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| 3.DMM'2013 — Data Mining in Marketing DMM |
| Beginn | 19. Jul 2013 | [ID=529004]  |
| Ort | New York, Vereinigte Staaten |
| Zusammenfassung | In business environment data warehousing - the practice of creating huge, central stores of customer data that can be used throughout the enterprise - is becoming more and more common practice and, as a consequence, the importance of data mining is growing stronger. Data mining allows indeed to extract the most important information from such vast data and to uncover previously unknown patterns that may be relevant to current business problems, thereby helping business managers to transform data into business decisions. In marketing data mining has several and profitable applications. It can help to identify market segments containing customers with high-profit potential, and then build campaigns that favorably impact their behavior; to detect customers dissatisfied and ready to leave, and then align campaigns more closely with their needs; to outline profiles of prospective customers, and then increase the response rates of the acquisition campaigns, and so on. |
| Webseite | http://www.data-mining-forum.de/w_marketing.php |
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| 4.MLDM´2013 — 9th International Conference on Machine Learning and Data Mining |
| Termin | 19. Jul 2013 → 25. Jul 2013 | [ID=529060] |
| Ort | New York, Vereinigte Staaten |
| Zusammenfassung | The aim of the conference is to bring together researchers from all over the world who deal with machine learning and data mining in order to discuss the recent status of the research and to direct further developments. Basic research papers as well as application papers are welcome. |
| Webseite | http://www.mldm.de/ |
| Verwandte Fachgebiete | Angewandte Mathematik: Neuronale Netze und Künstliche Intelligenz |
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| 5.SIGIR '13 — The 36th International ACM SIGIR conference on research and development in Information Retrieval |
| Termin | 28. Jul 2013 → 01. Aug 2013 | [ID=528273] |
| Ort | Dublin, Irland |
| Webseite | http://www.sigir2013.ie |
| Verwandte Fachgebiete | Informations & Wissensmanagement |
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| 6.BIOKDD — 12th International Workshop on Data Mining in Bioinformatics |
| Beginn | 11. Aug 2013 | [ID=545921] |
| Ort | Chicago, Vereinigte Staaten |
| Zusammenfassung | The goal of this workshop is to encourage KDD researchers to take on the numerous challenges that Bioinformatics offers. This year, the workshop will feature the theme ofBuilding network and predictive models of biological processes and diseases using complex data. This field focuses on the use of computational approaches, especially from data mining and machine learning, and the large amount and variety of biological data being generated. The goal here is to build accurate predictive or descriptive network models of biological processes and diseases. These approaches have revolutionized the new age biology by enabling novel discoveries in basic biology and diseases like cancer and diabetes, as well as the development of therapeutics. |
| Themen | Bioinformatics, data mining, systems biology, networks, machine learning, genomics |
| Webseite | http://home.biokdd.org/biokdd13/ |
| Kontakt | Gaurav Pandey; Email: pandey.gaurav@gmail.com |
| Verwandte Fachgebiete | Genomforschung und Bioinformatik; Systembiologie und mathematische Biologie |
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| 7.KDIR 2013 — 5th International Conference on Knowledge Discovery and Information Retrieval |
| Termin | 19. Sep 2013 → 22. Sep 2013 | [ID=531043] |
| Ort | Vilamoura, Portugal |
| Zusammenfassung | Knowledge Discovery is an interdisciplinary area focusing upon methodologies for identifying valid, novel, potentially useful and meaningful patterns from data, often based on underlying large data sets. A major aspect of Knowledge Discovery is data mining, i.e. applying data analysis and discovery algorithms that produce a particular enumeration of patterns (or models) over the data. Knowledge Discovery also includes the evaluation of patterns and identification of which add to knowledge. This has proven to be a promising approach for enhancing the intelligence of software systems and services. The ongoing rapid growth of online data due to the Internet and the widespread use of large databases have created an important need for knowledge discovery methodologies. The challenge of extracting knowledge from data draws upon research in a large number of disciplines including statistics, databases, pattern recognition, machine learning, data visualization, optimization, and high-performance computing, to deliver advanced business intelligence and web discovery solutions. |
| Themen | Web mining , Machine Learning Foundations of knowledge discovery in databases , Data Analytics , Data mining in electronic commerce , Interactive and online data mining , Process mining , Integration of data warehousing and data mining , Data reduction and quality assessment , Mining high-dimensional data , Mining text and semi-structured data , Mining multimedia data, Structured data analysis and statistical methods, BioInformatics & pattern discovery, Clustering and classification methods, Pre-processing and post-processing for data mining , Visual data mining and data visualization , Software development , Business intelligence applications , Information extraction , Concept Mining , Context Discovery, Optimization, Information Extraction from Emails, User Profiling and Recommender Systems, Collaborative Filtering |
| Webseite | http://www.kdir.ic3k.org/ |
| Verwandte Fachgebiete | Informations & Wissensmanagement |
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| 8.IDA 2013 — The Twelfth International Symposium on Intelligent Data Analysis |
| Termin | 17. Okt 2013 → 19. Okt 2013 | [ID=524171] |
| Ort | London, Großbritannien |
| Themen | data analysis, statistics, machine learning, data mining, visualization, big data |
| Webseite | http://ida2013.org |
| Verwandte Fachgebiete | Statistik; Informations & Wissensmanagement |
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| 9.IDEAL — 14th International Conference on Intelligent Data Engineering and Automated Learning |
| Termin | 20. Okt 2013 → 23. Okt 2013 | [ID=549313] |
| Ort | Hefei, China |
| Zusammenfassung | The International Conference on Intelligent Data Engineering and Automated Learning (IDEAL) is an annual international conference dedicated to emerging and challenging topics in intelligent data analysis, data mining and their associated learning systems and paradigms. Its core themes include: the Big Data challenges, Machine Learning, Data Mining, Information Retrieval and Management, Bio- and Neuro-Informatics, Bio-Inspired Models (including Neural Networks, Evolutionary Computation and Swarm Intelligence), Agents and Hybrid Intelligent Systems, and Real-world Applications of Intelligent Techniques. Other related and emerging themes and topics are also welcome. |
| Webseite | http://nical.ustc.edu.cn/ideal13/ |
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Stand vom 07. Mai 2013
