SOCR LetterFrequencyData - Revision history

Dinov at 13:15, 21 October 2016

2016-10-21T13:15:00Z

Dinov at 22:11, 20 October 2016

2016-10-20T22:11:51Z

IvoDinov: /* Data Description */

2010-05-31T18:49:18Z

‎Data Description

IvoDinov: /* Data Description */ typo

2010-05-31T18:46:03Z

‎Data Description: typo

IvoDinov: /* Data Description */ typo

2010-05-31T18:45:21Z

‎Data Description: typo

IvoDinov: /* Graphs */ added a Charts applets link

2010-01-15T16:29:36Z

‎Graphs: added a Charts applets link

IvoDinov: /* Graphs */ fixed a typo in reference to StackedBarChartDemo3

2010-01-15T16:29:02Z

‎Graphs: fixed a typo in reference to StackedBarChartDemo3

IvoDinov: added the Histogram and Bar Charts images/links at the bottom

2009-11-02T19:41:17Z

added the Histogram and Bar Charts images/links at the bottom

IvoDinov: /* Data Table */ Changed the bottom row from TOtal to (complementary) others

2009-11-02T18:52:23Z

‎Data Table: Changed the bottom row from TOtal to (complementary) others

IvoDinov: /* SOCR Data - Letter Frequency Data */

2009-11-02T03:47:19Z

‎SOCR Data - Letter Frequency Data

← Older revision		Revision as of 13:15, 21 October 2016
Line 82:		Line 82:

	=== See also===		=== See also===
		+	[[Image:SOCR_Data_Dinov_EnglishLetterFrequency_Fig2.png\|150px\|thumbnail\|right\| [http://link.springer.com/article/10.1007/BF00114162 20,000 Handwritten Letters] ]]
	* [https://umich.instructure.com/courses/38100/files/folder/Case_Studies/16_HandwrittenLetters A machine learning based case-study for optical character recognition (OCR) from handwritten notes].		* [https://umich.instructure.com/courses/38100/files/folder/Case_Studies/16_HandwrittenLetters A machine learning based case-study for optical character recognition (OCR) from handwritten notes].

← Older revision		Revision as of 22:11, 20 October 2016
Line 81:		Line 81:
	<center>[[Image:SOCR_Data_Dinov_EnglishLetterFrequency1.png\|400px]]</center>		<center>[[Image:SOCR_Data_Dinov_EnglishLetterFrequency1.png\|400px]]</center>

		+	=== See also===
		+	* [https://umich.instructure.com/courses/38100/files/folder/Case_Studies/16_HandwrittenLetters A machine learning based case-study for optical character recognition (OCR) from handwritten notes].

	<hr>		<hr>

@@ Line 4: / Line 4: @@
 [[Image:SOCR_Data_Dinov_EnglishLetterFrequency.png|150px|thumbnail|right| [http://en.wikipedia.org/wiki/Letter_frequency English Letter Frequencies] ]]
-The data table below present the average frequencies of the 26 most common Latin letters for different languages. Letter frequencies in text are studied in cryptography. There is no ''exact'' letter frequency distribution underlies a given language, since all writers write slightly differently. Modern International [http://en.wikipedia.org/wiki/Morse_code Morse code] encodes the most frequent letters with the shortest symbols; arranging the Morse alphabet into groups of letters that require equal amounts of time to transmit, and then sorting these groups in increasing order. Similar ideas are used in modern data-compression techniques such as [http://en.wikipedia.org/wiki/Huffman_coding Huffman coding].
+The data table below present the average frequencies of the 26 most common Latin letters for different languages. Letter frequencies in text are studied in cryptography. The exact letter frequency distribution underling a given language is unknown and varies with time, since all writers tend to write slightly differently and are affected by their culture. Modern International [http://en.wikipedia.org/wiki/Morse_code Morse code] encodes the most frequent letters with the shortest symbols; arranging the Morse alphabet into groups of letters that require equal amounts of time to transmit, and then sorting these groups in increasing order. Similar ideas are used in modern data-compression techniques such as [http://en.wikipedia.org/wiki/Huffman_coding Huffman coding].
 Letter frequencies, like word frequencies, tend to vary by writer, subject and language. Accurate average letter frequencies are obtained by analyzing large amounts of ''representative'' text.

@@ Line 4: / Line 4: @@
 [[Image:SOCR_Data_Dinov_EnglishLetterFrequency.png|150px|thumbnail|right| [http://en.wikipedia.org/wiki/Letter_frequency English Letter Frequencies] ]]
-The data table below present the average frequencies of the 26 most common Latin letters for different languages. Letter frequencies in text is studied in cryptography. There is no ''exact'' letter frequency distribution underlies a given language, since all writers write slightly differently. Modern International [http://en.wikipedia.org/wiki/Morse_code Morse code] encodes the most frequent letters with the shortest symbols; arranging the Morse alphabet into groups of letters that require equal amounts of time to transmit, and then sorting these groups in increasing order. Similar ideas are used in modern data-compression techniques such as [http://en.wikipedia.org/wiki/Huffman_coding Huffman coding].
+The data table below present the average frequencies of the 26 most common Latin letters for different languages. Letter frequencies in text are studied in cryptography. There is no ''exact'' letter frequency distribution underlies a given language, since all writers write slightly differently. Modern International [http://en.wikipedia.org/wiki/Morse_code Morse code] encodes the most frequent letters with the shortest symbols; arranging the Morse alphabet into groups of letters that require equal amounts of time to transmit, and then sorting these groups in increasing order. Similar ideas are used in modern data-compression techniques such as [http://en.wikipedia.org/wiki/Huffman_coding Huffman coding].
 Letter frequencies, like word frequencies, tend to vary by writer, subject and language. Accurate average letter frequencies are obtained by analyzing large amounts of ''representative'' text.

@@ Line 4: / Line 4: @@
 [[Image:SOCR_Data_Dinov_EnglishLetterFrequency.png|150px|thumbnail|right| [http://en.wikipedia.org/wiki/Letter_frequency English Letter Frequencies] ]]
-The data table below present the average frequencies of the 26 most common Latin letters for different languages. Letter frequenciess in text is studied in cryptography. There is no ''exact'' letter frequency distribution underlies a given language, since all writers write slightly differently. Modern International [http://en.wikipedia.org/wiki/Morse_code Morse code] encodes the most frequent letters with the shortest symbols; arranging the Morse alphabet into groups of letters that require equal amounts of time to transmit, and then sorting these groups in increasing order. Similar ideas are used in modern data-compression techniques such as [http://en.wikipedia.org/wiki/Huffman_coding Huffman coding].
+The data table below present the average frequencies of the 26 most common Latin letters for different languages. Letter frequencies in text is studied in cryptography. There is no ''exact'' letter frequency distribution underlies a given language, since all writers write slightly differently. Modern International [http://en.wikipedia.org/wiki/Morse_code Morse code] encodes the most frequent letters with the shortest symbols; arranging the Morse alphabet into groups of letters that require equal amounts of time to transmit, and then sorting these groups in increasing order. Similar ideas are used in modern data-compression techniques such as [http://en.wikipedia.org/wiki/Huffman_coding Huffman coding].
 Letter frequencies, like word frequencies, tend to vary by writer, subject and language. Accurate average letter frequencies are obtained by analyzing large amounts of ''representative'' text.

@@ Line 78: / Line 78: @@
 <center>[[Image:SOCR_Data_Dinov_EnglishLetterFrequency.png|400px]]</center>
-* [[SOCR_EduMaterials_Activities_BarCharts_CategoryPlot | Stacked Bar-Chart]] (StackedBarChartDemo3, under BarCharts --> CategoryPlots) of all letters across each language
+* [[SOCR_EduMaterials_Activities_BarCharts_CategoryPlot | Stacked Bar-Chart]] ([http://socr.ucla.edu/htmls/SOCR_Charts.html StackedBarChartDemo3, under BarCharts --> CategoryPlots]) of all letters across each language
 <center>[[Image:SOCR_Data_Dinov_EnglishLetterFrequency1.png|400px]]</center>

@@ Line 70: / Line 70: @@
 | z  || 0.00 || 0.00 || 0.01 || 0.01 || 0.00 || 0.01 || 0.00 || 0.02 || 0.00 || 0.05 || 0.00 || 0.01 || 0.01
 |-
-| total || 1.00 || 0.97 || 1.00 || 1.00 || 1.00 || 0.98 || 1.00 || 0.88 || 0.94 || 0.80 || 1.00 || 1.00 || 0.96
+| Others || 0 || 0.03 || 0 || 0 || 0 || 0.02 || 0 || 0.12 || 0.06 || 0.2 || 0 || 0 || 0.04
 |}
 </center>

← Older revision		Revision as of 03:47, 2 November 2009
Line 1:		Line 1:
−	== [[SOCR_Data \|SOCR Data]] - ~~Letter~~ Frequency ~~Data~~==	+	== [[SOCR_Data \|SOCR Data]] - Latin Letters Frequency Distributions in Different Languages==

	===Data Description===		===Data Description===