The following topics are dealt with: computationalintelligence security; computationalintelligence privacy; biomedical datamining; datamining planning; datamining algorithms; Web mining; data stream mining; seque...
The following topics are dealt with: computationalintelligence security; computationalintelligence privacy; biomedical datamining; datamining planning; datamining algorithms; Web mining; data stream mining; sequential datamining; near-duplicate detection; tree models; time series; earth science computationalintelligence; earth science statistics; earth science datamining; financial engineering and clinical free text analysis
The proceedings contain 46 papers. The topics discussed include: distinguishing defined concepts from prerequisite concepts in learning resources;trend cluster based compression of geographically distributed data stre...
ISBN:
(纸本)9781424499274
The proceedings contain 46 papers. The topics discussed include: distinguishing defined concepts from prerequisite concepts in learning resources;trend cluster based compression of geographically distributed data streams;about the analysis of time series with temporal association rule mining;generating materialized views using ant based approaches and information retrieval technologies;a GPU-based interactive bio-inspired visual clustering;discovering process models through relational disjunctive patterns mining;user-guided discovery of declarative process models;feature extraction for multi-label learning in the domain of email classification;link pattern prediction with tensor decomposition in multi-relational networks;using gaming strategies for attacker and defender in recommender systems;and empirical comparison of correlation measures and pruning levels in complex networks representing the global climate system.
The proceedings contain 44 papers. The topics discussed include: quantitative measurements of model interpretability for the analysis of spectral data;regularization and improved interpretation of linear data mappings...
ISBN:
(纸本)9781467358958
The proceedings contain 44 papers. The topics discussed include: quantitative measurements of model interpretability for the analysis of spectral data;regularization and improved interpretation of linear data mappings and adaptive distance measures;interpretable models from distributed data via merging of decision trees;machine learning of engineering diagnostic knowledge from unstructured verbatim text descriptions;kernel spectral clustering for predicting maintenance of industrial machines;how to extract meaningful shapes from noisy time-series subsequences?;a novel fuzzy classification to enhance software regression testing;ready-to-use activity recognition for smartphones;interpreting individual classifications;discovery of topological relations for spatial activity recognition;supervised novelty detection;and a two-step fast algorithm for the automated discovery of declarative workflows.
The proceedings contain 67 papers. The topics discussed include: clustering data over time using kernel spectral clustering with memory;agglomerative hierarchical kernel spectral data clustering;quantum clustering - a...
ISBN:
(纸本)9781479945191
The proceedings contain 67 papers. The topics discussed include: clustering data over time using kernel spectral clustering with memory;agglomerative hierarchical kernel spectral data clustering;quantum clustering - a novel method for text analysis;generalized information theoretic cluster validity indices for soft clusterings;a density-based clustering of the self-organizing map using graph cut;new bilinear formulation to semi-supervised classification based on kernel spectral clustering;convex multi-task relationship learning using hinge loss;precision-recall-optimization in learning vector quantization classifiers for improved medical classification systems;semi-supervised source extraction methodology for the nosological imaging of glioblastoma response to therapy;and relational data partitioning using evolutionary game theory.
The proceedings contain 110 papers. The topics discussed include: link analysis of incomplete relationship networks;validity of probabilistic rules;an efficient distance calculation method for uncertain objects;K2GA: ...
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ISBN:
(纸本)1424407052
The proceedings contain 110 papers. The topics discussed include: link analysis of incomplete relationship networks;validity of probabilistic rules;an efficient distance calculation method for uncertain objects;K2GA: heuristically guided evolution of Bayesian network structures from data;extracting borderline associations;selecting the right peer schools for AACSB accredition- a datamining application;structure prediction in temporal networks using frequent subgraphs;an analytical evaluation of objective measures behavior for generalized association rules;toward versatile and efficient meta-learning: knowledge representation and management in computationalintelligence;query-sensitive feature selection for lazy learners;comparison of classifiers efficiency on missing values recovering: application in a marketing database with massive missing data;manifold learning using growing locally linear embedding;and a novel complex-valued counterpropagation network.
The proceedings contain 57 papers. The topics discussed include: building ultra-low false alarm rate support vector classifier ensembles using random subspaces;collaborative filtering with fine-grained trust metric;as...
ISBN:
(纸本)9781424427659
The proceedings contain 57 papers. The topics discussed include: building ultra-low false alarm rate support vector classifier ensembles using random subspaces;collaborative filtering with fine-grained trust metric;assessing the influence probability between objects: a random walker approach;intelligent feature extraction and knowledge mining by multivariate analysis;efficient model selection for support vector machine with Gaussian Kernel function;a fault tolerant peer-to-peer distributed EM algorithm;a new hybrid method for Bayesian network learning With dependency constraints;a pillar algorithm for K-means optimization by distance maximization for initial centroid designation;an adaptive ensemble classifier for concept drifting stream;and missing traffic flow data prediction using least squares support vector machines in urban arterial streets.
The 2011 ieee symposium on computational intelligence and data mining (ieee CIDM 2011) is a forum for the presentation of recent results concerning computationalintelligence for data and process mining. The topics co...
The 2011 ieee symposium on computational intelligence and data mining (ieee CIDM 2011) is a forum for the presentation of recent results concerning computationalintelligence for data and process mining. The topics covered by the symposium include CI/probabilistic/statistical and other methods, mining spatial and temporal data, recognition and interpretation of images, text, graph and web mining, medical data analysis, process mining.
The proceedings contain 18 papers. The topics discussed include: sparse Bayesian approach for feature selection;sentiment analysis for various SNS media using naive Bayes classifier and its application to flaming dete...
ISBN:
(纸本)9781479945412
The proceedings contain 18 papers. The topics discussed include: sparse Bayesian approach for feature selection;sentiment analysis for various SNS media using naive Bayes classifier and its application to flaming detection;increasing big data front end processing efficiency via locality sensitive bloom filter for elderly healthcare;challenges in designing an online healthcare platform for personalised patient analytics;application of sparse matrix clustering with convex-adjusted dissimilarity matrix in an ambulatory hospital specialist service;microarray big data integrated analysis for the prediction of robust diagnostics signature for triple-negative breast cancer;mining the prescription-symptom regularity of TCM for HIV/AIDS based on complex network;regularity of herbal formulae for HIV/AIDS patients with syndromes based on complex networks;and methods and technologies of traditional Chinese medicine clinical information datamation in real world.
The era characterized by an exponential increase in data has led to the widespread adoption of dataintelligence as a crucial task. Within the field of datamining, frequent episode mining has emerged as an effective ...
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The era characterized by an exponential increase in data has led to the widespread adoption of dataintelligence as a crucial task. Within the field of datamining, frequent episode mining has emerged as an effective tool for extracting valuable and essential information from event sequences. Numerous algorithms have been developed to discover frequent episodes and subsequently derive episode rules based on the frequency function and anti-monotonicity principles. However, currently, there is a lack of algorithms specifically designed for mining episode rules that encompass user-specified query episodes. To address this challenge and enable the mining of target episode rules, we introduce the definition of targeted precise-positioning episode rules and formulate the problem of targeted mining precise-positioning episode rules. Most importantly, we develop an algorithm called Targeted mining Precision Episode Rules (TaMIPER) to address the problem and optimize it using four proposed strategies, leading to significant reductions in both time and space resource requirements. As a result, TaMIPER offers high accuracy and efficiency in mining episode rules of user interest and holds promising potential for prediction tasks in various domains, such as weather observation, network intrusion, and e-commerce. Experimental results on six real datasets demonstrate the exceptional performance of TaMIPER.
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