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simetrics.r

REBOL [ Title: "Similarity Metrics" File: %simetrics.r Date: 19-Feb-2006 Purpose: "Toolkit of string distance metrics." Version: 0.5.0 Library: [ Level: 'intermediate Platform: 'all Type: [function module tool] Domain: [ai math parse scientific text text-processing] tested-under: [ core 2.5.6.3.1 on [WXP] "fvz" ] Support: none License: 'bsd See-also: none ] Author: "Francois Vanzeveren (fvz)" History: [ 0.5.0 [19-Feb-2006 { Improved interface for 'accumulate-statistics and 'get-similarity: the corpus statistics are returned to the client and must be passed back to 'get-similarity for token-base metrics. } "fvz"] 0.4.1 [19-Feb-2006 { - BUG FIX: recursive calls to get-similarity/jaro(-winkler) must be done with 'case and 'strict refinements. - Performance improvement: Jaccard metric accepts pre-tokenized source string. } "fvz"] 0.4.0 [18-Feb-2006 { - NEW METRIC: Hybrid Jaccard - Jaro - NEW METRIC: Hybrid Jaccard - Jaro-Winkler} "fvz"] 0.3.2 [18-Feb-2006 { - Some code improvement for 'sm-multiply 'sm-divide and 'sm-max (thanks to Marco) - NEW TOKENIZER: 'tokenize-text } "fvz"] 0.3.1 [18-Feb-2006 { - Interface change for hybrid token-based metrics - BUG FIX: remove folders in the corpus} "fvz"] 0.3.0 [17-Feb-2006 { NEW METRIC: Term Frequency-Inverse Document Frequency NEW METRIC: Term Frequency-Inverse Document Frequency with Jaro (slow!) NEW METRIC: Term Frequency-Inverse Document Frequency with Jaro-Winkler (slow!) } "fvz"] 0.2.1 [12-Feb-2006 "BUG FIX: in simetrics/ctx-jaro/get-prefix-length. Thanks to Sunanda from Rebol.org" "fvz"] 0.2.0 [11-Feb-2006 { - NEW METRIC: Jaccard Similarity - /case refinement: matching is case sensitive - /strict refinement: matching is non-english characters sensitive } "fvz"] 0.1.1 [11-Feb-2006 { - The script is now compatible with older versions of rebol (i.e. < 2.6.x) - BUG FIX Levenshtein: the subtitution's cost was not properly computed from the deletion and insertion's costs - Levenshtein: result normalized - NEW METRIC: Jaro and Jaro-Winkler metrics - New interface: 'get-similarity is the unique entry point to all metrics } "fvz"] 0.1.0 [10-Feb-2006 "Levenshtein distance implemented" "fvz"] 0.0.1 [9-Feb-2006 "Created this file" "fvz"] ] ] simetrics: context [ set 'accumulate-statistics function [ "Accumulates and returns the statistics on the corpus of documents." corpus [file! block! hash!] "Path to where the collection of documents (the corpus) is stored, or the corpus itself!" tokenize [function!] "Splits a string into tokens." ] [ corpus-path document-frequency ; maps each word to the number of documents in which it appears ; maps each document d of the corpus D to the number of times each ; token/word w appears in d and the weight of w in d ; The structure is: ; [ ; d1 [ ; w1 [frequency weight] ; w2 [frequency weight] ; ... ; ] ; d2 [ ; w1 [frequency weight] ; w2 [frequency weight] ; ... ; ] ; ... ; ] term-stats d-stats tokens prev-token pointer count corpus-size w w-stats w-count w-weight err ] [ corpus-path: none if file? corpus [ corpus-path: corpus corpus: read corpus-path forall corpus [ either dir? join corpus-path first corpus [corpus: back remove corpus ] [insert corpus: next corpus none] ] corpus: head corpus ] document-frequency: make hash! [] term-stats: make hash! [] d-stats: make hash! [] ; The following loop count the frequencies of each token: ; * the number of documents in which a token w appears (document-frequency) ; * within each document, the frequency of token w (term-stats) foreach [doc-name doc] corpus [ tokens: sort tokenize either doc [copy doc] [read join corpus-path doc-name] prev-token: none forall tokens [ either not all [prev-token equal? prev-token first tokens] [ ; increment document frequency counts pointer: find document-frequency first tokens either pointer [ count: add 1 first next pointer change next pointer count ] [ repend document-frequency [first tokens 1] ] if prev-token [append d-stats compose/deep [(prev-token) [(w-count) 0]]] w-count: 1 ] [ w-count: add w-count 1 ] prev-token: first tokens ] repend term-stats [doc-name d-stats] d-stats: make hash! [] ] corpus: head corpus ; The following computes the weight of each token w in each document of the corpus (term-stats) corpus-size: divide length? corpus 2 forskip term-stats 2 [ tokens: second term-stats forskip tokens 2 [ w: first tokens w-stats: second tokens w-count: first w-stats w-weight: multiply w-count log-10 divide corpus-size select document-frequency w change next w-stats w-weight ] ] term-stats: head term-stats return reduce [document-frequency term-stats] ] set 'get-similarity function [ {Measures the similarity of two strings.} s [string! block!] "Source string or token multiset. Token multiset is ONLY for Jaccard metric!" /jaro {Measures the similarity of two strings based on the number and the order of common characters between them.} t-jaro [string!] "Target string" /jaro-winkler {Variant of the Jaro metric adjusting the weighting for common prefixes.} t-jaro-winkler [string!] "Target string" /levenshtein {Measures the distance (i.e. similarity) between two strings. The distance is the number of edit operations (deletions, insertions, substitutions) required to transform the source string into the target string.} t-levenshtein [string!] "Target string" /levenstein {See /levenshtein.} t-levenstein [string!] "Target string" /del-cost dc [number!] "Deletion's cost. ONLY with /levenshtein refinement." /ins-cost ic [number!] "Insertion's cost. ONLY with /levenshtein refinement." /sub-cost sc [number!] "Substitution's cost. ONLY with /levenshtein refinement." /case "Characters are case-sensitive." /strict "Matching is non-english characters sensitive." ; Token-Based Metrics /jaccard {Token based distance function. The Jaccard similarity between word sets S and T is simply |S intersect T| / |S union T|} t-jaccard [string!] "Target string" tokenize-jaccard [function!] "Splits a string into tokens." /tfidf "Term Frequency-Inverse Document Frequency Metric" corpus-stats [block!] "Corpus statistics as build and returned by 'accumulate-statistics." tokenize-tfidf [function!] "Splits a string into tokens." ; Hybrid token-based metrics /jaro-hybrid "Hybrid token-based and Jaro-Winkler metric. ONLY with token-based metric." /jaro-winkler-hybrid "Hybrid token-based and Jaro-Winkler metric. ONLY with token-based metric." ] [t tokenize] [ t: any [t-jaro t-jaro-winkler t-levenshtein t-levenstein t-jaccard] tokenize: any [:tokenize-jaccard :tokenize-tfidf] ; TOKEN-BASED METRICS if jaccard [ use [s-bag t-bag current-score max-score score] [ s-bag: unique either block? s [s] [tokenize s] t-bag: unique tokenize t either any [jaro-hybrid jaro-winkler-hybrid] [ score: 0 forall s-bag [ current-score: max-score: 0 forall t-bag [ if jaro-hybrid [current-score: get-similarity/jaro/case/strict first s-bag first t-bag] if jaro-winkler-hybrid [current-score: get-similarity/jaro-winkler/case/strict first s-bag first t-bag] max-score: max current-score max-score ] t-bag: head t-bag score: add score max-score ] s-bag: head s-bag t-bag: head t-bag return divide score max length? s-bag length? t-bag ] [ return divide length? intersect s-bag t-bag length? union s-bag t-bag ] ] ] if tfidf [ use [document-frequency term-stats retval q-tok f-score score tokens j-score w-stats q-tok-scores w-scores d-frequency ] [ document-frequency: first corpus-stats term-stats: second corpus-stats retval: make hash! [] q-tok: sort unique tokenize s q-tok-scores: make hash! [] if any [jaro-hybrid jaro-winkler-hybrid] [ d-frequency: document-frequency forall q-tok [ w-scores: make hash! [] forskip d-frequency 2 [ if jaro-hybrid [j-score: get-similarity/jaro/case/strict first q-tok first d-frequency] if jaro-winkler-hybrid [j-score: get-similarity/jaro-winkler/case/strict first q-tok first d-frequency] if greater-or-equal? j-score 0.9 [repend w-scores [first d-frequency j-score]] ] repend q-tok-scores [first q-tok w-scores] d-frequency: head d-frequency ] ] f-score: select reduce [ any [jaro-hybrid jaro-winkler-hybrid] [ w-scores: select q-tok-scores first q-tok forskip w-scores 2 [ if w-stats: select tokens first w-scores [ j-score: second w-scores score: add score multiply j-score second w-stats ] ] ] true [ w-stats: select tokens first q-tok score: add score either w-stats [second w-stats] [0] ] ] true forskip term-stats 2 [ score: 0 tokens: second term-stats forall q-tok [ do f-score ] repend retval [score first term-stats] q-tok: head q-tok ] term-stats: head term-stats return sort/skip/reverse retval 2 ] ] ; NON TOKEN-BASED METRICS trim s: copy any [s ""] trim t: copy any [t ""] if not case [ lowercase s lowercase t ] if not strict [ parse/all s [ any [ mark: alpha-ext (change mark select/case alpha-map first mark) | skip ] ] parse/all t [ any [ mark: alpha-ext (change mark select/case alpha-map first mark) | skip ] ] ] if jaro [ use [half-len s-common t-common transpositions] [ ; get half the length of the string rounded up - (this is the distance used for acceptable transpositions) half-len: to-integer divide min length? s length? t 2 ; get common characters s-common: ctx-jaro/get-common-characters s t half-len t-common: ctx-jaro/get-common-characters t s half-len ; Check for empty and/or different size common strings if any [ not-equal? length? s-common length? t-common empty? s-common empty? t-common ] [return 0] ; Get the number of transpositions ; A transposition for s-common, t-common is a position i ; such that s-common[i] <> t-common[i] transpositions: 0 for i 1 length? s-common 1 [ if not-equal? s-common/:i t-common/:i [transpositions: add transpositions 1] ] transpositions: divide transpositions 2 return divide add add divide length? s-common length? s divide length? t-common length? t divide subtract length? s-common transpositions length? s-common 3 ] ] if jaro-winkler [ use [dist prefix-length] [ dist: get-similarity/jaro/case/strict s t ; This extension modifies the weights of poorly matching pairs s, t which share a common prefix prefix-length: ctx-jaro/get-prefix-length s t return add dist multiply multiply prefix-length ctx-jaro/PREFIXADUSTMENTSCALE subtract 1 dist ] ] if any [levenshtein levenstein] [ use [dist max-len] [ ; 0.1.1 either any [ins-cost del-cost sub-cost] [ sc: any [sc sm-multiply sm-max dc ic 2 2] dc: any [dc ic sm-divide sc 2] ic: any [ic dc] ] [ sc: dc: ic: 1 ] dist: ctx-levenshtein/get-distance back tail s back tail t array reduce [length? t length? s] dc ic sc ; get the max possible levenstein distance score for string max-len: max length? s length? t if zero? max-len [return 1] ; as both strings identically zero length ; return actual / possible levenstein distance to get 0-1 range subtract 1 divide dist max-len ] ] ] sm-divide: func [ "Returns the first value divided by the second." value1 [number! pair! char! money! time! tuple! none!] value2 [number! pair! char! money! time! tuple! none!] ] [ all [ value1 value2 divide value1 value2 ] ] sm-multiply: func [ "Returns the first value multiplied by the second." value1 [number! pair! char! money! time! tuple! none!] value2 [number! pair! char! money! time! tuple! none!] ] [ all [ value1 value2 multiply value1 value2 ] ] sm-max: func [ "Returns the greater of the two values." value1 [number! pair! char! money! date! time! tuple! series! none!] value2 [number! pair! char! money! date! time! tuple! series! none!] ] [ all [ value1: any [value1 value2] value2: any [value2 value1] max value1 value2 ] ] alpha-map: make block! reduce [ make char! 131 make char! 102 ; to f make char! 138 make char! 83 ; to S make char! 142 make char! 90 ; to Z make char! 154 make char! 115 ; to s make char! 158 make char! 122 ; to z make char! 159 make char! 89 ; to Y make char! 192 make char! 65 ; to A make char! 193 make char! 65 ; to A make char! 194 make char! 65 ; to A make char! 195 make char! 65 ; to A make char! 196 make char! 65 ; to A make char! 197 make char! 65 ; to A make char! 199 make char! 67 ; to C make char! 200 make char! 69 ; to E make char! 201 make char! 69 ; to E make char! 202 make char! 69 ; to E make char! 203 make char! 69 ; to E make char! 204 make char! 73 ; to I make char! 205 make char! 73 ; to I make char! 206 make char! 73 ; to I make char! 207 make char! 73 ; to I make char! 208 make char! 68 ; to D make char! 209 make char! 78 ; to N make char! 210 make char! 79 ; to O make char! 211 make char! 79 ; to O make char! 212 make char! 79 ; to O make char! 213 make char! 79 ; to O make char! 214 make char! 79 ; to O make char! 217 make char! 85 ; to U make char! 218 make char! 85 ; to U make char! 219 make char! 85 ; to U make char! 220 make char! 85 ; to U make char! 221 make char! 89 ; to Y make char! 224 make char! 97 ; to a make char! 225 make char! 97 ; to a make char! 226 make char! 97 ; to a make char! 227 make char! 97 ; to a make char! 228 make char! 97 ; to a make char! 229 make char! 97 ; to a make char! 231 make char! 99 ; to c make char! 232 make char! 101 ; to e make char! 233 make char! 101 ; to e make char! 234 make char! 101 ; to e make char! 235 make char! 101 ; to e make char! 236 make char! 105 ; to i make char! 237 make char! 105 ; to i make char! 238 make char! 105 ; to i make char! 239 make char! 105 ; to i make char! 241 make char! 110 ; to n make char! 242 make char! 111 ; to o make char! 243 make char! 111 ; to o make char! 244 make char! 111 ; to o make char! 245 make char! 111 ; to o make char! 246 make char! 111 ; to o make char! 249 make char! 117 ; to u make char! 250 make char! 117 ; to u make char! 251 make char! 117 ; to u make char! 252 make char! 117 ; to u make char! 253 make char! 121 ; to y make char! 255 make char! 121 ; to y ] alpha-ext: make block! [] forskip alpha-map 2 [ append alpha-ext first alpha-map ] alpha-map: head alpha-map ; for compatibility with Rebol/Core < 2.6.x ; Charsets digit: charset [#"0" - #"9"] alpha-ext: charset alpha-ext alpha: charset [#"A" - #"Z" #"a" - #"z"] alphanum: union alpha digit space: charset reduce [#" " newline crlf tab] ctx-jaro: context [ ;maximum prefix length to use. MINPREFIXTESTLENGTH: 6 ;prefix adjustment scale. PREFIXADUSTMENTSCALE: 0.1 get-common-characters: func [ {Returns a string of characters from string1 within string2 if they are of a given distance seperation from the position in string1} string1 [string!] string2 [string!] distance-sep [integer!] /local return-commons pos str ] [ ; create a return string of characters return-commons: copy "" ; create a copy of string2 for processing string2: copy string2 ; iterate over string1 forall string1 [ if found? str: find/part at string2 add 1 pos: subtract index? string1 distance-sep first string1 subtract add multiply distance-sep 2 min pos 0 1 [ ; append character found append return-commons first string1 ; alter copied string2 for processing change/part str to-char 0 1 ] string2: head string2 ] return-commons ] get-prefix-length: func [ "Returns the prefix length found of common characters at the begining of the strings." string1 [string!] string2 [string!] /local n ] [ n: first minimum-of reduce [MINPREFIXTESTLENGTH length? string1 length? string2] for i 1 n 1 [ ; check the prefix is the same so far if not-equal? string1/:i string2/:i [ ; not the same so return as far as got return subtract i 1 ] ] ; 0.2.1 return n ; first n characters are the same ] ] ctx-levenshtein: context [ get-distance: function [ s [string!] "Source string" t [string!] "Target string" m [block!] dc [number!] "Deletion's cost" ic [number!] "Insertion's cost" sc [number!] "Substitution's cost" ] [ letter-copy letter-substitute letter-insert letter-delete i j ] [ if empty? head s [return length? head t] if empty? head t [return length? head s] ; 0.1.1 ; if m/(index? t)/(index? s) [return m/(index? t)/(index? s)] j: index? t i: index? s if m/:j/:i [return m/:j/:i] letter-copy: letter-substitute: letter-insert: letter-delete: 1E+99 ; Copy t[j] to s[i] if equal? first s first t [ letter-copy: do select reduce [ all [head? s head? t] [0] true [get-distance back s back t m dc ic sc] ] true ] ; Substitute t[j] for s[i] letter-substitute: add sc do select reduce [ all [head? s head? t] [0] head? s [subtract index? t 1] head? t [subtract index? s 1] true [get-distance back s back t m dc ic sc] ] true ; Insert the letter t[j] letter-insert: add ic do select reduce [ head? t [index? s] true [get-distance s back t m dc ic sc] ] true ; Delete the letter s[i] letter-delete: add dc do select reduce [ head? s [index? t] true [get-distance back s t m dc ic sc] ] true ; 0.1.1 ; m/(index? t)/(index? s): first minimum-of reduce [letter-copy letter-substitute letter-insert letter-delete] poke m/:j i first minimum-of reduce [letter-copy letter-substitute letter-insert letter-delete] m/:j/:i ] ] ] ; Sample tokenizers tokenize-rebol-script: func [ "Converts a string to a token multiset (where each token is a word)." str [string!] /local rebol-punctuation tokens t-alpha t-digit char mark space alpha-ext alpha digit ] [ space: simetrics/space alpha-ext: simetrics/alpha-ext alpha: simetrics/alpha digit: simetrics/digit rebol-punctuation: charset "-!?~" tokens: make block! [] t-alpha: copy "" t-digit: copy "" parse/all str [ any [ "64#{" thru "}" | copy char rebol-punctuation ( if not empty? t-alpha [append t-alpha char] if not empty? t-digit [ append tokens t-digit t-digit: copy "" ] ) | copy char space ( if not empty? t-alpha [ append tokens t-alpha t-alpha: copy "" ] if not empty? t-digit [ append tokens t-digit t-digit: copy "" ] ) | copy char alpha-ext ( if not empty? t-digit [ append tokens t-digit t-digit: copy "" ] lowercase char char: select/case simetrics/alpha-map first char append t-alpha char ) | copy char alpha ( if not empty? t-digit [ append tokens t-digit t-digit: copy "" ] lowercase char append t-alpha char ) | copy char digit ( either not empty? t-alpha [ append t-alpha char ] [ append t-digit char ] ) | mark: ( if not empty? t-alpha [ append tokens t-alpha t-alpha: copy "" ] if not empty? t-digit [ append tokens t-digit t-digit: copy "" ] ) skip ] ] return tokens ] tokenize-rebol-script-query: func [ "Converts a string to a token multiset (where each token is a word)." str [string!] /local tokens ] [ tokens: tokenize-rebol-script str return tokens ] tokenize-text: func [ str [string!] /local rebol-punctuation tokens t-alpha t-digit char mark space alpha-ext alpha digit ] [ space: simetrics/space alpha-ext: simetrics/alpha-ext alpha: simetrics/alpha digit: simetrics/digit tokens: make block! [] t-alpha: copy "" t-digit: copy "" parse/all str [ any [ copy char space ( if not empty? t-alpha [ append tokens t-alpha t-alpha: copy "" ] if not empty? t-digit [ append tokens t-digit t-digit: copy "" ] ) | copy char alpha-ext ( if not empty? t-digit [ append tokens t-digit t-digit: copy "" ] lowercase char char: select/case simetrics/alpha-map first char append t-alpha char ) | copy char alpha ( if not empty? t-digit [ append tokens t-digit t-digit: copy "" ] lowercase char append t-alpha char ) | copy char digit ( either not empty? t-alpha [ append t-alpha char ] [ append t-digit char ] ) | mark: ( if not empty? t-alpha [ append tokens t-alpha t-alpha: copy "" ] if not empty? t-digit [ append tokens t-digit t-digit: copy "" ] ) skip ] ] return tokens ]
halt ;; to terminate script if DO'ne from webpage