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7th international conference on Similarity Search and Applications, SISAP 2014

ISBN: (纸本)9783319119878

the proceedings contain 29 papers. the special focus in this conference is on technological problems shared by many application domains, such as data mining, information retrieval, computer vision, pattern recognition, computational biology, geography, biometrics and machine learning. the topics include: Efficient algorithms for similarity search in axis-aligned subspaces;partial refinement for similarity search with multiple features;video retrieval with feature signature sketches;metric space searching based on random bisectors and binary fingerprints;faster proximity searching with the distal SAT;a dynamic pivoting algorithm based on spatial approximation indexes;large-scale distributed locality-sensitive hashing for general metric data;dynamic list of clusters in secondary memory;index-based r-s similarity joins;a compressed index for hamming distances;perils of combining parallel distance computations with metric and Ptolemaic indexing in kNN queries;transition-sensitive distances;retrieval of binary features in image databases;the similarity-aware relational intersect database operator;high dimensional search using polyhedral query;generating synthetic data to allow learning from a single exemplar per class;similarity for natural semantic networks;anomaly detection in streaming time series based on bounding boxes;SVG-to-RDF image semantization;employing similarity methods for stellar spectra classification in astroinformatics;a similarity-based method for visual search in time series using Coulomb’s law;classification of epileptoid oscillations in EEG Using Shannon’s entropy amplitude probability distribution;entity recognition for duplicate filtering;a Bayesian ensemble classifier for source code authorship attribution;multi-core (CPU and GPU) for permutation-based indexing and an efficient DTW-based approach for melodic similarity in flamenco singing.

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Education Quality measured by the classification of school performance using Quality Labels 4

Education Quality measured by the classification of school p...

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4th international conference on Applied Mechanics, Materials and Manufacturing (ICAMMM)

作者： Teixeira Goes, Anderson Roges Arns Steiner, Maria Teresinha Steiner Neto, Pedro Jose Fed Univ Parana UFPR Grad Program Numer Methods Engn Curitiba Parana Brazil Pontif Catholic Univ Parana PUCPR Polytechn Sch Grad Program Ind Engn & Syst PPGEPS Curitiba Parana Brazil

ISBN: (纸本)9783038352884

Quality in education has been the subject of many debates, be it among managers in schools, in the media or in literature. However, the literature appears not to include methods or techniques for exploring databases to obtain classifications for this quality;nor is there a consensus as to the definition of "education quality". To address these issues, this article proposes a methodology similar to the KDD (Knowledge Discovery in databases) to classify Education Quality in schools comparatively, based on grades scored in school performance tests. For the purposes of this study, the test used was the Prova Brasil examination, which is part of the Basic Education Development Index (IDEB) used in Brazil. the methodology was applied to public municipal schools in the town of Araucaria in the metropolitan district of Curitiba in Parani State. Seventeen schools that offer elementary and junior high school education were included. All the grades of every student were considered from the early and later years at the schools. During the data mining stage, the main stage of the KDD process, three comparative methods were used for pattern recognition: Artificial Neural Networks, Support Vector machines and Genetic Algorithms. these methods supplied satisfactory results in the classification of schools represented by way of a "Quality Label", with Artificial Neural Networks having the best performance for the problem in question. With this quality label, educational managers can decide on which measures to adopt at all the schools to help them achieve their goals.

关键词： Education Quality KDD Process pattern recognition Real Case Study

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Tool support for detection and analysis of following and leadership behavior of pedestrians from mobile sensing data

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PERVASIVE AND MOBILE COMPUTING 2014年第PartA期10卷 104-117页

作者： Kjaergaard, Mikkel Baun Blunck, Henrik Aarhus Univ Dept Comp Sci DK-8000 Aarhus C Denmark

the vast availability of mobile phones with built-in movement and location sensors enables the collection of detailed information about human movement even indoors. As mobility is a key element of many processes and activities, an interesting class of information to extract is movement patterns that quantify how humans move, interact and group. In this paper we propose methods for detecting two common pedestrian movement patterns, namely individual following relations and group leadership. the proposed methods for identifying following patterns employ machine learning on features derived using similarity analysis on time-lagged sequences of WiFi measurements containing either raw signal strength values or derived locations. To detect leadership we combine the individual following relations into directed graphs and detect leadership within groups by graph link analysis. Methods for detecting these movement patterns open up new possibilities in - amongst others - computational social science, reality mining, marketing research and location-based gaming. We provide evaluation results that show error rates down to 7%, improving over state-of-the-art methods with up to eleven percentage points for following patterns and up to twenty percentage points for leadership patterns. Furthermore, we provide an analysis of the computational efficiency of the proposed methods and present visualizations for the analysis of detected patterns. Our methods are, contrary to state of the art, also applicable in challenging indoor environments, e.g., multi-story buildings. this implies that even quite small samples allow us to detect information such as how events and campaigns in multi-story shopping malls may trigger following in small groups, or which group members typically take the lead when triggered by e.g. commercials, or how rescue or police forces act during training exercises. (C) 2013 Elsevier B.V. All rights reserved.

关键词： pattern recognition Crowd behavior sensing Mobile sensing Signal-strength-based methods

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Tabu search for dynamic time warping global constraint learning

Tabu search for dynamic time warping global constraint learn...

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international conference of Soft Computing and pattern recognition (SOCPAR)

作者： Bilel Ben Ali Youssef Masmoudi Souhail Dhouib LOGIQ Research Unit University of Sfax Tunisia High School of Commerce University of Sfax Tunisia AL-Baha University Arabie Saoudite

Measuring similarity or distance between two data points is fundamental to many machine learning algorithms such as K-Nearest-Neighbor, Clustering etc. Depending on the nature of the data point, various measurements can be used. DTW is largely used for mining time series but it is not adopted to large data sets because of its quadratic complexity. Global constraints narrow the search path in the matrix which results in a significant decrease in the number of performed calculations. the distance between examples from the same class is small. Instances from different classes are with large distances. A field called metric learning is introduced to make such criteria. In some time series classification tasks, it is a common case that two time series are out of phase, even they share the same class label. An appropriate constraint of DTW can strongly improve the classification performance. It is to choose the appropriate size of the global constraint. A Tabu search algorithm is used to find the optimal size of the global constraint. Results show the efficiency of the proposed method in terms of the improvement of the classification results and the CPU time.

关键词： Time series analysis Euclidean distance Accuracy Equations Heuristic algorithms Educational institutions

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Tool support for detection and analysis of following and leadership behavior of pedestrians from mobile sensing data

Tool support for detection and analysis of following and lea...

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11th Annual IEEE international conference on Pervasive Computing and Communications (PerCom)

作者： Kjaergaard, Mikkel Baun Blunck, Henrik Aarhus Univ Dept Comp Sci DK-8000 Aarhus C Denmark

关键词： pattern recognition Crowd behavior sensing Mobile sensing Signal-strength-based methods

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Text Document Preprocessing and Dimension Reduction Techniques for Text Document Clustering

Text Document Preprocessing and Dimension Reduction Techniqu...

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Artificial Intelligence with Applications in Engineering and Technology (ICAIET)

作者： Ammar Ismael Kadhim Yu-N Cheah Nurul Hashimah Ahamed Department of Computer Science College of Medicine Baghdad Iraq School of Computer Sciences Universiti Sains Malaysia Penang Malaysia Universiti Sains Malaysia Minden Pulau Pinang MY

Text mining defines generally the process of extracting interesting features (non-trivial) and knowledge from unstructured text documents. Text mining is an interdisciplinary field which depends on information retrieval, data mining, machine learning, parameter statistics and computational linguistics. Standard text mining and retrieval information techniques of text document usually rely on similar categories. An alternative method of retrieving information is clustering documents to preprocess text. the preprocessing steps have a huge effect on the success to extract knowledge. this study implements TF-IDF and singular value decomposition (SVD) dimensionality reduction techniques. the proposed system presents an effective preprocessing and dimensionality reduction techniques which help the document clustering by using k-means algorithm. Finally, the experimental results show that the proposed method enhances the performance of English text document clustering. Simulation results on BBC news and BBC sport datasets show the superiority of the proposed algorithm.

关键词： Clustering algorithms Text mining Algorithm design and analysis data models Singular value decomposition Indexing

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Multi-modal pipeline for comprehensive validation of Mitral Valve geometry and functional computational models

Multi-modal pipeline for comprehensive validation of Mitral ...

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4th international Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, STACOM 2013, Held in Conjunction with MICCAI 2013

作者： Neumann, Dominik Grbic, Sasa Mansi, Tommaso Voigt, Ingmar Rabbah, Jean-Pierre Siefert, Andrew W. Saikrishnan, Neelakantan Yoganathan, Ajit P. Yuh, David D. Ionasec, Razvan Ioan Imaging and Computer Vision Siemens Corporate Technology Princeton NJ United States Pattern Recognition Lab. University of Erlangen-Nuremberg Germany Computer Aided Medical Procedures Technical University Munich Germany Wallace H. Coulter Department of Biomedical Engineering Georgia Institute of Technology Emory University Atlanta GA United States Section of Cardiac Surgery Department of Surgery Yale University New Haven CT United States

ISBN: (纸本)9783642542671

Valvular heart disease affects a high number of patients, exhibiting significant mortality and morbidity rates. Mitral Valve (MV) Regurgitation, a disorder in which the MV does not close properly during systole, is among its most common forms. Traditionally, it has been treated with MV replacement. However, recently there is an increased interest in MV repair procedures, providing better long-term survival, better preservation of heart function, lower risk of complications, and usually eliminating the need for long-term use of blood thinners (anticoagulants). these procedures are complex and require an experienced surgeon and elaborate pre-operative planning. Hence, there is a need for efficient tools for training and planning of MV repair interventions. Computational models of valve function have been developed for these purposes. Nevertheless, state-of-the-art models remain approximations of real anatomy with considerable simplifications, since current modalities are limited by image quality. Hence, there is an important need to validate such low-fidelity models against comprehensive ex-vivo data to assess their clinical applicability. As a first step towards this aim, we propose an integrated pipeline for the validation of MV geometry and function models estimated in ex-vivo TEE data with respect to ex-vivo microCT data. We utilize a controlled experimental setup for ex-vivo imaging and employ robust machine learning and optimization techniques to extract reproducible geometrical models from both modalities. Using one exemplary case, we demonstrate the validity of our framework. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Pipelines

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machine learning based biomedical named entity recognition 4

Machine learning based biomedical named entity recognition

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IET Chennai 4th international conference on Sustainable Energy and Intelligent Systems, SEISCON 2013

作者： Kanya, N. Ravi, T. Manonmanium Sundaranar University TN India Srinivasa Institute of Engineering and Technology TN India

ISBN: (纸本)9781785610301

the biomedical society makes wide use of text mining technology. Named Entity (NE) extraction is one of the most primary and significant tasks in biomedical information extraction of text mining technology. Named Entity recognition (NER) involves processing structured and unstructured documents to recognize the definite kinds of entities and categorization of them into some predefined classes. Several Named Entity recognition systems have been developed for the Biomedical Domain based on the Rule-Based, Dictionary based and machine learning based techniques. Implementing the best approach is not possible in all domains. machine learning based approaches have many advantages than other approaches. In this paper we are proposing a machine learning based framework for recognizing named entities from biomedical abstracts. For this study we used benchmarked datasets such as GENETAG and JNLPBA.

关键词： data mining

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A study on mammography computer aided diagnosis system using machine learning methods 4

A study on mammography computer aided diagnosis system using...

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IET Chennai 4th international conference on Sustainable Energy and Intelligent Systems, SEISCON 2013

作者： Dinakaran, K. Sivakrithika, V. Department of CSE RMD Engineering College India Department of CSE TRP Engineering College India

ISBN: (纸本)9781785610301

Early diagnosis is an important aspect of successful treatment for breast cancer. Mammogram is the most reliable imaging technique available. It is a challenging task for radiologists to detect the abnormalities in the mammograms. Computing helps the radiologists in diagnosing the abnormalities in the mammogram. Computer Aided Diagnosis System involves computerized biomedical image analysis to classify the mammography into benign or malign. In a decade of research work number of algorithms had been proposed to classify the image that employ data mining techniques, image processing methods, machine learning methods and pattern recognition. In this paper such algorithms in previous research work is studied and their performance is discussed.

关键词： Computer aided diagnosis

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Implementation of General Motion recognition Library for Smart Devices

Implementation of General Motion Recognition Library for Sma...

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4th international conference on Information Science and Applications (ICISA)

作者： Kim, Taewoo Kim, Suna Kim, Yoonkyung Kim, Chulyun Gachon Univ Dept Software Design & Management Songnam South Korea

ISBN: (纸本)9781479906048;9781479906024

Apple's iPhone has opened the market of various smart devices and changed the way of computing in daily life. In traditional PCs, mouse and keyboard are representative input devices, but, in smart devices, touch screen and motion recognition become major input methods. Especially, in game applications, motion recognition is more important to dynamically interact with users. In this paper, we propose a library of motion recognition for general interactive applications on smart devices. the proposed library provides the functions of registering motions in the development phase and recognizing a real-time motion in the running phase. By using the proposed library, any application can create and register its customized motions and recognize user's real-time motion from the registered motions in the common interface.

关键词： motion recognition pattern matching data mining

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