Recursive data mining for role identification in electronic communications

Although the rapid development of the modern distance education, there is still some shortcomings. In order to overcome these shortcomings and use a large number of data in these remote teaching sites effectively, it is necessary for the introduction of data mining technology to the modern remote education system. The paper introduced distance education system based on Web mining, and how data mining of these distance education website.Modern distance education is the common trend of the development of education in the world. With the development and application of satellite and cable TV, as well as a variety of electronic communications technology, especially with the advancement of the global computer network and multimedia technology, many universities have established distance education platforms. Because of a large number of students, we are relative lack of educational resources nowadays. For this reason, our country is actively developing modern distance education and integrating the various types of educational resources by advanced information technology and educational technology.

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Privacy: Users of Pharmaceutical Websites

The Journal of Law Medicine & Ethics ◽

10.1017/s1073110500008810 ◽

2002 ◽

Vol 30 (3) ◽

pp. 466-474

Keyword(s):

Personal Information ◽

District Court ◽

Traffic Data ◽

Web Traffic ◽

Electronic Communications ◽

Private Action

In In re Pharmatrak, Inc. Privacy Litigation, website users brought suit claiming that major pharmaceutical corporations and a web monitoring company violated three federal statutes protecting electronic communications and data by collecting web traffic data and personal information about website users. On August 13,2002, the District Court of Massachusetts dismissed these allegations, holding that the defendants were parties to the communications and thus exempted under the statutory language.The court also found that plaintiffs had not suffered an amount of damages required to sustain private action.

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Data Mining and Machine Learning

10.1017/9781108564175 ◽

2020 ◽

Cited By ~ 2

Author(s):

Mohammed J. Zaki ◽

Wagner Meira, Jr

Keyword(s):

Machine Learning ◽

Data Mining

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The economics of selection of mail orders Drs. Zahavi and Levin are the masterminds behind the development of AMOS, a customized predictive modeling system for the Franklin Mint in Philadelphia, and GainSmarts, a general purpose data mining system that is the two-time winner of the KDD-CUP competition for the best data mining tools (1997 and 1998) sponsored by the American Association for Artificial Intelligence.

Journal of Interactive Marketing ◽

10.1002/dir.1016.abs ◽

2001 ◽

Vol 15 (3) ◽

pp. 53

Author(s):

Nissan Levin ◽

Jacob Zahavi

Keyword(s):

Artificial Intelligence ◽

Data Mining ◽

Predictive Modeling ◽

American Association ◽

General Purpose ◽

Mining System ◽

Data Mining System ◽

Mining Tools ◽

Selection Of

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Heart Rate Variability, Emotions, and Music

Journal of Psychophysiology ◽

10.1027/0269-8803/a000021 ◽

2010 ◽

Vol 24 (2) ◽

pp. 112-119 ◽

Cited By ~ 9

Author(s):

F. Riganello ◽

A. Candelieri ◽

M. Quintieri ◽

G. Dolce

Keyword(s):

Data Mining ◽

Heart Rate ◽

Heart Rate Variability ◽

Vegetative State ◽

Low Frequency ◽

Emotional Reactions ◽

Heart Beat ◽

Healthy Controls ◽

Frequency Spectra ◽

Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

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