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3rd international conference on advances in Information Systems, ADVIS 2004

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3rd international conference on advances in Information Systems, ADVIS 2004

ISBN: (纸本)9783540234784

The proceedings contain 61 papers. The special focus in this conference is on advances in Information Systems. The topics include: Temporality in databases;a data warehouse engineering process;aggregation and analysis of spatial data by means of materialized aggregation tree;an object-oriented framework for reconciliation and extraction in heterogeneous data federations;on optimising data access via materialised methods in object-oriented systems;some modifications of bucket-based algorithms for query rewriting using views;a data mining application on air temperature database;incremental association rule mining using materialized data mining views;outlier effects on databases;finding maximal similar paths between XML documents using sequential patterns;the construction of domain ontology and its application to document retrieval;towards building knowledge centres on the world wide web;navigation modelling from a user services oriented approach;adaptive architecture for web server survivability;integration and maintenance of heterogeneous applications and data structures;a component language for hybrid solver cooperations;non-interleaved quadtree node codification;parameterized formatting of an XML document by XSL rules;a middleware approach to storing and querying XML documents in relational databases;text summarization and singular value decomposition;sentence boundary detection in turkish;multiple sets of rules for text categorization;letter based text scoring method for language identification;a distributed model of neuronal regulators based on message-driven software component architecture;integrating distributed composite objects into java environment and a study on grid partition for declustering high-dimensional data.

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New Frontiers in Applied data Mining 2012

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丛书名： Lecture Notes in Computer Science

2012年

作者： Longbing Cao Joshua Zhexue Huang James Bailey Yun Sing Koh Jun Luo

ISBN: (数字)9783642283208

ISBN: (纸本)9783642283192

This book constitutes the thoroughly refereed post-conference proceedings of five international workshops held in conjunction with PAKDD 2011 in Shenzhen, China, in May 2011: the international Workshop on Behavior Informatics (BI 2011), the Workshop on Quality Issues, Measures of Interestingness and Evaluation of data Mining Models (QIMIE 2011), the Workshop on Biologically Inspired Techniques for data Mining (BDM 2011), the Workshop on advances and Issues in Traditional Chinese Medicine Clinical data Mining (AI-TCM 2011), and the Second Workshop on data Mining for Healthcare Management (DMGHM 2011). The book also includes papers from the First PAKDD Doctoral Symposium on data Mining (DSDM 2011). The42 papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics discussing emerging techniques in the field of knowledge discovery in databases and their application domains extending to previously unexplored areas such as data mining based on optimization techniques from biological behavior of animals and applications in Traditional Chinese Medicine clinical research and health care management.

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Scalable P2P Reconciliation Infrastructure for Collaborative Text Editing

Scalable P2P Reconciliation Infrastructure for Collaborative...

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international conference on advances in databases, knowledge, and data applications, dbkda

作者： Mounir Tlili Reza Akbarinia Esther Pacitti Patrick Valduriez INRIA-LINA Nantes France INRIA-LIRMM Montpellier France

ISBN: (纸本)9781424460816

We address the problem of optimistic replication for collaborative text editing in Peer-to-Peer (P2P) systems. This problem is challenging because of concurrent updating at multiple peers and dynamic behavior of peers. Operational transformation (OT) is a typical approach used for handling optimistic replication in the context of distributed text editing. However, most of OT solutions are neither scalable nor suited for P2P networks due to the dynamic behavior of peers. In this paper, we propose a scalable P2P reconciliation infrastructure for OT that assures eventual consistency and liveness despite dynamicity and failures. We propose a P2P logging and timestamping service called P2P-LTR (P2P Logging and Timestamping for Reconciliation) which exploits a distributed hash table (DHT) for reconciliation. While updating replica copies at collaborating peer editors, updates are stored in a highly available P2P log. To enforce eventual consistency, these updates must be retrieved in a specific total order to be reconciled at the peer editors. P2P-LTR provides an efficient mechanism for determining the total order of updates. It also deals with the case of peers that may join and leave the system during the update operation. We evaluated the performance of P2P-LTR through simulation; the results show the efficiency and the scalability of our solution.

关键词： Collaborative work Scalability Peer to peer computing databases international collaboration Fault tolerant systems Large-scale systems Buildings Fault tolerance Network servers

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data preprocessing using intelligent agents

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1st international conference on Frontiers in Intelligent Computing: Theory and applications, FICTA 2012

作者： Christa, Sharon Suma, V. Madhuri, Lakshmi Department of Information Science and Engineering Dayananda Sagar College of Engineering Bangalore India Research and Industry Incubation Centre Dayananda Sagar College of Engineering Bangalore India

ISBN: (纸本)9783642353130

knowledge discovery in data base aims to analyze the databases for meaningful patterns and information regarding the same. data mining is the process in KDD that identifies patterns and knowledge from various sources of database or even from different database. Even though data mining has a very significant role in the real world, the mining of data in the database does not yield correct results due to various real world problems like data inconsistencies. There comes the significance of data preprocessing where the inconsistencies of data is removed. This paper provides the design and development of intelligent software that uses agent based data preprocessing environment to improve the data processing activities, which in turn enhances the quality of data to be mined. © 2013 Springer-Verlag.

关键词： database systems

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Hybrid Technique Based on DBSCAN for Selection of Improved Features for Intrusion Detection System

Hybrid Technique Based on DBSCAN for Selection of Improved F...

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international conference on Emerging Trends in Expert applications and Security (ICETEAS)

作者： Saxena, Akash Saxena, Khushboo Goyal, Jayanti Compucom Inst Informat Technol & Management Dept Comp Sci & Engn Jaipur Rajasthan India Oriental Inst Sci & Technol Dept Comp Sci & Engn Bhopal India Kanoria PG Mahila Mahavidyalaya Jaipur Rajasthan India

ISBN: (纸本)9789811322853;9789811322846

data mining is the taking out of concealed data from enormous databases (DBs);it is an effective innovation with unusual probable to enable associations to deliberate on the mainly imperative data in their data warehouses. IDS are the chief issue of the security which is helpful in everyday life to avoid the data from the attackers. data mining includes numerous methods for the detection of intrusion which involves the detection of all harmful activities. In our proposed work, we initially apply KDD cup'99 dataset which is most broadly used method for detecting intrusion. DBSCAN is the most utilized method which is used to eliminate noise from the data. Then, we generate the most meaning inputs by analyzing and processing whole data which is done by the selection of feature method. K-means clustering performs grouping of data which is followed by SMO classifier. So we proposed a hybrid structure which improves the taken as a whole accuracy. MATLAB and WEKA tools are used to execute the whole process.

关键词： data mining knowledge discovery database Machine learning SVM K-means

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FedGait: A Benchmark for Federated Gait Recognition 26

FedGait: A Benchmark for Federated Gait Recognition

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26th international conference on Pattern Recognition / 8th international Workshop on Image Mining - Theory and applications (IMTA)

作者： Li, Ziqiong Li, Yan-ran Yu, Shiqi Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen Peoples R China Southern Univ Sci & Technol Dept Comp Sci & Engn Shenzhen Peoples R China

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Gait recognition has been greatly improved by deep learning and can achieve a relative high accuracy. The advances depend on the data size of gait. However, due to public concerns on privacy and regulations and laws from different countries, it is very difficult and almost impossible to collect a huge centralized gait database for algorithm training. Federated learning is a distributed machine learning technique for privacy-preserving, and can help to solve the problem. We propose a federated gait recognition benchmark, FedGait, to train algorithms using distributed gait data. It is the first benchmark on gait recognition to the best of our knowledge. FedGait can utilizes the gait videos available on multiple clients to learn a robust and generalized model. Based on the real-world gait scenarios, we introduce two federated gait recognition scenarios: institution-based scenario (IBS) and device-based scenario (DBS). Compared with centralized training, federated learning will encounter more serious heterogeneous data and data imbalance problems. We employ four popular databases for experiments, CASIA-B, CASIA-E, ReSGait and OU-MVLP, are involved in FedGait to investigate the problems in federated learning. We hope FedGait is a good start to solve data privacy problem in gait recognition.

关键词： Training Privacy data privacy Machine learning algorithms Federated learning Satellite broadcasting Benchmark testing

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Anomalies detection in mobile network management data

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12th international conference on database Systems for Advanced applications

作者： Anisetti, Marco Ardagna, Claudio A. Bellandi, Valerio Bernardoni, Elisa Damiani, Ernesto Reale, Salvatore Univ Milan Dept Informat Technol Via Bramante65 I-26013 Crema Italy Carrier Res Dev Radio Access Network Management Milan 20092 Italy

ISBN: (纸本)9783540717027

Third generation (3G) mobile networks rely on distributed architectures where Operation and Maintenance Centers handle a large amount of information about network behavior. Such data can be processed to extract higher-level knowledge, useful for network management and optimization. In this paper we apply reduction techniques, such as Principal Component Analysis, to identify orthogonal subspaces representing the more interesting data contributing to overall variance and to split them up in "normal" and "anomalous" subspaces. Patterns within anomalous subspaces allow for early detection of network anomalies, improving mobile networks management and reducing the risk of malfunctioning.

关键词： Network security

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advances in databases and Information Systems 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Johann Eder Maria Bielikova A Min Tjoa

ISBN: (数字)9783642237379

ISBN: (纸本)9783642237362

This book constitutes the refereed proceedings of the 15th international conference on advances in databases and Information Systems, ADBIS 2011, held in Vienna, Austria, in September 2011. The 30 revised full papers presented together with 2 full length invited talks were carefully reviewed and selected from 105 submissions. They are organized in topical sections on query processing; data warehousing; DB systems; spatial data; information systems; physical DB design; evolution, integrity, security; and data semantics.

关键词： database Management Information Systems applications (incl. Internet) Information Storage and Retrieval Computer Communication Networks data Mining and knowledge Discovery Management of Computing and Information Systems

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advances in databases and Information Systems 1

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丛书名： Lecture Notes in Computer Science

1000年

ISBN: (数字)9783540857136

ISBN: (纸本)9783540857129

This volume contains the best papers presented at the 12th East-European conference on advances in databases and Information Systems (ADBIS 2008) held during S- tember 5–9, 2008, in Pori, Finland. The series of ADBIS conferences is the successor of the annual international workshops with the same title that during 1993-1996 were organized in Russia by the Moscow ACM SIGMOD Chapter. ADBIS 2008 continues the series of ADBIS conferences held in St. Petersburg, Russia (1997), Poznan, Poland (1998), Maribor, Slovenia (1999), Prague, Czech Republic (2000), Vilnius, Lithuania (2001), Bratislava, Slovakia (2002), Dresden, Germany (2003), Budapest, Hungary (2004), Tallinn, Estonia (2005), Thessaloniki, Greece (2006), and Varna, Bulgaria (2007). The conferences are initiated and supervised by an international Steering Committee chaired by professor Leonid Kalinichenko. The ADBIS conferences established an outstanding reputation as a scientific event of high quality serving as an internationally highly visible showcase for research achie- ments in the field of databases and information systems. ADBIS 2008 aimed to create conditions for experienced researchers to impart their knowledge and experience to the young researchers at pre- or post-doctoral level, and to promote interaction and colla- ration between European research communities (especially from Central and East Europe) and the rest of the world. The conference encourages contacts between the p- ticipants who are nationals of, but active outside, the Member States and Associated States and their colleagues in Member States and Associated States. Special attention is paid to collaboration of researchers in Central and East Europe.

关键词： data Structures and Information Theory database Management Information Systems applications (incl. Internet) data Mining and knowledge Discovery Information Storage and Retrieval Multimedia Information Systems

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10th international conference on Practical applications of Computational Biology & Bioinformatics 1st ed. 2016

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丛书名： advances in Intelligent Systems and Computing

2016年

作者： Mohd Saberi Mohamad Miguel P. Rocha Florentino Fdez-Riverola Francisco J. Domínguez Mayo Juan F. De Paz

ISBN: (数字)9783319401263

ISBN: (纸本)9783319401256

Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as databases, Statistics, data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. PACBB16 hopes to contribute to this effort promoting this fruitful interaction. PACBB'16 technical program included 21 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Therefore, the conference will certainly promote the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists). The scientific content will certainly be challenging and will promote the improvement of the work being developed by each of the participants.

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