Data Extraction Techniques for Spreadsheet Records

Abstract Many accounting applications use spreadsheets as repositories of accounting records, and a common requirement is the need to extract specific information from them. This paper describes a number of techniques that accountants can use to perform such tasks directly using common spreadsheet tools. These techniques include (1) simple and advanced filtering techniques, (2) database functions, (3) methods for both simple and stratified sampling, and, (4) tools for finding duplicate or unmatched records.

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CCD Time-Series Photometry of Faint Astronomical Sources

International Astronomical Union Colloquium ◽

10.1017/s0252921100007715 ◽

1993 ◽

Vol 136 ◽

pp. 318-324 ◽

Cited By ~ 1

Author(s):

Steve B. Howell

Keyword(s):

Time Series ◽

Data Collection ◽

Light Curve ◽

Data Extraction ◽

High Signal ◽

Extraction Techniques ◽

Signal To Noise ◽

Noise Sources ◽

New Methods ◽

Area Of Interest

AbstractUsing CCDs to obtain time-series light curve information is an increasing area of interest in astronomy. For brighter, high signal-to-noise sources, the data collection and reduction procedures are very robust and easy to use. However, for fainter, low signal-to-noise objects we must resort to new methods. These include the use of optimum data extraction techniques, a fuller understanding of the CCD itself, and a more complete error model. This paper will provide a brief introduction to CCD time-series photometry and then explore the above new methods in relation to real observational situations.

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A Comparison of Web Data Extraction Techniques

2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT) ◽

10.1109/jeeit.2019.8717519 ◽

2019 ◽

Author(s):

Mosa Salah ◽

Basem Al Okush ◽

Mustafa Al Rifaee

Keyword(s):

Data Extraction ◽

Extraction Techniques ◽

Web Data ◽

Web Data Extraction

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An Overview of Data Extraction Techniques of Mobile Device

Digital Forensics (4n6) Journal ◽

10.46293/4n6/2020.02.03.16 ◽

2020 ◽

Author(s):

Ashish Suthar

Keyword(s):

Mobile Device ◽

Data Extraction ◽

Extraction Techniques

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Image-based continental shelf habitat mapping using novel automated data extraction techniques

Continental Shelf Research ◽

10.1016/j.csr.2012.06.003 ◽

2012 ◽

Vol 45 ◽

pp. 87-97 ◽

Cited By ~ 13

Author(s):

Jan Seiler ◽

Ariell Friedman ◽

Daniel Steinberg ◽

Neville Barrett ◽

Alan Williams ◽

...

Keyword(s):

Continental Shelf ◽

Data Extraction ◽

Habitat Mapping ◽

Extraction Techniques

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Advances in Multi-Signal Spectrum-Image Acquisition and Data Extraction Techniques involving Spectral Cathodoluminescence

Microscopy and Microanalysis ◽

10.1017/s1431927606069662 ◽

2006 ◽

Vol 12 (S02) ◽

pp. 1520-1521 ◽

Cited By ~ 1

Author(s):

SA Galloway ◽

PJ Thomas

Keyword(s):

Data Extraction ◽

Image Acquisition ◽

Signal Spectrum ◽

Extraction Techniques

Extended abstract of a paper presented at Microscopy and Microanalysis 2006 in Chicago, Illinois, USA, July 30 – August 3, 2005

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Web Harvesting

Advances in Data Mining and Database Management - Web Usage Mining Techniques and Applications Across Industries ◽

10.4018/978-1-5225-0613-3.ch014 ◽

2017 ◽

pp. 351-378 ◽

Cited By ~ 1

Author(s):

B. Umamageswari ◽

R. Kalpana

Keyword(s):

Web Mining ◽

Data Extraction ◽

Web Pages ◽

Extraction Techniques ◽

Web Data ◽

Web Data Extraction ◽

Region Extraction ◽

Universal Applicability ◽

Web Harvesting

Web mining is done on huge amounts of data extracted from WWW. Many researchers have developed several state-of-the-art approaches for web data extraction. So far in the literature, the focus is mainly on the techniques used for data region extraction. Applications which are fed with the extracted data, require fetching data spread across multiple web pages which should be crawled automatically. For this to happen, we need to extract not only data regions, but also the navigation links. Data extraction techniques are designed for specific HTML tags; which questions their universal applicability for carrying out information extraction from differently formatted web pages. This chapter focuses on various web data extraction techniques available for different kinds of data rich pages, classification of web data extraction techniques and comparison of those techniques across many useful dimensions.

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Applications of Machine Learning in Steganography for Data Protection and Privacy

Multidisciplinary Approach to Modern Digital Steganography - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-7998-7160-6.ch014 ◽

2021 ◽

pp. 306-325

Author(s):

Mahip M. Bartere ◽

Sneha Bohra ◽

Prashant Adakane ◽

B. Santhosh Kumar

Keyword(s):

Machine Learning ◽

Data Hiding ◽

Data Protection ◽

Data Security ◽

Data Extraction ◽

Original Data ◽

Extraction Techniques ◽

Reverse Engineer ◽

Applications Of Machine Learning

Data security is one of the most important aspects in today's scenario. Whenever we send our data from source to destination, data protection is one of the prime components. With the help of data hiding and data extraction techniques, we are able to provide the solution of different types of problems whenever we transfer our data. Steganography is a process where we can hide our data and maintain the quality of the image. At the same time, we think about data alteration. With the help of stegtanalysis method, we reverse engineer and extract the original data. In this chapter, data hiding and data extraction techniques are explained in the combination of machine learning architecture. The combination of steganography and steganalysis along with machine learning is used to identify protected data using different techniques.

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