The proceedings contain 23 papers. The topics discussed include: on the usefulness of similarity based projection spaces for transfer learning;metric anomaly detection via asymmetric risk minimization;one shot similar...
ISBN:
(纸本)9783642244704
The proceedings contain 23 papers. The topics discussed include: on the usefulness of similarity based projection spaces for transfer learning;metric anomaly detection via asymmetric risk minimization;one shot similarity metric learning for action recognition;on a non-monotonicity effect of similarity measures;section-wise similarities for clustering and outlier detection of subjective sequential data;hybrid generative-discriminative nucleus classification of renal cell carcinoma;multi-task regularization of generative similarity models;a generative dyadic aspect model for evidence accumulation clustering;an information theoretic approach to learning generative graph prototypes;impact of the initialization in tree-based fast similarity search techniques;and multiple-instance learning with instance selection via dominant sets.
The proceedings contain 8 papers. The topics discussed include: towards multi-facet snippets for dataset search;towards employing semantic license annotations for sensor data profiling;miningmachine-readable knowledg...
The proceedings contain 8 papers. The topics discussed include: towards multi-facet snippets for dataset search;towards employing semantic license annotations for sensor data profiling;miningmachine-readable knowledge from structured web markup;using semantic domain-specific dataset profiles for data analytics;on the role of knowledge graphs in explainable AI;semantic web technologies for explainable machinelearning models: a literature review;towards automatic domain classification of LOV vocabularies;and semantic web technologies for explainable machinelearning models: a literature review.
All sciences, including astronomy, are now entering the era of information abundance. The, exponentially increasing volume and complexity of modern, data sets promises to transform the scientific practice, but also, p...
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ISBN:
(纸本)0769522556
All sciences, including astronomy, are now entering the era of information abundance. The, exponentially increasing volume and complexity of modern, data sets promises to transform the scientific practice, but also, poses a number of common technological challenges. The Virtual Observatory concept is the astronomical community's response to these challenges: it aims to harness the progress in information technology in the service of astronomy, and at the same time provide a valuable testbed for information technology and applied computer science. Challenges broadly fall into two categories: data handling (or "data farming"), including issues such as archives, intelligent storage, databases, interoperability, fast networks, etc., and datamining, data understanding, and knowledge discovery, which include issues such as automated clustering and classification, multivariate correlation searches, patternrecognition, visualization in highly hyperdimensional parameter spaces, etc., as well as various applications of machinelearning in these contexts. Such techniques are forming a methodological foundation for science with massive and complex data sets in general, and are likely to have a much broather impact on the modern society, commerce, information economy, security, etc. There is a powerful emerging synergy between the computationally enabled science and the science-driven computing, which will drive the progress in science, scholarship, and many other venues in the 21st century.
In this paper we investigate a trie-based APRIORI algorithm for mining frequent item sequences in a transactional database. We examine the datastructure, implementation and algorithmic features mainly focusing on tho...
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ISBN:
(纸本)1595932100
In this paper we investigate a trie-based APRIORI algorithm for mining frequent item sequences in a transactional database. We examine the datastructure, implementation and algorithmic features mainly focusing on those that also arise in frequent itemset mining. In our analysis we take into consideration modern processors' properties (memory hierarchies, prefetching, branch prediction, cache line size, etc.), in order to better understand the results of the experiments. Copyright 2005 ACM.
Ontology matching approaches have mostly worked on the schema level so far. With the advent of Linked Open data and the availability of a massive amount of instance information, instance-based approaches become possib...
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Ontology matching approaches have mostly worked on the schema level so far. With the advent of Linked Open data and the availability of a massive amount of instance information, instance-based approaches become possible. This position paper discusses approaches and challenges for using those instances as input for machinelearning algorithms, with a focus on rule learning algorithms, as a means for ontology matching.
The proceedings contain 147 papers. The topics discussed include: estimation of the common oscillation for phase locked matrix factorization;a general algorithm for calculating force histograms using vector data;on th...
ISBN:
(纸本)9789898425980
The proceedings contain 147 papers. The topics discussed include: estimation of the common oscillation for phase locked matrix factorization;a general algorithm for calculating force histograms using vector data;on the crossover operator for GA-based optimizers in sequential projection pursuit;a dynamic wrapper method for feature discretization and selection;generative embeddings based on rician mixtures - application to kernel-based discriminative classification of magnetic resonance images;clustering complex multimedia objects using an ensemble approach;the stepwise response refinement screener (SRRS) and its applications to analysis of factorial experiments;handling imprecise labels in feature selection with graph Laplacian;the interplay of statistical and structural patternrecognition from a machinelearning perspective;and context sensitive information: model validation by information theory.
The proceedings contain 147 papers. The topics discussed include: estimation of the common oscillation for phase locked matrix factorization;a general algorithm for calculating force histograms using vector data;on th...
ISBN:
(纸本)9789898425980
The proceedings contain 147 papers. The topics discussed include: estimation of the common oscillation for phase locked matrix factorization;a general algorithm for calculating force histograms using vector data;on the crossover operator for GA-based optimizers in sequential projection pursuit;a dynamic wrapper method for feature discretization and selection;generative embeddings based on rician mixtures - application to kernel-based discriminative classification of magnetic resonance images;clustering complex multimedia objects using an ensemble approach;the stepwise response refinement screener (SRRS) and its applications to analysis of factorial experiments;handling imprecise labels in feature selection with graph Laplacian;the interplay of statistical and structural patternrecognition from a machinelearning perspective;and context sensitive information: model validation by information theory.
In response to the construction requirements of electromagnetic interference monitoring equipment for substations, a high-speed data acquisition system with matching specifications is designed. LabVIEW language is emp...
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ISBN:
(纸本)9798400707032
In response to the construction requirements of electromagnetic interference monitoring equipment for substations, a high-speed data acquisition system with matching specifications is designed. LabVIEW language is employed to establish the upper computer data acquisition system. The principles of PXIe and Aurora transmission protocols, as well as the control characteristics of DDR3 SDRAM storage, are investigated. A human-machine interaction interface is provided to realize data acquisition, storage, various waveform displays, and data monitoring. Save the large capacity of real-time data to the PC. The system achieves an analog bandwidth of each channel >= 100MHz, synchronous continuous sampling rate >= 250MSa/s, total channel transmission rate >= 8GB/s, and continuous storage space >= 4TB. Practical operation demonstrates that the system's data acquisition process is stable and reliable, meeting the design requirements. This research has achieved a high-speed data acquisition function based on LabView and FPGA multi-channel signal synchronous acquisition system and delay acquisition function, which has certain application value and promotion space.
Assessing the lower limb motor states of stroke patients based on biosignals is very important in the field of medical rehabilitation, and the importance of finding effective physiological signal indicators and proces...
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ISBN:
(纸本)9798400707032
Assessing the lower limb motor states of stroke patients based on biosignals is very important in the field of medical rehabilitation, and the importance of finding effective physiological signal indicators and processing methods for patient rehabilitation training and evaluation is self-evident. In this paper, a CNN-SVM model is constructed based on the CNN classifier to classify the three motion states of the lower limbs of the subjects, and the method is verified in the WAY-EEG-GAL multimodal open dataset to have a better classification effect, and the experimental data are used to verify the effectiveness of the model classification. The results show that the CNN-SVM method proposed in this paper outperforms the CNN classification model for all three classifications on both the WAY-EEG-GAL dataset and the experimental data, with average accuracies of 86.60% and 95.43%, respectively. This study provides a theoretical basis for combining EEG and EMG signals to establish a BCI-based method for lower limb exercise rehabilitation.
The proceedings contain 54 papers. The topics discussed include: an intelligent approach for food recipe rating prediction using machinelearning;hardware implementation of IP-enabled wireless sensor network using 6Lo...
ISBN:
(纸本)9780738131771
The proceedings contain 54 papers. The topics discussed include: an intelligent approach for food recipe rating prediction using machinelearning;hardware implementation of IP-enabled wireless sensor network using 6LoWPAN;an efficient machinelearning-based approach for android v.11 ransomware detection;robotics to enhance the teaching and learning process;an efficient patternrecognition based method for drug-drug interaction diagnosis;enhancing the prediction of MERS-CoV survivability using stacking-based method;a new solution to the brain state permanency for brain-based authentication methods;towards efficient detection and crowd management for law enforcing agencies;and AI support marketing: understanding the customer journey towards the business development.
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