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This is the mk-string-metrics Reference Manual, version 0.1.2, generated automatically by Declt version 2.4 "Will Decker" on Wed Jun 20 12:17:32 2018 GMT+0.
| • Introduction: | What mk-string-metrics is all about | |
| • Systems: | The systems documentation | |
| • Files: | The files documentation | |
| • Packages: | The packages documentation | |
| • Definitions: | The symbols documentation | |
| • Indexes: | Concepts, functions, variables and data types |
This library implements efficient algorithms that calculate various string metrics in Common Lisp:
Copy files of this library in any place where ASDF can find them. Then you can use it in system definitions and ASDF will take care of the rest.
Via Quicklisp (recommended):
(ql:quickload "mk-string-metrics")
damerau-levenshtein x y
Calculate Damerau-Levenshtein distance between two given strings x and
y.
hamming x y
Calculate Hamming distance between two given strings x and y, they have
to be of the same length.
jaccard x y
Calculate Jaccard similarity coefficient for two strings x and y.
Returned value is in range from 0 (no similarity) to 1 (exact match).
jaro x y
Calculate Jaro distance between two strings x and y. Returned value is
in range from 0 (no similarity) to 1 (exact match).
jaro-winkler x y
Calculate Jaro-Winkler distance between two strings x and y. Returned
value is in range from 0 (no similarity) to 1 (exact match).
levenshtein x y
Calculate Levenshtein distance between two given strings x and y.
norm-damerau-levenshtein x y
Return normalized Damerau-Levenshtein distance between x and y. Result
is a real number from 0 to 1, where 0 signifies no similarity between
the strings, while 1 means exact match.
norm-levenshtein x y
Return normalized Levenshtein distance between x and y. Result is a real
number from 0 to 1, where 0 signifies no similarity between the
strings, while 1 means exact match.
overlap x y
This function calculates overlap coefficient between two given strings x
and y. Returned value is in range from 0 (no similarity) to 1 (exact
match).
Copyright © 2014–2018 Mark Karpov
Distributed under MIT Licens
Next: Files, Previous: Introduction, Up: Top [Contents][Index]
The main system appears first, followed by any subsystem dependency.
| • The mk-string-metrics system: |
Mark Karpov
MIT
efficient implementations of various string metric algorithms
0.1.2
mk-string-metrics.asd (file)
mk-string-metrics.lisp (file)
Files are sorted by type and then listed depth-first from the systems components trees.
| • Lisp files: |
| • The mk-string-metrics.asd file: | ||
| • The mk-string-metrics/mk-string-metrics.lisp file: |
Next: The mk-string-metrics/mk-string-metrics<dot>lisp file, Previous: Lisp files, Up: Lisp files [Contents][Index]
mk-string-metrics.asd
mk-string-metrics (system)
Previous: The mk-string-metrics<dot>asd file, Up: Lisp files [Contents][Index]
mk-string-metrics (system)
mk-string-metrics.lisp
Next: Definitions, Previous: Files, Up: Top [Contents][Index]
Packages are listed by definition order.
| • The mk-string-metrics package: |
mk-string-metrics.lisp (file)
mksm
common-lisp
Definitions are sorted by export status, category, package, and then by lexicographic order.
| • Exported definitions: | ||
| • Internal definitions: |
Next: Internal definitions, Previous: Definitions, Up: Definitions [Contents][Index]
| • Exported functions: |
Previous: Exported definitions, Up: Exported definitions [Contents][Index]
Calculate Damerau-Levenshtein distance between two given strings X and Y.
mk-string-metrics.lisp (file)
Calculate Hamming distance between two given strings X and Y, they have to be of the same length.
mk-string-metrics.lisp (file)
Calculate Jaccard similarity coefficient for two strings X and
Y. Returned value is in range from 0 (no similarity) to 1 (exact match).
mk-string-metrics.lisp (file)
Calculate Jaro distance between two strings X and Y. Returned value is in range from 0 (no similarity) to 1 (exact match).
mk-string-metrics.lisp (file)
Calculate Jaro-Winkler distance between two strings X and Y. Returned value is in range from 0 (no similarity) to 1 (exact match).
mk-string-metrics.lisp (file)
Calculate Levenshtein distance between two given strings X and Y.
mk-string-metrics.lisp (file)
Return normalized Damerau-Levenshtein distance between X and Y. Result is a real number from 0 to 1, where 0 signifies no similarity between the strings, while 1 means exact match.
mk-string-metrics.lisp (file)
Return normalized Levenshtein distance between X and Y. Result is a real number from 0 to 1, where 0 signifies no similarity between the strings, while 1 means exact match.
mk-string-metrics.lisp (file)
This function calculates overlap coefficient between two given strings X and Y. Returned value is in range from 0 (no similarity) to 1 (exact match).
mk-string-metrics.lisp (file)
Previous: Exported definitions, Up: Definitions [Contents][Index]
| • Internal functions: | ||
| • Internal types: |
Next: Internal types, Previous: Internal definitions, Up: Internal definitions [Contents][Index]
Check if CHAR is in STR. This function is supposed to be inlined.
mk-string-metrics.lisp (file)
Returns length of intersection of two strings X and Y. This function is supposed to be inlined.
mk-string-metrics.lisp (file)
Calculate length of common prefix for strings X and Y.
mk-string-metrics.lisp (file)
Convert string STR into a set. This function is supposed to be inlined.
mk-string-metrics.lisp (file)
Returns length of union of two strings X and Y. This function is supposed to be inlined.
mk-string-metrics.lisp (file)
Previous: Internal functions, Up: Internal definitions [Contents][Index]
mk-string-metrics.lisp (file)
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| • Concept index: | ||
| • Function index: | ||
| • Variable index: | ||
| • Data type index: |
Next: Function index, Previous: Indexes, Up: Indexes [Contents][Index]
| Jump to: | F L M |
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| Jump to: | F L M |
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Next: Variable index, Previous: Concept index, Up: Indexes [Contents][Index]
| Jump to: | D F H I J L N O P S U |
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| Jump to: | D F H I J L N O P S U |
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Next: Data type index, Previous: Function index, Up: Indexes [Contents][Index]
Previous: Variable index, Up: Indexes [Contents][Index]
| Jump to: | A M P S T |
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| Jump to: | A M P S T |
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