulary/relators/aut472359Zwinderman Aeilko Hauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910254660003321Modern Meta-Analysis2519907UNINA