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检索条件"主题词=Algorithm Design And Analysis"

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Fast and Efficient Mining of Frequent and Maximal Periodic Patterns in Spatiotemporal Databases for Shifted Instances

Fast and Efficient Mining of Frequent and Maximal Periodic P...

引用

IEEE International Advance Computing Conference, IACC

作者： O. Obulesu A. Rama Mohan Reddy Research Scholar in CSE JNTUA Anantapuramu A.P. India Professor of CSE SVUCE Tirupati A.P. India

ISBN: (纸本)9781467382878

Mining frequent and maximal Periodic Patterns is the challenging task for the data scientists due to unstructured, dynamic and huge raw data generated from web. Big Data is a latest tendency used to examine the datasets from large, complex databases. Developers cannot supervise them through conventional algorithms or Knowledge discovery software tools. Big Data mining is the ability to extract valuable information either from these huge datasets or else streams of data, due to its three V's (Volume, Velocity, and Variety). The previous studies focus on how to find frequent patterns from large traffic and sensor data based applications. However, mining maximal and useful periodic patterns from spatiotemporal datasets is still an open research problem in weather conditions, Fraud recognition and forest fire prevention Applications. We propose two algorithms such as Enhanced Tree based pattern mining algorithm (ETMA) and Extended Frequent Pattern Mining algorithm (EFPMA, which generates all frequent and maximal periodic patterns from spatiotemporal databases. A novel framework is introduced to mine spatiotemporal patterns from Big Data. All Existing algorithms are fit in calculation of essential patterns, but more tedious if they apply for Big Data. The proposed framework and algorithms produce better results than UDDAG, STNR algorithms towards scalability and decreased run time compared to DBSCAN, ECLAT algorithms.

关键词： Data mining Big data algorithm design and analysis Databases Spatiotemporal phenomena Clustering algorithms Heuristic algorithms

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A new dual forward BSS based RLS (DFRLS) algorithm for speech enhancement

A new dual forward BSS based RLS (DFRLS) algorithm for speec...

引用

International Conference on Engineering & MIS (ICEMIS)

作者： Mohamed Djendi Rahima Henni Akila Sayoud University of Blida 1 Signal Processing and Image Laboratory (LATSI) Blida Algeria

ISBN: (纸本)9781509055807

This paper addresses the speech enhancement problem with adaptive filtering algorithms. We propose a new dual forward blind source separation (FBSS) algorithm based on the use of the recursive least square algorithm to update the cross-filters of the forward structure. This algorithm inherits the good characteristics of the combination between the FBSS and the good properties of the RLS algorithm. In this work, we propose to use the DFRLS algorithm in speech enhancement and acoustic noise reduction application. This proposed algorithm shows good characteristics in comparison with dual forward normalized least mean square (DFNLMS) algorithm is terms of various objective criteria as the segmental signal to noise ratio (SegSNR), the cepstral distance (CD), the system mismatch (SM) and the segmental mean square error (SegMSE).

关键词： Signal processing algorithms Speech Speech enhancement algorithm design and analysis Signal to noise ratio Blind source separation Convergence

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Fractality of Massive Graphs: Scalable analysis with Sketch-Based Box-Covering algorithm

Fractality of Massive Graphs: Scalable Analysis with Sketch-...

引用

IEEE International Conference on Data Mining (ICDM)

作者： Takuya Akiba Kenko Nakamura Taro Takaguchi Preferred Networks Inc. Recruit Communications Co. Ltd. National Institute of Information and Communications Technology

ISBN: (纸本)9781509054749

analysis and modeling of networked objects are fundamental pieces of modern data mining. Most real-world networks, from biological to social ones, are known to have common structural properties. These properties allow us to model the growth processes of networks and to develop useful algorithms. One remarkable example is the fractality of networks, which suggests the self-similar organization of global network structure. To determine the fractality of a network, we need to solve the so-called box-covering problem, where preceding algorithms are not feasible for large-scale networks. The lack of an efficient algorithm prevents us from investigating the fractal nature of large-scale networks. To overcome this issue, we propose a new box-covering algorithm based on recently emerging sketching techniques. We theoretically show that it works in near-linear time with a guarantee of solution accuracy. In experiments, we have confirmed that the algorithm enables us to study the fractality of million-scale networks for the first time. We have observed that its outputs are sufficiently accurate and that its time and space requirements are orders of magnitude smaller than those of previous algorithms.

关键词： Fractals algorithm design and analysis Approximation algorithms Greedy algorithms Data mining Biological system modeling

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A comprehensive trust-based item evaluation model for recommendation in social network

A comprehensive trust-based item evaluation model for recomm...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Laizhong Cui Peng Ou Nan Lu Guanjing Zhang College of Computer Science and Software Engineering Shenzhen University Shenzhen China E-Techco Information Technologies Co. Ltd Shenzhen China

ISBN: (纸本)9781509006809

With the rapid development of online social network, people tend to express opinions and obtain information in social network. Due to the overwhelming amount of data in social network, users resort to recommendation system to find appropriate services or items. However, most current recommendation systems rely on the user to calculate the item evaluation results, which has many limitations in the item evaluation. To solve these limitations on item evaluation in social network, we put forward a new trust-based item evaluation model (called CTDR), which integrates trust, domain inclination and item reputation in this paper. First, we use the similarity between users, interaction, as well as the reputation of the target user to introduce a new trust computation method. Second, we introduce the concept of domain inclination and combine the domain activity of user and domain popularity to calculate the domain inclination. Third, we make use of the favorable rate of an item to compute the item reputation. Through extensive experiments, we evaluate CTDR with the traditional collaborative filtering algorithm. The experimental results validate the effectiveness and performance of our trust-based item evaluation model.

关键词： Social network services Computational modeling Collaboration Computers algorithm design and analysis Heuristic algorithms Noise measurement

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A density-based algorithm for detecting anomalous trajectories

A density-based algorithm for detecting anomalous trajectori...

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International Conference on Microelectronics, Computing and Communications (MicroCom)

作者： Rajesh P. Barnwal S. Baride S. Majumder Soumya K. Ghosh Information Technology Group CSIR-Central Mechanical Engineering Research Institute Durgapur India School of Information Technology Indian Institute of Technology Kharagpur Kharagpur India

ISBN: (纸本)9781467366229

Fast growth of mobile sensing technologies, like GPS in smart phones, made capturing position data in the form of trajectories easy. But detecting anomalous trajectories, which are grossly different from remaining trajectories, is a major challenge in the surveillance domain and a big data problem. In the present work, a novel density-based method has been proposed and implemented for detection of anomalous trajectories. We introduced the concept of Hausdorff-neighborhood-trajectory, which makes our approach capable of handling border trajectory situations.

关键词： Trajectory Training Clustering algorithms Vehicles Detectors Detection algorithms algorithm design and analysis

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PLC-RED-based AQM algorithm in terminal communication access network

PLC-RED-based AQM algorithm in terminal communication access...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Qinghai Ou Zhe Zhang Wanqing Yang Bing Liu Yu Tian Zhao Liu Yaomu Tan Liangrui Tang State Grid Information&Telecommunication Group Co. LTD Beijing China State Grid Dalian Electric Power Supply Company Dalian China State Grid Jibei Information&Telecommunication Company Beijing China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing China

ISBN: (纸本)9781509040940

To develop intelligent power grid, it will undertake more businesses. People put forward higher requirements to communication process in power grid. As the increasingly needs of complex business in power terminal communication access network, this paper proposes a new AQM algorithm which based on differentiated services. This new algorithm calculates the average queue length and takes into account historical loss situation to predict the length of the buffer. And then changing the buffer length according to each queue buffer's idle condition. Simulation results show that this algorithm not only ensures high priority queue's QoS requirements, but also significantly improve the buffer utilization when congestion occurs.

关键词： Packet loss Business Quality of service Prediction algorithms algorithm design and analysis Power system stability

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Are We Asking the Right Questions to Grade Our Students In a Knowledge-State Space analysis?

Are We Asking the Right Questions to Grade Our Students In a...

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International Workshop on Technology for Education, T4E

作者： Rania Aboalela Javed Khan Department of Computer Science Kent State University

ISBN: (纸本)9781509061167

This research presents novel knowledge assessment analysis methods. We add a new parameter, which is the cognitive skill level, to the knowledge assessment. The cognitive skill levels refer to levels such as whether a student has acquired the concept at the level of understanding, applying, analyzing, evaluating, or creating. Identifying the cognitive skill level parameter of the concept in a knowledge domain provides an accurate measurement value to the assessment. In this attempt, we provide knowledge assessment analysis methods that help to design a proper test and that can measure exactly the covered knowledge of the course objective. The result of the assessment analysis is the concept states, which inform if a student has already learned, is ready to learn, or is not ready to learn a certain skill level.

关键词： algorithm design and analysis Taxonomy Computer science Education Conferences Extraterrestrial measurements Visualization

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On Competitive algorithms for Approximations of Top-k-Position Monitoring of Distributed Streams

On Competitive Algorithms for Approximations of Top-k-Positi...

引用

International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Alexander Mäcker Manuel Malatyali Friedhelm Meyer auf der Heide Heinz Nixdorf Institute & Computer Science Department Paderborn University Germany Universitat Paderborn Paderborn Nordrhein-Westfalen DE

ISBN: (纸本)9781509021413

Consider the continuous distributed monitoring model in which n distributed nodes, receiving individual data streams, are connected to a designated server. The server is asked to continuously monitor a function defined over the values observed across all streams while minimizing the communication. We study a variant in which the server is equipped with a broadcast channel and is supposed to keep track of an approximation of the set of nodes currently observing the k largest values. Such an approximate set is exact except for some imprecision in an -neighborhood of the k-th largest value. This approximation of the Top-k-Position Monitoring Problem is of interest in cases where marginal changes (e.g. due to noise) in observed values can be ignored so that monitoring an approximation is sufficient and can reduce communication. This paper extends our results from [6], where we have developed a filter-based online algorithm for the (exact) Top-k-Position Monitoring Problem. There we have presented a competitive analysis of our algorithm against an offline adversary that also is restricted to filter-based algorithms. Our new algorithms as well as their analyses use new methods. We analyze their competitiveness against adversaries that use both exact and approximate filter-based algorithms, and observe severe differences between the respective powers of these adversaries.

关键词： Servers Monitoring algorithm design and analysis Approximation algorithms Computational modeling Clustering algorithms Upper bound

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Expectation-maximization algorithm for topic modeling on big data streams

Expectation-maximization algorithm for topic modeling on big...

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IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)

作者： Walisa Romsaiyud School of Science and Technology Sukhothai Thammathirat Open University Pakkret Nonthaburi Thailand

ISBN: (纸本)9781509014972

Expectation-Maximization (EM) is typically used to compute maximum likelihood estimates given incomplete samples and estimated the parameters. We proposed a new algorithm for generating an extension Dynamic Topic Model (exDTM)-in a time-based manner and based on the distribution of documents topics on Spark. The proposed algorithm can be applied in clustering documents from data streams for threat cyberbullying detection of the collected datasets that continuously change over time. In particular, the algorithm includes two main methods. The first method introduces a clustering method rooted in content-based coded dialogues collected from several data sources. This method measures the centroid for each cluster with EM. The second method calculates the joint distribution of the latent variables of the documents for finding the posterior distribution, and generates a final model using a variational Bayesian inference over a sequential time. In this experiment, authentic datasets collected from year - 2010 to 2011 - using corpus-wide patterns of words-were analyzed and studied. In order to enhance the reliability and computation time, the methods were applied on real-life settings where cyberbullying features and user-based features had experienced.

关键词： Data models Computational modeling Sparks Clustering algorithms Heuristic algorithms algorithm design and analysis Probabilistic logic

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Real-time algorithm for the front-side-looking SAR

Real-time algorithm for the front-side-looking SAR

引用

International Radar Symposium (IRS)

作者： Kseniia Semenova Electronics Department National Aviation University Kyiv Ukraine

ISBN: (纸本)9781509025190

In this paper data processing algorithm for the front-side-looking synthetic aperture radar is proposed. This algorithm is based on the Least Square method and the spline model. The real-time algorithm is designed using filter having similar principle of construction as a Savitzky-Golay filter. The filter is designed with Altera DSP Builder using 16-bit elements.

关键词： Synthetic aperture radar Real-time systems Splines (mathematics) algorithm design and analysis Filtering algorithms Signal processing algorithms Digital signal processing

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