Sentiment Polarity Classification Using Statistical Data Compression Models

2012 ◽  
Author(s):  
Dominique Ziegelmayer ◽  
Rainer Schrader
Keyword(s):  
Data Compression ◽  
Statistical Data ◽  
Polarity Classification

Key Technologies for Next-Generation Digital RoF Mobile Fronthaul With Statistical Data Compression and Multiband Modulation

2017 ◽  
Vol 35 (17) ◽  
pp. 3671-3679 ◽  
Author(s):  
Mu Xu ◽  
Feng Lu ◽  
Jing Wang ◽  
Lin Cheng ◽  
Daniel Guidotti ◽  
...  
Keyword(s):  
Data Compression ◽  
Statistical Data ◽  
Next Generation ◽  
Key Technologies

Statistical Data Compression and Differential Coding for Digital Radio-Over-Fiber-Based Mobile Fronthaul

2018 ◽  
Vol 11 (1) ◽  
pp. A60 ◽  
Author(s):  
Mu Xu ◽  
Zhensheng Jia ◽  
Jing Wang ◽  
L. Alberto Campos ◽  
Gee-Kung Chang
Keyword(s):  
Data Compression ◽  
Statistical Data ◽  
Radio Over Fiber ◽  
Digital Radio ◽  
Differential Coding

scholarly journals Performance Analysis of Data Compression using Lossless Run Length Encoding

2017 ◽  
Vol 10 (3) ◽  
pp. 703-707
Author(s):  
CHETAN R. DUDHAGARA ◽  
HASAMUKH B. PATEL
Keyword(s):  
Image Compression ◽  
Data Compression ◽  
Digital Media ◽  
Input Data ◽  
Statistical Data ◽  
Original Data ◽  
Modern Technology ◽  
Efficient Manner ◽  
Compression Algorithms ◽  
Run Length

In a recent era of modern technology, there are many problems for storage, retrieval and transmission of data. Data compression is necessary due to rapid growth of digital media and the subsequent need for reduce storage size and transmit the data in an effective and efficient manner over the networks. It reduces the transmission traffic on internet also. Data compression try to reduce the number of bits required to store digitally. The various data and image compression algorithms are widely use to reduce the original data bits into lesser number of bits. Lossless data and image compression is a special class of data compression. This algorithm involves in reducing numbers of bits by identifying and eliminating statistical data redundancy in input data. It is very simple and effective method. It provides good lossless compression of input data. This is useful on data that contains many consecutive runs of the same values. This paper presents the implementation of Run Length Encoding for data compression.

Knowledge-Based Decision Support for Diagnosis and Therapy: On the Multiple Usability of Patient Data

1989 ◽  
Vol 28 (02) ◽  
pp. 69-77 ◽  
Author(s):  
R. Haux
Keyword(s):  
Expert Systems ◽  
Statistical Data ◽  
Patient Data ◽  
Attribute Selection ◽  
Patient Specific ◽  
Statistical Data Analysis ◽  
Inference Mechanism ◽  
Diagnosis And Therapy ◽  
Knowledge Based ◽  
Clinical Registries

Abstract:Expert systems in medicine are frequently restricted to assisting the physician to derive a patient-specific diagnosis and therapy proposal. In many cases, however, there is a clinical need to use these patient data for other purposes as well. The intention of this paper is to show how and to what extent patient data in expert systems can additionally be used to create clinical registries and for statistical data analysis. At first, the pitfalls of goal-oriented mechanisms for the multiple usability of data are shown by means of an example. Then a data acquisition and inference mechanism is proposed, which includes a procedure for controlling selection bias, the so-called knowledge-based attribute selection. The functional view and the architectural view of expert systems suitable for the multiple usability of patient data is outlined in general and then by means of an application example. Finally, the ideas presented are discussed and compared with related approaches.

Confidentiality of Statistical Records: A Threat-Monitoring Scheme for On Line Dialogue

1976 ◽  
Vol 15 (01) ◽  
pp. 36-42 ◽  
Author(s):  
J. Schlörer
Keyword(s):  
Statistical Data ◽  
Cost Benefit ◽  
Data Bank ◽  
High Ratio ◽  
Point Of View ◽  
Data Sets ◽  
Monitoring Scheme ◽  
Access Controls ◽  
On Line ◽  
Bona Fide

From a statistical data bank containing only anonymous records, the records sometimes may be identified and then retrieved, as personal records, by on line dialogue. The risk mainly applies to statistical data sets representing populations, or samples with a high ratio n/N. On the other hand, access controls are unsatisfactory as a general means of protection for statistical data banks, which should be open to large user communities. A threat monitoring scheme is proposed, which will largely block the techniques for retrieval of complete records. If combined with additional measures (e.g., slight modifications of output), it may be expected to render, from a cost-benefit point of view, intrusion attempts by dialogue valueless, if not absolutely impossible. The bona fide user has to pay by some loss of information, but considerable flexibility in evaluation is retained. The proposal of controlled classification included in the scheme may also be useful for off line dialogue systems.

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