Bibliografie tematiche / Data mining

Indice

Articoli di riviste
Tesi
Libri
Capitoli di libri
Atti di convegni
Rapporti di organizzazioni

Letteratura scientifica selezionata sul tema "Data mining"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 30 luglio 2024

Cita una fonte nei formati APA, MLA, Chicago, Harvard e in molti altri stili

Scegli il tipo di fonte:

Consulta la lista di attuali articoli, libri, tesi, atti di convegni e altre fonti scientifiche attinenti al tema "Data mining".

Accanto a ogni fonte nell'elenco di riferimenti c'è un pulsante "Aggiungi alla bibliografia". Premilo e genereremo automaticamente la citazione bibliografica dell'opera scelta nello stile citazionale di cui hai bisogno: APA, MLA, Harvard, Chicago, Vancouver ecc.

Puoi anche scaricare il testo completo della pubblicazione scientifica nel formato .pdf e leggere online l'abstract (il sommario) dell'opera se è presente nei metadati.

Articoli di riviste sul tema "Data mining"

PYLYPIUK, Tetiana, e Viktor SHCHYRBA. "DATA MINING METHODS". Collection of scientific papers Kamianets-Podilsky Ivan Ohienko National University Pedagogical series 29 (14 dicembre 2023): 7–10. http://dx.doi.org/10.32626/2307-4507.2023-29.7-10.

Testo completo

Abstract (sommario):

Research is devoted to Data Mining methods. A comparison of classical and mathematical and statistical methods of data analysis was made. One of the variants of correlation analysis method for intelligent data analysis is proposed and described in an argumentative manner. The question of applying different methodologies for Data Mining is actual. Classically, the following methods of knowledge discovery and analysis are offered in Data Mining: classification; regression; forecasting time sequences (series); clustering; association. As mathematical and statistical methods of analysis in applied research, the most of authors offer such methods as: statistical hypothesis testing, regression models construction and research. Since most real models are not amenable to analysis using classical methods, including regression analysis, the authors propose to use correlational analysis method in Data Mining.

Gli stili APA, Harvard, Vancouver, ISO e altri

Shah Neha K, Shah Neha K. "Introduction of Data mining and an Analysis of Data mining Techniques". Indian Journal of Applied Research 3, n. 5 (1 ottobre 2011): 137–39. http://dx.doi.org/10.15373/2249555x/may2013/41.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Rakholiya, Kalpesh R., e Dr Dhaval Kathiriya. "Data Mining for Moving Object Data". Indian Journal of Applied Research 2, n. 3 (1 ottobre 2011): 111–13. http://dx.doi.org/10.15373/2249555x/dec2012/34.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Chomboon, K., N. Kaoungku, K. Kerdprasop e N. Kerdprasop. "Data Mining in Semantic Web Data". International Journal of Computer Theory and Engineering 6, n. 6 (dicembre 2014): 472–75. http://dx.doi.org/10.7763/ijcte.2014.v6.912.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Загороднюк, П. А. "Data mining in Go". Vestnik of Russian New University. Series «Complex systems: models, analysis, management», n. 4 (10 gennaio 2022): 161–66. http://dx.doi.org/10.18137/rnu.v9187.21.04.p.161.

Testo completo

Abstract (sommario):

Целью данной статьи является оценка языка программирования Go как инструмента для реализации методов data mining. Для этого проводится анализ задачи классификации и метода k-ближайших соседей, затем предлагается способ программирования данного метода и организации процесс управления и подготовки исходных данных. В заключение на основе проведенной работы делается вывод, насколько Go подходит для решения подобных задач, и есть ли потенциал для реализации остальных методов. The purpose of this article is to evaluate the Go programming language as a tool for implementing data mining methods. To do this, an analysis of the classification problem and the k-nearest neighbors’ algorithm is carried out, then a method is proposed for how this method can be programmed and the process of managing and preparing the initial data can be organized. In conclusion, based on the work carried out, it sums up how well Go is suitable for solving such problems and whether there is potential for the implementation of other methods.

Gli stili APA, Harvard, Vancouver, ISO e altri

AVeselý. "Neural networks in data mining". Agricultural Economics (Zemědělská ekonomika) 49, No. 9 (2 marzo 2012): 427–31. http://dx.doi.org/10.17221/5427-agricecon.

Testo completo

Abstract (sommario):

To posses relevant information is an inevitable condition for successful enterprising in modern business. Information could be parted to data and knowledge. How to gather, store and retrieve data is studied in database theory. In the knowledge engineering, there is in the centre of interest the knowledge and methods of its formalization and gaining are studied. Knowledge could be gained from experts, specialists in the area of interest, or it can be gained by induction from sets of data. Automatic induction of knowledge from data sets, usually stored in large databases, is called data mining. Classical methods of gaining knowledge from data sets are statistical methods. In data mining, new methods besides statistical are used. These new methods have their origin in artificial intelligence. They look for unknown and unexpected relations, which can be uncovered by exploring of data in database. In the article, a utilization of modern methods of data mining is described and especially the methods based on neural networks theory are pursued. The advantages and drawbacks of applications of multiplayer feed forward neural networks and Kohonen’s self-organizing maps are discussed. Kohonen’s self-organizing map is the most promising neural data-mining algorithm regarding its capability to visualize high-dimensional data.

Gli stili APA, Harvard, Vancouver, ISO e altri

M., Inbavalli. "An Intelligent Agent based Mining Techniques for Distributed Data Mining". Journal of Advanced Research in Dynamical and Control Systems 12, SP4 (31 marzo 2020): 610–17. http://dx.doi.org/10.5373/jardcs/v12sp4/20201527.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Raval, Hitesh R., e Dr Vikram Kaushik. "Data Mining: Performance Tuning Of Temporal Data Mining Based On Frequent Inter-Transaction Itemsets Discovery". International Journal of Scientific Research 3, n. 2 (1 giugno 2012): 78–82. http://dx.doi.org/10.15373/22778179/feb2014/25.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Stoffel, Kilian. "Web + Data Mining = Web Mining". HMD Praxis der Wirtschaftsinformatik 46, n. 4 (agosto 2009): 6–20. http://dx.doi.org/10.1007/bf03340377.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Tsuta, Mizuki. "Data Mining". Nippon Shokuhin Kagaku Kogaku Kaishi 64, n. 6 (2017): 334–35. http://dx.doi.org/10.3136/nskkk.64.334.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Più fonti

Tesi sul tema "Data mining"

Mrázek, Michal. "Data mining". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-400441.

Testo completo

Abstract (sommario):

The aim of this master’s thesis is analysis of the multidimensional data. Three dimensionality reduction algorithms are introduced. It is shown how to manipulate with text documents using basic methods of natural language processing. The goal of the practical part of the thesis is to process real-world data from the internet forum. Posted messages are transformed to the numerical representation, then to two-dimensional space and visualized. Later on, topics of the messages are discovered. In the last part, a few selected algorithms are compared.

Gli stili APA, Harvard, Vancouver, ISO e altri

Payyappillil, Hemambika. "Data mining framework". Morgantown, W. Va. : [West Virginia University Libraries], 2005. https://etd.wvu.edu/etd/controller.jsp?moduleName=documentdata&jsp%5FetdId=3807.

Testo completo

Abstract (sommario):

Thesis (M.S.)--West Virginia University, 2005
Title from document title page. Document formatted into pages; contains vi, 65 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 64-65).

Gli stili APA, Harvard, Vancouver, ISO e altri

Abedjan, Ziawasch. "Improving RDF data with data mining". Phd thesis, Universität Potsdam, 2014. http://opus.kobv.de/ubp/volltexte/2014/7133/.

Testo completo

Abstract (sommario):

Linked Open Data (LOD) comprises very many and often large public data sets and knowledge bases. Those datasets are mostly presented in the RDF triple structure of subject, predicate, and object, where each triple represents a statement or fact. Unfortunately, the heterogeneity of available open data requires significant integration steps before it can be used in applications. Meta information, such as ontological definitions and exact range definitions of predicates, are desirable and ideally provided by an ontology. However in the context of LOD, ontologies are often incomplete or simply not available. Thus, it is useful to automatically generate meta information, such as ontological dependencies, range definitions, and topical classifications. Association rule mining, which was originally applied for sales analysis on transactional databases, is a promising and novel technique to explore such data. We designed an adaptation of this technique for min-ing Rdf data and introduce the concept of “mining configurations”, which allows us to mine RDF data sets in various ways. Different configurations enable us to identify schema and value dependencies that in combination result in interesting use cases. To this end, we present rule-based approaches for auto-completion, data enrichment, ontology improvement, and query relaxation. Auto-completion remedies the problem of inconsistent ontology usage, providing an editing user with a sorted list of commonly used predicates. A combination of different configurations step extends this approach to create completely new facts for a knowledge base. We present two approaches for fact generation, a user-based approach where a user selects the entity to be amended with new facts and a data-driven approach where an algorithm discovers entities that have to be amended with missing facts. As knowledge bases constantly grow and evolve, another approach to improve the usage of RDF data is to improve existing ontologies. Here, we present an association rule based approach to reconcile ontology and data. Interlacing different mining configurations, we infer an algorithm to discover synonymously used predicates. Those predicates can be used to expand query results and to support users during query formulation. We provide a wide range of experiments on real world datasets for each use case. The experiments and evaluations show the added value of association rule mining for the integration and usability of RDF data and confirm the appropriateness of our mining configuration methodology.
Linked Open Data (LOD) umfasst viele und oft sehr große öffentlichen Datensätze und Wissensbanken, die hauptsächlich in der RDF Triplestruktur bestehend aus Subjekt, Prädikat und Objekt vorkommen. Dabei repräsentiert jedes Triple einen Fakt. Unglücklicherweise erfordert die Heterogenität der verfügbaren öffentlichen Daten signifikante Integrationsschritte bevor die Daten in Anwendungen genutzt werden können. Meta-Daten wie ontologische Strukturen und Bereichsdefinitionen von Prädikaten sind zwar wünschenswert und idealerweise durch eine Wissensbank verfügbar. Jedoch sind Wissensbanken im Kontext von LOD oft unvollständig oder einfach nicht verfügbar. Deshalb ist es nützlich automatisch Meta-Informationen, wie ontologische Abhängigkeiten, Bereichs-und Domänendefinitionen und thematische Assoziationen von Ressourcen generieren zu können. Eine neue und vielversprechende Technik um solche Daten zu untersuchen basiert auf das entdecken von Assoziationsregeln, welche ursprünglich für Verkaufsanalysen in transaktionalen Datenbanken angewendet wurde. Wir haben eine Adaptierung dieser Technik auf RDF Daten entworfen und stellen das Konzept der Mining Konfigurationen vor, welches uns befähigt in RDF Daten auf unterschiedlichen Weisen Muster zu erkennen. Verschiedene Konfigurationen erlauben uns Schema- und Wertbeziehungen zu erkennen, die für interessante Anwendungen genutzt werden können. In dem Sinne, stellen wir assoziationsbasierte Verfahren für eine Prädikatvorschlagsverfahren, Datenvervollständigung, Ontologieverbesserung und Anfrageerleichterung vor. Das Vorschlagen von Prädikaten behandelt das Problem der inkonsistenten Verwendung von Ontologien, indem einem Benutzer, der einen neuen Fakt einem Rdf-Datensatz hinzufügen will, eine sortierte Liste von passenden Prädikaten vorgeschlagen wird. Eine Kombinierung von verschiedenen Konfigurationen erweitert dieses Verfahren sodass automatisch komplett neue Fakten für eine Wissensbank generiert werden. Hierbei stellen wir zwei Verfahren vor, einen nutzergesteuertenVerfahren, bei dem ein Nutzer die Entität aussucht die erweitert werden soll und einen datengesteuerten Ansatz, bei dem ein Algorithmus selbst die Entitäten aussucht, die mit fehlenden Fakten erweitert werden. Da Wissensbanken stetig wachsen und sich verändern, ist ein anderer Ansatz um die Verwendung von RDF Daten zu erleichtern die Verbesserung von Ontologien. Hierbei präsentieren wir ein Assoziationsregeln-basiertes Verfahren, der Daten und zugrundeliegende Ontologien zusammenführt. Durch die Verflechtung von unterschiedlichen Konfigurationen leiten wir einen neuen Algorithmus her, der gleichbedeutende Prädikate entdeckt. Diese Prädikate können benutzt werden um Ergebnisse einer Anfrage zu erweitern oder einen Nutzer während einer Anfrage zu unterstützen. Für jeden unserer vorgestellten Anwendungen präsentieren wir eine große Auswahl an Experimenten auf Realweltdatensätzen. Die Experimente und Evaluierungen zeigen den Mehrwert von Assoziationsregeln-Generierung für die Integration und Nutzbarkeit von RDF Daten und bestätigen die Angemessenheit unserer konfigurationsbasierten Methodologie um solche Regeln herzuleiten.

Gli stili APA, Harvard, Vancouver, ISO e altri

Liu, Tantan. "Data Mining over Hidden Data Sources". The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1343313341.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Taylor, Phillip. "Data mining of vehicle telemetry data". Thesis, University of Warwick, 2015. http://wrap.warwick.ac.uk/77645/.

Testo completo

Abstract (sommario):

Driving a safety critical task that requires a high level of attention and workload from the driver. Despite this, people often perform secondary tasks such as eating or using a mobile phone, which increase workload levels and divert cognitive and physical attention from the primary task of driving. As well as these distractions, the driver may also be overloaded for other reasons, such as dealing with an incident on the road or holding conversations in the car. One solution to this distraction problem is to limit the functionality of in-car devices while the driver is overloaded. This can take the form of withholding an incoming phone call or delaying the display of a non-urgent piece of information about the vehicle. In order to design and build these adaptions in the car, we must first have an understanding of the driver's current level of workload. Traditionally, driver workload has been monitored using physiological sensors or camera systems in the vehicle. However, physiological systems are often intrusive and camera systems can be expensive and are unreliable in poor light conditions. It is important, therefore, to use methods that are non-intrusive, inexpensive and robust, such as sensors already installed on the car and accessible via the Controller Area Network (CAN)-bus. This thesis presents a data mining methodology for this problem, as well as for others in domains with similar types of data, such as human activity monitoring. It focuses on the variable selection stage of the data mining process, where inputs are chosen for models to learn from and make inferences. Selecting inputs from vehicle telemetry data is challenging because there are many irrelevant variables with a high level of redundancy. Furthermore, data in this domain often contains biases because only relatively small amounts can be collected and processed, leading to some variables appearing more relevant to the classification task than they are really. Over the course of this thesis, a detailed variable selection framework that addresses these issues for telemetry data is developed. A novel blocked permutation method is developed and applied to mitigate biases when selecting variables from potentially biased temporal data. This approach is infeasible computationally when variable redundancies are also considered, and so a novel permutation redundancy measure with similar properties is proposed. Finally, a known redundancy structure between features in telemetry data is used to enhance the feature selection process in two ways. First the benefits of performing raw signal selection, feature extraction, and feature selection in different orders are investigated. Second, a two-stage variable selection framework is proposed and the two permutation based methods are combined. Throughout the thesis, it is shown through classification evaluations and inspection of the features that these permutation based selection methods are appropriate for use in selecting features from CAN-bus data.

Gli stili APA, Harvard, Vancouver, ISO e altri

Sherikar, Vishnu Vardhan Reddy. "I2MAPREDUCE: DATA MINING FOR BIG DATA". CSUSB ScholarWorks, 2017. https://scholarworks.lib.csusb.edu/etd/437.

Testo completo

Abstract (sommario):

This project is an extension of i2MapReduce: Incremental MapReduce for Mining Evolving Big Data . i2MapReduce is used for incremental big data processing, which uses a fine-grained incremental engine, a general purpose iterative model that includes iteration algorithms such as PageRank, Fuzzy-C-Means(FCM), Generalized Iterated Matrix-Vector Multiplication(GIM-V), Single Source Shortest Path(SSSP). The main purpose of this project is to reduce input/output overhead, to avoid incurring the cost of re-computation and avoid stale data mining results. Finally, the performance of i2MapReduce is analyzed by comparing the resultant graphs.

Gli stili APA, Harvard, Vancouver, ISO e altri

Zhang, Nan. "Privacy-preserving data mining". [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1080.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Hulten, Geoffrey. "Mining massive data streams /". Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/6937.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Büchel, Nina. "Faktorenvorselektion im Data Mining /". Berlin : Logos, 2009. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=019006997&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Shao, Junming. "Synchronization Inspired Data Mining". Diss., lmu, 2011. http://nbn-resolving.de/urn:nbn:de:bvb:19-137356.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Più fonti

Libri sul tema "Data mining"

Xu, Yue, Rosalind Wang, Anton Lord, Yee Ling Boo, Richi Nayak, Yanchang Zhao e Graham Williams, a cura di. Data Mining. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-8531-6.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Dulli, Susi, Sara Furini e Edmondo Peron. Data mining. Milano: Springer Milan, 2009. http://dx.doi.org/10.1007/978-88-470-1163-2.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Stahlbock, Robert, Sven F. Crone e Stefan Lessmann, a cura di. Data Mining. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-1280-0.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Islam, Rafiqul, Yun Sing Koh, Yanchang Zhao, Graco Warwick, David Stirling, Chang-Tsun Li e Zahidul Islam, a cura di. Data Mining. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6661-1.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Boo, Yee Ling, David Stirling, Lianhua Chi, Lin Liu, Kok-Leong Ong e Graham Williams, a cura di. Data Mining. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0292-3.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Nakhaeizadeh, Gholamreza, a cura di. Data Mining. Heidelberg: Physica-Verlag HD, 1998. http://dx.doi.org/10.1007/978-3-642-86094-2.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Aggarwal, Charu C. Data Mining. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14142-8.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Runkler, Thomas A. Data Mining. Wiesbaden: Vieweg+Teubner, 2010. http://dx.doi.org/10.1007/978-3-8348-9353-6.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Kantardzic, Mehmed. Data Mining. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118029145.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Le, Thuc D., Kok-Leong Ong, Yanchang Zhao, Warren H. Jin, Sebastien Wong, Lin Liu e Graham Williams, a cura di. Data Mining. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1699-3.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Più fonti

Capitoli di libri sul tema "Data mining"

Freitas, Alex A., e Simon H. Lavington. "Data Mining". In Mining Very Large Databases with Parallel Processing, 41–50. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-5521-6_5.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Rahman, Mirza I., e Robbert P. van Manen. "Data Mining". In Principles and Practice of Pharmaceutical Medicine, 587–600. Oxford, UK: Wiley-Blackwell, 2010. http://dx.doi.org/10.1002/9781444325263.ch44.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Du, Ke-Lin, e M. N. S. Swamy. "Data Mining". In Neural Networks and Statistical Learning, 747–78. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5571-3_25.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Chang, George, Marcus J. Healey, James A. M. McHugh e Jason T. L. Wang. "Data Mining". In Mining the World Wide Web, 67–80. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1639-2_5.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Pappa, Gisele L., e Alex A. Freitas. "Data Mining". In Natural Computing Series, 17–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02541-9_2.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Du, Ke-Lin, e M. N. S. Swamy. "Data Mining". In Neural Networks and Statistical Learning, 871–903. London: Springer London, 2019. http://dx.doi.org/10.1007/978-1-4471-7452-3_30.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Lee, Raymond S. T. "Data Mining". In Artificial Intelligence in Daily Life, 71–118. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7695-9_4.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Morzy, Tadeusz, e Maciej Zakrzewicz. "Data Mining". In Handbook on Data Management in Information Systems, 487–565. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-24742-5_11.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

van der Aalst, Wil. "Data Mining". In Process Mining, 89–121. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49851-4_4.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Mohan, Chilukuri Krishna. "Data Mining". In Frontiers of Expert Systems, 237–58. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4509-5_9.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Atti di convegni sul tema "Data mining"

Song, Xiaoli, XiaoTong Wang e Xiaohua Hu. "Semantic pattern mining for text mining". In 2016 IEEE International Conference on Big Data (Big Data). IEEE, 2016. http://dx.doi.org/10.1109/bigdata.2016.7840600.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Agarwal, Shivam. "Data Mining: Data Mining Concepts and Techniques". In 2013 International Conference on Machine Intelligence and Research Advancement (ICMIRA). IEEE, 2013. http://dx.doi.org/10.1109/icmira.2013.45.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Edelstein, Herb. "Data mining". In the seventh ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2001. http://dx.doi.org/10.1145/502512.502517.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

"Data mining". In 2015 International Symposium on Advanced Computing and Communication (ISACC). IEEE, 2015. http://dx.doi.org/10.1109/isacc.2015.7377334.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

DeWaal, Mindy. "Data Mining". In the 46th ACM Technical Symposium. New York, New York, USA: ACM Press, 2015. http://dx.doi.org/10.1145/2676723.2693628.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Ursyn, Anna. "Data mining". In ACM SIGGRAPH 2004 Art gallery. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/1185884.1186011.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Peñafiel, Myriam, Stefanie Vásquez, Diego Vásquez, Juan Zaldumbide e Sergio Luján-Mora. "Data Mining and Opinion Mining". In the 2018 International Conference. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3274250.3274263.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Yang, Tie-li, Ping-Bai e Yu-Sheng Gong. "Spatial Data Mining Features between General Data Mining". In 2008 International Workshop on Geoscience and Remote Sensing (ETT and GRS). IEEE, 2008. http://dx.doi.org/10.1109/ettandgrs.2008.167.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Ashok, Vikas, e Ravi Mukkamala. "Data mining without data". In the 10th annual ACM workshop. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2046556.2046578.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

"Session C: Dynamic data mining & data stream mining". In 2016 IEEE First International Conference on Data Stream Mining & Processing (DSMP). IEEE, 2016. http://dx.doi.org/10.1109/dsmp.2016.7583553.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Rapporti di organizzazioni sul tema "Data mining"

Lee, K., H. Kargupta, B. G. Stafford, K. L. Buescher e B. Ravindran. Data mining. Office of Scientific and Technical Information (OSTI), dicembre 1998. http://dx.doi.org/10.2172/334314.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Kramer, Mitchell. Customer Data Mining. Boston, MA: Patricia Seybold Group, maggio 2004. http://dx.doi.org/10.1571/psgp5-27-04cc.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Kramer, Mitchell. Data Mining at Work. Boston, MA: Patricia Seybold Group, giugno 2004. http://dx.doi.org/10.1571/psgp6-10-04cc.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Brown, David A., John Hirdt e Michal Herman. Data mining the EXFOR database. Office of Scientific and Technical Information (OSTI), dicembre 2013. http://dx.doi.org/10.2172/1122776.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Lu, Xiaomeng, Robert Stambaugh e Yu Yuan. Anomalies Abroad: Beyond Data Mining. Cambridge, MA: National Bureau of Economic Research, settembre 2017. http://dx.doi.org/10.3386/w23809.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Davidson, George S., Jana Strasburg, David Stampf, Lev Neymotin, Carl Czajkowski, Eugene Shine, James Bollinger et al. Data mining for ontology development. Office of Scientific and Technical Information (OSTI), giugno 2010. http://dx.doi.org/10.2172/992328.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Berry, Jonathan W., Vitus Joseph Leung, Cynthia Ann Phillips, Ali Pinar, David Gerald Robinson, Tanya Berger-Wolf, Sanjukta Bhowmick et al. Statistically significant relational data mining :. Office of Scientific and Technical Information (OSTI), febbraio 2014. http://dx.doi.org/10.2172/1204082.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Zdonik, Stanley B. Monitoring and Mining Data Streams. Fort Belvoir, VA: Defense Technical Information Center, ottobre 2004. http://dx.doi.org/10.21236/ada431589.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Zdonik, Stan B. Monitoring and Mining Data Streams. Fort Belvoir, VA: Defense Technical Information Center, ottobre 2003. http://dx.doi.org/10.21236/ada419707.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Zhan, Zhijun, e LiWu Chang. Privacy-Preserving Collaborative Data Mining. Fort Belvoir, VA: Defense Technical Information Center, gennaio 2003. http://dx.doi.org/10.21236/ada464602.

Testo completo

Gli stili APA, Harvard, Vancouver, ISO e altri

Offriamo sconti su tutti i piani premium per gli autori le cui opere sono incluse in raccolte letterarie tematiche. Contattaci per ottenere un codice promozionale unico!