Results 241 to 250 of about 3,447,982 (286)

Knowledge discovery in data warehouses

ACM SIGMOD Record, 2000
As the size of data warehouses increase to several hundreds of gigabytes or terabytes, the need for methods and tools that will automate the process of knowledge extraction, or guide the user to subsets of the dataset that are of particular interest, is becoming prominent.
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Context-aware data discovery

2012 16th International Conference on Intelligence in Next Generation Networks, 2012
This paper discusses context-aware data browsing and data retrieval for mobile subscribers. We describe existing models as well as provide a new description for our SpotEx approach. Our model for context-aware data discovery uses mobile phones as proximity sensors.
Dmitry Namiot, Manfred Sneps-Sneppe
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Data compression producing structures—Discoveries

Information Processing & Management, 1976
Abstract This paper describes a formalism to construct some kinds of algorithms useful to represent one structure about a set of data. It proves that if we do not take into account cost considerations of one algorithm, one can partialy replace the memory by an algorithm. It also proves that the remaining memory part is independant of the construction
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Deterring Discovery-Driven Data Deletion

2014
Litigation costs frequently frighten companies into deleting valuable data—and this problem has gotten worse with new technology. In the past, litigation costs were dwarfed by the physical costs of storage: keeping letters in filing cabinets was so expensive that companies deleted data without even considering litigation.
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Knowledge discovery from data?

IEEE Intelligent Systems, 2000
The knowledge discovery and data mining (KDD) field draws on findings from statistics, databases, and artificial intelligence to construct tools that let users gain insight from massive data sets. People in business, science, medicine, academia, and government collect such data sets, and several commercial packages now offer general-purpose KDD tools ...
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Interactive Data Discovery in Data Lakes

2021
As data is produced at an unprecedented rate, the need and ex- pectation to make it easily available for the end-users is growing. Dataset Discovery has become an important subject in the data management community, as it represents the means of providing the data to the user and fulfilling an information need.
Ionescu, A. (author), Katsifodimos, A (author), Houben, G.J.P.M. (author)   +2 more
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Data discovery in data lakes

The availability of large data lakes has led to the development of numerous data discovery approaches, such as join discovery and correlation discovery with task-specific index structures and algorithms. However, current approaches face several disadvantages. The join discovery methods lead to a large number of false positives in the existence of multi-
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Mobile Enterprise Data Discovery

2016
One of the most famous generals of World War II was George Patton, and the above quote is attributed to him. The statement reflects what Patton was best known for: taking action with the best possible information, instead of excessively analyzing situations. Patton was ardently opposed to digging in or establishing fixed fortifications, and he demanded
William Smith, Helen Sun
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Data, Knowledge and Discovery

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015
Increasingly it is data, vast amounts of data, that drives scientific discovery. At the heart of this so-called "fourth paradigm of science" is the rapid development of large scale statistical data fusion and machine learning methods. While these developments in "big data" methods are largely driven by commercial applications such as internet search or
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Data Linkage Discovery Applications

2018
This chapter discusses the topic of linkage discovery for data and their applications. This chapter enhances a previous study by the authors and includes additional references that pertain to applications of linkage discovery not requiring a glossary framework.
Richard S. Segall, Shen Lu
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