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knowledge Discovery Using Big data in Biomedical Systems

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2015年第4期12卷 726-728页

作者： Janga, Sarath Chandra Zhu, Dongxiao Chen, Jake Y. Zaki, Mohammed J. Indiana Univ Purdue Univ Sch Informat & Comp Dept Biohlth Informat Indianapolis IN 46202 USA Indiana Univ Sch Med Ctr Computat Biol & Bioinformat Indianapolis IN 46202 USA Wayne State Univ Dept Comp Sci Detroit MI 48202 USA Rensselaer Polytech Inst Dept Comp Sci Troy NY 12180 USA

the papers in this special section were presented at the 13th International Workshop on data mining in Bioinformatics (BIOKDD’14) was organized in conjunction with the ACM SIGKDD International conference on knowledge Discovery and data mining that was held on August 24, 2014 in New York, NY. It brought together international researchers in the interacting disciplines of data mining, systems biology, and bioinformatics at the Bloomberg Headquarters venue. the goal of this workshop is to encourage knowledge Discovery and data mining (KDD) researchers to take on the numerous challenges that Bioinformatics offers.

关键词： Special Issues And Sections Bioinformatics data mining knowledge Discovery Systems Biology Meetings

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An Efficient Candidate Pruning Technique for High Utility Pattern mining

An Efficient Candidate Pruning Technique for High Utility Pa...

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13th pacific-asia conference on knowledge Discovery and data mining

作者： Ahmed, Chowdhury Farhan Tanbeer, Syed Khairuzzaman Jeong, Byeong-Soo Lee, Young-Koo Kyung Hee Univ Dept Comp Engn Youngin Si 446701 Kyunggi Do South Korea

ISBN: (纸本)9783642013065

High utility pattern mining extracts more useful and realistic knowledge from transaction databases compared to the traditional frequent pattern mining by considering the non-binary frequency values of items in transactions and different profit values for every item. However, the existing high utility pattern mining algorithms suffer from the level-wise candidate generation-and-test problem and need several database scans to mine the actual high utility patterns. In this paper, we propose a novel tree-based candidate priming technique HUC-Prime (high utility candidates prune) to efficiently mine high utility patterns without level-wise candidate generation-and-test. It exploits a pattern growth mining approach and needs maximum three database scans in contrast to several database scans of the existing algorithms. Extensive experimental results show that our technique is very efficient for high utility pattern mining and it outperforms the existing algorithms.

关键词： data mining knowledge discovery frequent pattern mining high utility pattern mining association rules

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InCoB2014: bioinformatics to tackle the data to knowledge challenge

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BMC BIOINFORMATICS 2014年第16期15卷 1-3页

作者： Ranganathan, Shoba Tan, Tin Wee Schoenbach, Christian Macquarie Univ Dept Chem & Biomol Sci Sydney NSW 2109 Australia Macquarie Univ ARC Ctr Excellence Bioinformat Sydney NSW 2109 Australia Natl Univ Singapore Yong Loo Lin Sch Med Dept Biochem Singapore 117599 Singapore Nazarbayev Univ Sch Sci & Technol Dept Biol Astana 010000 Kazakhstan Kumamoto Univ Ctr AIDS Res Kumamoto 8600811 Japan

Since 2006, the International conference on Bioinformatics (InCoB) has been publishing selected papers in BMC Bioinformatics. Papers within the scope of the journal from the 13th InCoB July 31-2 August, 2014 in Sydney, Australia have been compiled in this supplement. these span protein and proteome informatics, structural bioinformatics, software development and bioimaging to pharmacoinformatics and disease informatics, representing the breadth of bioinformatics research in the asia-pacific.

关键词： Bioinformatics

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Solving Smart City Revitalisation Problems With Geoparticipation Process and Fuzzy Methods 13

Solving Smart City Revitalisation Problems With Geoparticipa...

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13th International conference on Natural Computation, Fuzzy Systems and knowledge Discovery (ICNC-FSKD)

作者： Olszewski, Robert Trojanowska, Hanna Turek, Agnieszka Kietlinska, Bogna Warsaw Univ Technol Fac Geodesy & Cartog Warsaw Poland Univ Warsaw Inst Appl Social Sci Warsaw Poland

ISBN: (纸本)9781538621653

the paper presents an exceptionally simple method that allows a researcher to find out the interpretation of the complicated revitalization processes on the bases of the collected data. It employs spatial data mining and fuzzy inference system. thanks to building the FIS knowledge base and selecting the fuzzy rules, it is possible to point out the important factors that influence the process that is being the subject of the research. In this paper this is the dialogue between Polish local governments and their residents to solve the problem of urban revitalization in the context of smart city creation. Keywords-spatial data mining

关键词： spatial data mining FIS smart city revitalisation geoparticipation citizens urban planning

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Computation rotating for data reuse

Computation rotating for data reuse

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13th IEEE asia-pacific Computer Systems Architecture conference, ACSAC 2008

作者： Guiming, Wu Jinhui, Xu Yong, Dou Miao, Wang School of Computer National University of Defense Technology Changsha Hunan 410073 China

ISBN: (纸本)9781424426836

Loop tiling is an effective loop transformation technique that tiles the iteration space of loop nests to improve the data locality. the appropriate data layout and transfer strategies are also important to assist loop tiling. this paper describes an approach to enhance data reuse and reduce off-chip memory access after loop tiling. data tiles due to loop tiling may have overlapped elements, which will lead to more larger data transfer cost. this also provides us with the challenge to exploit data reuse between data tiles. Using our approach we are able to reduce these unnecessary data transfers and improve the performance compared to traditional pure loop tiling. © 2008 IEEE.

关键词： data transfer

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Accurate Synthetic Generation of Realistic Personal Information

Accurate Synthetic Generation of Realistic Personal Informat...

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13th pacific-asia conference on knowledge Discovery and data mining

作者： Christen, Peter Pudjijono, Agus Australian Natl Univ Sch Comp Sci Canberra ACT 0200 Australia Minist Publ Works Republic Indonesia Data Ctr Latham NY 12110 USA

ISBN: (纸本)9783642013065

A large portion of data collected by many organisations today is about people;and often contains personal identifying information, such as names and addresses. Privacy and confidentiality are of great concern when such data is being shared between organisations or made publicly available. Research in (privacy-preserving) data ruining and data linkage is suffering front a lack of publicly available real-world data, sets that contain personal information;And therefore experimental evaluations cart be difficult to conduct. In order to overcome this problem, we have developed a data generator that allows flexible creation of synthetic data, containing personal information with realistic characteristics, such as frequency distributions, attribute dependencies, and error probabilities. Our generator significantly improves earlier approaches, and allows the generation of data for individuals;families and households.

关键词： Artificial data data matching data linkage privacy data mining pre-processing

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mining the Web of Linked data with RapidMiner

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JOURNAL OF WEB SEMANTICS 2015年 35卷 142-151页

作者： Ristoski, Petar Bizer, Christian Paulheim, Heiko Univ Mannheim Data & Web Sci Grp B626 D-68159 Mannheim Germany

Lots of data from different domains are published as Linked Open data (LOD). While there are quite a few browsers for such data, as well as intelligent tools for particular purposes, a versatile tool for deriving additional knowledge by mining the Web of Linked data is still missing. In this system paper, we introduce the RapidMiner Linked Open data extension. the extension hooks into the powerful data mining and analysis platform RapidMiner, and offers operators for accessing Linked Open data in RapidMiner, allowing for using it in sophisticated data analysis workflows without the need for expert knowledge in SPARQL or RDF. the extension allows for autonomously exploring the Web of data by following links, thereby discovering relevant datasets on the fly, as well as for integrating overlapping data found in different datasets. As an example, we show how statistical data from the World Bank on scientific publications, published as an RDF data cube, can be automatically linked to further datasets and analyzed using additional background knowledge from ten different LOD datasets. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Linked Open data data mining RapidMiner

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An Efficient Method for Generating, Storing and Matching Features for Text mining

An Efficient Method for Generating, Storing and Matching Fea...

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13th pacific-asia conference on knowledge Discovery and data mining

作者： Chan, Shing-Kit Lam, Wai Chinese Univ Hong Kong Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9783642013065

Log-linear models have been widely used in text mining tasks because it call incorporate a large number of possibly correlated features. In text mining;these possibly correlated features tire generated by conjunction of features. they are usually used with log-linear models to estimate robust conditional distributions. To avoid manual construction of conjunction of features. we propose a new algorithmic framework called F-tree for automatically generating and storing conjunctions of features in text mining tasks. this compact graph-based data structure allows fast one-vs-all matching of features in the feature space which is crucial for many text;mining tasks. Based on this hierarchical data structure;we propose a systematic method For removing redundant features to further reduce memory usage and improve performance. We do large-scale experiments oil three publicly-available datasets and show that this automatic method can get state-of the-art performance achieved by manual construction of Features.

关键词： data mining

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Analysis of Call-Center Operational data Using Role Hierarchy Miner 13

Analysis of Call-Center Operational Data Using Role Hierarch...

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13th International conference on ICT and knowledge Engineering

作者： Wongvigran, Sompong Premchaiswadi, Wichian Siam Univ Grad Sch Informat Technol Bangkok Thailand

ISBN: (纸本)9781467391900

the main objective of this research is to analyze information of customer contact made to a call center section of a telecommunication company in thailand. Using role hierarchy mining approach (as process mining technique) enabled us to focus on the hierarchical perspectives of the collected event log with respect to the functional relationships amongst the originators (i.e., the administrators and operators who were in charge of handling incoming calls made from customers/clients). Following a role hierarchy approach, we could better track and trace the interactions made between different personnel/administrators in a functional organizational structure from top to down. One of the main advantages of the proposed approach was the ability to detect and identify potential discrepancies and outbreaks made against the rules and responsibilities previously defined by the top management and human resource staff. Accordingly, the results of the study can help the telecommunication companies to improve their call center (customer service) section in such a way to result in more customer/client satisfaction toward the quality of service on work. therefore, applying a role hierarchy mining approach will eventually lead to improving the performance of the handling calls made to the call center section, in a more efficient, effective and timely manner.

关键词： Process mining Role Hierarchy Miner Disco Fluxicon call center event log Fuzzy mining model telecommunication company

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mining Both Positive and Negative Impact-Oriented Sequential Rules from Transactional data

Mining Both Positive and Negative Impact-Oriented Sequential...

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13th pacific-asia conference on knowledge Discovery and data mining

作者： Zhao, Yanchang Zhang, Huaifeng Cao, Longbing Zhang, Chengqi Bohlscheid, Hans Univ Technol Sydney Fac Engn & IT Data Sci & Knowledge Discovery Lab Sydney NSW 2007 Australia

ISBN: (纸本)9783642013065

Traditional sequential pattern milling deals with positive correlation between sequential patterns only, without considering negative relationship between them. In this paper, we present a. notion of impact-oriented negative sequential rules, in which the left side is a positive sequential pattern or it's negation;and the right side is a predefined outcome or its negation. Impact-oriented negative sequential rides are formally defined to show the impact of sequential patterns on the outcome. and all efficient algorithm is designed to discover both positive and negative impact-oriented sequential rules. Experimental results oil both synthetic data and real-life data show the efficiency and effectiveness of the proposed technique.

关键词： negative sequential rules sequential pattern mining

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