CommonPattern: Discovers common patterns in a group of strings - full version

Description

CommonPattern finds common patterns shared by a group of strings.

It is the extended version of CommonPatt and the users have more options.

A common pattern is defined as a substring with the minimum length of three that occurs at least twice among a group of strings.

Usage

CommonPattern(strings.vec, low = 5, high = 25, interval = 5, eveChar.df)

Arguments

strings.vec

String vector.

low

The lowest cutoff. It is the minimum percentage of the occurrence of patterns that the user specifies. The default value is 5.

high

The highest cutoff, which is the maximum percentage of the occurrence of patterns that the user specifies. The default value is 25.

interval

The increment percentage from the lowest to the highest cutoff. The default value is 5.

eveChar.df

Data frame that stores the event name - character conversion key (optional).

Value

A set of .txt files are exported into the current directory that contain patterns, lengths, percents of patterns, and converted event names if eveChar.fle is included. The names of these files are the name of strings.vec appended with the percentages. In addition, a file with all patterns that occurred at least 2 times is exported.

row name - The initial order of substrings, which can be ignored.

Column 1 - Pattern: common pattern.

Column 2 - Freq_grp: the overall frequency (times of occurrence) of each pattern.

Column 3 - Percent_grp: the ratio of Freq_grp to the number of original strings, in percent.

Column 4 - Length: the length (i.e., number of characters) of pattern.

Column 5 - Freq_str: similar to Freq_grp; but each pattern is counted only once in a string even if the string contains that pattern multiple times.

Column 6 - Percent_str: similar to Percent; but each pattern is counted only once in a string if this string contains the pattern.

Column 7 - Event_name (optional): sequence of event names converted back from pattern string

Data is sorted by Length, then Freq_grp, in decreasing order.

Details

The arguments 'low', 'high' and 'interval' range from 0 to 100 in percentage.

References

1. H. Tang; E. Day; L. Kendhammer; J. N. Moore; S. A. Brown; N. J. Pienta. (2016). Eye movement patterns in solving science ordering problems. Journal of eye movement research, 9(3), 1-13.

2. J. J. Topczewski; A. M. Topczewski; H. Tang; L. Kendhammer; N. J. Pienta.(2017). NMR Spectra through the eyes of a student: eye tracking applied to NMR items. Journal of chemical education, 94(1), 29-37.

3. J. M. West; A. H. Haake; E. P. Rozanksi; K. S. Karn. (2006). EyePatterns: Software for identifying patterns and similarities across fixation sequences. In Proceedings of the Symposium on Eye-tracking Research & Applications, ACM Press, New York, 149-154.

Examples

Run this code

# NOT RUN {
# simple strings
strs.vec <- c("ABCDdefABCDa", "def123DC", "123aABCD", "ACD13", "AC1ABC", "3123fe")
CommonPattern(strs.vec, low = 30, high = 50, interval = 20)

# None-default cutoff values, with conversion back
data(eventChar.df)
data(str1)
s0 <- str1[5:15]
CommonPattern(s0, low = 20, high = 30, interval = 10, eveChar.df = eventChar.df)
# }

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