data mining in English
It is not uncommon that databases for data mining require their own analytic engine, design and structure.
Use "data mining" in a sentence
1. The Core team understand data mining.
2. Data Applied, a web based data mining environment.
3. Apriori algorithm is a classical algorithm in data mining
4. Data mining is used to analyse individuals' buying habits.
5. KNIME: free and commercial machine learning and data mining software.
6. Cross-industry standard process for data mining, known as Crisp-DM, is an open standard process model that describes common approaches used by data mining experts
7. Aidm Information Technology and Services Al Khaldeyah, Makkah 1,395 followers Artificial Intelligence and Data Mining (Aidm) company specializes in developing innovative AI and Data Mining Solutions
8. This topic in development uses data warehouse and data mining technology.
9. The basic step of the data mining has five stages: question definition and subject analysis, data preparation, model build, mode assessment, appraisal and verification of the data mining result.
10. The genetic algorithm plays an important role in area of data mining.
11. This process is called data accumulation or data enhancement in data mining lingo.
12. • Analytical Tools (e.g., Advanced Analysis Tools, Data Mining/Knowledge Discovery, and Knowledge Management);
13. Advanced data-mining techniques and enhanced learning algorithms are also being worked on.
14. For example, data mining techniques might be applied to mine and structure personal information.
15. Himalaya Tools is a suite of programs focusing on new techniques in data mining.
16. Data sources for data mining access are uniformly modelled using the abstract class MiningInputStream.
17. This article introduces the background, basic tasks and methods of Data Mining with pellucid examples.
18. The technology integrates advanced criminal and social network analysis, together with text and data mining methods.
19. The issue of data mining also come into place as countries head towards a cashless society.
20. Using the method of binary system in association rule data mining may produce some redundancy patterns.
21. There are two types of data mining methods integration, they are horizontal integration and vertical integration.
22. Spatial clustering analysis is important method and study content of spatial analysis and spatial data mining.
23. The growth of data mining has led many to worry about invasions of privacy by overzealous marketers.
24. Augustus is designed for statistical and data mining models and produces and consumes models with 10,000s of segments
25. The Commission will continue to support R&D in data-handling technologies, e.g. data mining, analytics or visualisation.
26. The extension method enriches the content of data mining, and provides new tools for building multivalue correlative criteria.
27. Data mining requires data preparation which can uncover information or patterns which may compromise confidentiality and privacy obligations.
28. Mathematical and programming methods of data processing; modelling and prediction; data mining; expert information systems; and decision support systems;
29. In particular, machine learning algorithms together with data mining processes can help in pattern recognition even with unstructured data.
30. University projects from California, Switzerland and Germany try to improve that by methods of formal analysis and data mining.
31. Weimann has argued that data mining could sniff out jihadists or remove information before would-be terrorists see it.
32. Spatial clustering is one of the important research topic in spatial data mining, it is widely applied in spatial analysis.
33. Business intelligence (Bi) is an umbrella term for the technology that enables data preparation, data mining, data management, and data visualization
34. (dental practice management placement) Admi: Air Defense MSE Interface: Admi: Australian DeMining International Pty Ltd: Admi: Agents and Data Mining Interaction (workshop)
35. There are three common personalized recommendatory technologies: information retrieval and extractor, content-based filtering and collaborative filtering, data mining and knowledge discovery.
36. Aiming at the method of binary system conversion in data mining, this paper defines binary system sequences set and its related concepts.
37. In the area of electrical power engineering, data mining methods have been widely used for condition monitoring of high voltage electrical equipment.
38. Depending on all above studies and experiments, we can conclude that using data mining distill prosodic rules in speech synthesis is viable.
39. This add-in can be used alone, but it’s designed to work with Frontline’s Analytic Solver Data Mining add-in, offering powerful forecasting
40. Deep Packet Inspection (and filtering) enables advanced network management, user service, and security functions as well as Internet data mining, eavesdropping, censorship etc.
41. Data mining is an intercrossed subject, involving many fields such as machine learning, model reorganization, induction and deduction, statistics, database and high performance calculation.
42. Such as: the establishment of databank, category analysis and management, data mining and implementation, integration "between proscenium and tiring-room" of Digital Marketing etc.
43. BI is a broad term that encompasses data mining, process analysis, performance benchmarking, and descriptive analytics. BI parses all the data generated by a …
44. This also includes the use of Big Data infrastructures, Data Mining, advanced analytics, predictive analytics and Customer Journey management and xIntelligence: multi-channel analytics.
45. Emerging technology, uses advanced data-mining and software algorithms to detect what the users themselves consider to be "topics", then virtually classifies the documents automatically.
46. Computer software for reporting, online analytical processing, analytics, data mining, business performance management, benchmarking, text mining, and predictive analytics, all in the field of business intelligence
47. In this paper we give an archetypal design for data mining system, Incremental updating technique is applied in this archetypal system which quickly dealing with large databases.
48. Tolerence operators are kind of operations converting general relation to compatibility relation, It also extends the application range of the compatibility relation-based methods for data mining.
49. In 2015, IBM released a new methodology called Analytics Solutions Unified Method for Data Mining/Predictive Analytics (also known as ASUM-DM) which refines and extends Crisp-DM.
50. Our track in Biostatistics and Data Science is unique as it focuses on data mining and machine learning techniques yet retains the rigor of a traditional Biostatistics program