ADDED ext/misc/editdist3.wiki Index: ext/misc/editdist3.wiki ================================================================== --- ext/misc/editdist3.wiki +++ ext/misc/editdist3.wiki @@ -0,0 +1,114 @@ +The editdist3 algorithm + +The editdist3 algorithm is a function that computes the minimum edit distance +(a.k.a. the Levenshtein distance) between two input strings. Features of +editdist3 include: + + * It works with unicode (UTF8) text. + + * A table of insertion, deletion, and substitution costs can be + provided by the application. + + * Multi-character insertsions, deletions, and substitutions can be + enumerated in the cost table. + +

The COST table

+ +To program the costs of editdist3, create a table such as the following: + +
+CREATE TABLE editcost(
+  iLang INT,   -- The language ID
+  cFrom TEXT,  -- Convert text from this
+  cTo   TEXT,  -- Convert text into this
+  iCost INT    -- The cost of doing the conversionnn
+);
+
+ +The cost table can be named anything you want - it does not have to be called +"editcost". And the table can contain additional columns. However, it the +table must contain the four columns show above, with exactly the names shown. + +The iLang column is a non-negative integer that identifies a set of costs +appropriate for a particular language. The editdist3 function will only use +a single iLang value for any given edit-distance computation. The default +value is 0. It is recommended that applications that only need to use a +single langauge always use iLang==0 for all entries. + +The iCost column is the numeric cost of transforming cFrom into cTo. This +value should be a non-negative integer, and should probably be less than 100. +The default single-character insertion and deletion costs are 100 and the +default single-character to single-character substitution cost is 150. A +cost of 10000 or more is considered "infinite" and causes the rule to be +ignored. + +The cFrom and cTo columns show edit transformation strings. Either or both +columns may contain more than one character. Or either column (but not both) +may hold an empty string. When cFrom is empty, that is the cost of inserting +cTo. When cTo is empty, that is the cost of deleting cFrom. + +In the spellfix1 algorithm, cFrom is the text as the user entered it and +cTo is the correctly spelled text as it exists in the database. The goal +of the editdist3 algorithm is to determine how close the user-entered text is +to the dictionary text. + +There are three special-case entries in the cost table: + + + + + + +
cFromcToMeaning
'''?'The default insertion cost
'?'''The default deletion cost
'?''?'The default substitution cost
+ +If any of the special-case entries shows above are omitted, then the +value of 100 is used for insertion and deletion and 150 is used for +substitution. To disable the default insertion, deletion, and/or substitution +set their respective cost to 10000 or more. + +Other entries in the cost table specific transforms for particular characters. +The cost of specific transforms should be less than the default costs, or else +the default costs will take precedence and the specific transforms will never +be used. + +Some example, cost table entries: + +
+INSERT INTO editcost(iLang, cFrom, cTo, iCost)
+VALUES(0, 'a', 'ä', 5);
+
+ +The rule above says that the letter "a" in user input can be matched against +the letter "ä" in the dictionary with a penalty of 5. + +
+INSERT INTO editcost(iLang, cFrom, cTo, iCost)
+VALUES(0, 'ss', 'ß', 8);
+
+ +The number of characters in cFrom and cTo do not need to be the same. The +rule above says that "ss" on user input will match "ß" with a penalty of 8. + +

Experimenting with the editcost3() function

+ +The [./spellfix1.wiki | spellfix1 virtual table] +uses editdist3 if the "edit_cost_table=TABLE" option +is specified as an argument when the spellfix1 virtual table is created. +But editdist3 can also be tested directly using the built-in "editdist3()" +SQL function. The editdist3() SQL function has 3 forms: + + 1. editdist3('TABLENAME'); + 2. editdist3('string1', 'string2'); + 3. editdist3('string1', 'string2', langid); + +The first form loads the edit distance coefficients from a table called +'TABLENAME'. Any prior coefficients are discarded. So when experimenting +with weights and the weight table changes, simply rerun the single-argument +form of editdist3() to reload revised coefficients. Note that the +edit distance +weights used by the editdist3() SQL function are independent from the +weights used by the spellfix1 virtual table. + +The second and third forms return the computed edit distance between strings +'string1' and "string2'. In the second form, an language id of 0 is used. +The language id is specified in the third form. ADDED ext/misc/spellfix1.wiki Index: ext/misc/spellfix1.wiki ================================================================== --- ext/misc/spellfix1.wiki +++ ext/misc/spellfix1.wiki @@ -0,0 +1,464 @@ +The Spellfix1 Virtual Table + +This spellfix1 virtual table is used to search +a large vocabulary for close matches. For example, spellfix1 +can be used to suggest corrections to misspelled words. Or, +it could be used with FTS4 to do full-text search using potentially +misspelled words. + +Create an instance of the spellfix1 virtual table like this: + +
+CREATE VIRTUAL TABLE demo USING spellfix1;
+
+ +The "spellfix1" term is the name of this module and must be entered as +shown. The "demo" term is the +name of the virtual table you will be creating and can be altered +to suit the needs of your application. The virtual table is initially +empty. In order for the virtual table to be useful, you will need to +populate it with your vocabulary. Suppose you +have a list of words in a table named "big_vocabulary". Then do this: + +
+INSERT INTO demo(word) SELECT word FROM big_vocabulary;
+
+ +If you intend to use this virtual table in cooperation with an FTS4 +table (for spelling correctly of search terms) then you might extract +the vocabulary using an fts3aux table: + +
+INSERT INTO demo(word) SELECT term FROM search_aux WHERE col='*';
+
+ +You can also provide the virtual table with a "rank" for each word. +The "rank" is an estimate of how common the word is. Larger numbers +mean the word is more common. If you omit the rank when populating +the table, then a rank of 1 is assumed. But if you have rank +information, you can supply it and the virtual table will show a +slight preference for selecting more commonly used terms. To +populate the rank from an fts4aux table "search_aux" do something +like this: + +
+INSERT INTO demo(word,rank)
+   SELECT term, documents FROM search_aux WHERE col='*';
+
+ +To query the virtual table, include a MATCH operator in the WHERE +clause. For example: + +
+SELECT word FROM demo WHERE word MATCH 'kennasaw';
+
+ +Using a dataset of American place names (derived from +[http://geonames.usgs.gov/domestic/download_data.htm]) the query above +returns 20 results beginning with: + +
+kennesaw
+kenosha
+kenesaw
+kenaga
+keanak
+
+ +If you append the character '*' to the end of the pattern, then +a prefix search is performed. For example: + +
+SELECT word FROM demo WHERE word MATCH 'kennes*';
+
+ +Yields 20 results beginning with: + +
+kennesaw
+kennestone
+kenneson
+kenneys
+keanes
+keenes
+
+ +

Search Refinements

+ +By default, the spellfix1 table returns no more than 20 results. +(It might return less than 20 if there were fewer good matches.) +You can change the upper bound on the number of returned rows by +adding a "top=N" term to the WHERE clause of your query, where N +is the new maximum. For example, to see the 5 best matches: + +
+SELECT word FROM demo WHERE word MATCH 'kennes*' AND top=5;
+
+ +Each entry in the spellfix1 virtual table is associated with a +a particular language, identified by the integer "langid" column. +The default langid is 0 and if no other actions are taken, the +entire vocabulary is a part of the 0 language. But if your application +needs to operate in multiple languages, then you can specify different +vocabulary items for each language by specifying the langid field +when populating the table. For example: + +
+INSERT INTO demo(word,langid) SELECT word, 0 FROM en_vocabulary;
+INSERT INTO demo(word,langid) SELECT word, 1 FROM de_vocabulary;
+INSERT INTO demo(word,langid) SELECT word, 2 FROM fr_vocabulary;
+INSERT INTO demo(word,langid) SELECT word, 3 FROM ru_vocabulary;
+INSERT INTO demo(word,langid) SELECT word, 4 FROM cn_vocabulary;
+
+ +After the virtual table has been populated with items from multiple +languages, specify the language of interest using a "langid=N" term +in the WHERE clause of the query: + +
+SELECT word FROM demo WHERE word MATCH 'hildes*' AND langid=1;
+
+ +Note that if you do not include the "langid=N" term in the WHERE clause, +the search will be against language 0 (English in the example above.) +All spellfix1 searches are against a single language id. There is no +way to search all languages at once. + + +

Virtual Table Details

+ +The virtual table actually has a unique rowid with seven columns plus five +extra hidden columns. The columns are as follows: + +
+
rowid
+A unique integer number associated with each +vocabulary item in the table. This can be used +as a foreign key on other tables in the database. + +
word
+The text of the word that matches the pattern. +Both word and pattern can contains unicode characters +and can be mixed case. + +
rank
+This is the rank of the word, as specified in the +original INSERT statement. + + +
distance
+This is an edit distance or Levensthein distance going +from the pattern to the word. + +
langid
+This is the language-id of the word. All queries are +against a single language-id, which defaults to 0. +For any given query this value is the same on all rows. + +
score
+The score is a combination of rank and distance. The +idea is that a lower score is better. The virtual table +attempts to find words with the lowest score and +by default (unless overridden by ORDER BY) returns +results in order of increasing score. + +
matchlen
+In a prefix search, the matchlen is the number of characters in +the string that match against the prefix. For a non-prefix search, +this is the same as length(word). + +
phonehash
+This column shows the phonetic hash prefix that was used to restrict +the search. For any given query, this column should be the same for +every row. This information is available for diagnostic purposes and +is not normally considered useful in real applications. + +
top
+(HIDDEN) For any query, this value is the same on all +rows. It is an integer which is the maximum number of +rows that will be output. The actually number of rows +output might be less than this number, but it will never +be greater. The default value for top is 20, but that +can be changed for each query by including a term of +the form "top=N" in the WHERE clause of the query. + +
scope
+(HIDDEN) For any query, this value is the same on all +rows. The scope is a measure of how widely the virtual +table looks for matching words. Smaller values of +scope cause a broader search. The scope is normally +choosen automatically and is capped at 4. Applications +can change the scope by including a term of the form +"scope=N" in the WHERE clause of the query. Increasing +the scope will make the query run faster, but will reduce +the possible corrections. + +
srchcnt
+(HIDDEN) For any query, this value is the same on all +rows. This value is an integer which is the number of +of words examined using the edit-distance algorithm to +find the top matches that are ultimately displayed. This +value is for diagnostic use only. + +
soundslike
+(HIDDEN) When inserting vocabulary entries, this field +can be set to an spelling that matches what the word +sounds like. See the DEALING WITH UNUSUAL AND DIFFICULT +SPELLINGS section below for details. + +
command
+(HIDDEN) The value of the "command" column is always NULL. However, +applications can insert special strings into the "command" column in order +to provoke certain behaviors in the spellfix1 virtual table. +For example, inserting the string 'reset' into the "command" column +will cause the virtual table will reread its edit distance weights +(if there are any). +
+ +

Algorithm

+ +The spellfix1 virtual table creates a single +shadow table named "%_vocab" (where the % is replaced by the name of +the virtual table; Ex: "demo_vocab" for the "demo" virtual table). +the shadow table contains the following columns: + +
+
id
+The unique id (INTEGER PRIMARY KEY) + +
rank
+The rank of word. + +
langid
+The language id for this entry. + +
word
+The original UTF8 text of the vocabulary word + +
k1
+The word transliterated into lower-case ASCII. +There is a standard table of mappings from non-ASCII +characters into ASCII. Examples: "æ" -> "ae", +"þ" -> "th", "ß" -> "ss", "á" -> "a", ... The +accessory function spellfix1_translit(X) will do +the non-ASCII to ASCII mapping. The built-in lower(X) +function will convert to lower-case. Thus: +k1 = lower(spellfix1_translit(word)). + +
k2
+This field holds a phonetic code derived from k1. Letters +that have similar sounds are mapped into the same symbol. +For example, all vowels and vowel clusters become the +single symbol "A". And the letters "p", "b", "f", and +"v" all become "B". All nasal sounds are represented +as "N". And so forth. The mapping is base on +ideas found in Soundex, Metaphone, and other +long-standing phonetic matching systems. This key can +be generated by the function spellfix1_phonehash(X). +Hence: k2 = spellfix1_phonehash(k1) +
+ +There is also a function for computing the Wagner edit distance or the +Levenshtein distance between a pattern and a word. This function +is exposed as spellfix1_editdist(X,Y). The edit distance function +returns the "cost" of converting X into Y. Some transformations +cost more than others. Changing one vowel into a different vowel, +for example is relatively cheap, as is doubling a constant, or +omitting the second character of a double-constant. Other transformations +or more expensive. The idea is that the edit distance function returns +a low cost of words that are similar and a higher cost for words +that are futher apart. In this implementation, the maximum cost +of any single-character edit (delete, insert, or substitute) is 100, +with lower costs for some edits (such as transforming vowels). + +The "score" for a comparison is the edit distance between the pattern +and the word, adjusted down by the base-2 logorithm of the word rank. +For example, a match with distance 100 but rank 1000 would have a +score of 122 (= 100 - log2(1000) + 32) where as a match with distance +100 with a rank of 1 would have a score of 131 (100 - log2(1) + 32). +(NB: The constant 32 is added to each score to keep it from going +negative in case the edit distance is zero.) In this way, frequently +used words get a slightly lower cost which tends to move them toward +the top of the list of alternative spellings. + +A straightforward implementation of a spelling corrector would be +to compare the search term against every word in the vocabulary +and select the 20 with the lowest scores. However, there will +typically be hundreds of thousands or millions of words in the +vocabulary, and so this approach is not fast enough. + +Suppose the term that is being spell-corrected is X. To limit +the search space, X is converted to a k2-like key using the +equivalent of: + +
+   key = spellfix1_phonehash(lower(spellfix1_translit(X)))
+
+ +This key is then limited to "scope" characters. The default scope +value is 4, but an alternative scope can be specified using the +"scope=N" term in the WHERE clause. After the key has been truncated, +the edit distance is run against every term in the vocabulary that +has a k2 value that begins with the abbreviated key. + +For example, suppose the input word is "Paskagula". The phonetic +key is "BACACALA" which is then truncated to 4 characters "BACA". +The edit distance is then run on the 4980 entries (out of +272,597 entries total) of the vocabulary whose k2 values begin with +BACA, yielding "Pascagoula" as the best match. + +Only terms of the vocabulary with a matching langid are searched. +Hence, the same table can contain entries from multiple languages +and only the requested language will be used. The default langid +is 0. + +

Configurable Edit Distance

+ +The built-in Wagner edit-distance function with fixed weights can be +replaced by the [./editdist3.wiki | editdist3()] edit-distance function +with application-defined weights and support for unicode, by specifying +the "edit_cost_table=TABLENAME" parameter to the spellfix1 module +when the virtual table is created. +For example: + +
+CREATE VIRTUAL TABLE demo2 USING spellfix1(edit_cost_table=APPCOST);
+
+ +In the example above, the APPCOST table would be interrogated to find +the edit distance coefficients. It is the presence of the "edit_cost_table=" +parameter to the spellfix1 module name that causes editdist3() to be used +in place of the built-in edit distance function. + +The edit distance coefficients are normally read from the APPCOST table +once and there after stored in memory. Hence, run-time changes to the +APPCOST table will not normally effect the edit distance results. +However, inserting the special string 'reset' into the "command" column of the +virtual table causes the edit distance coefficients to be reread the +APPCOST table. Hence, applications should run a SQL statement similar +to the following when changes to the APPCOST table occur: + +
+INSERT INTO demo2(command) VALUES('reset'); +
+ +The tables used for edit distance costs can be changed using a command +like the following: + +
+INSERT INTO demo2(command) VALUES('edit_cost_table=APPCOST2'); +
+ +In the example above, any prior edit distance costs would be discarded and +all future queries would use the costs found in the APPCOST2 table. If the +name of the table specified by the "edit_cost_table" command is "NULL", then +theh built-in Wagner edit-distance function will be used instead of the +editdist3() function in all future queries. + +

Dealing With Unusual And Difficult Spellings

+ +The algorithm above works quite well for most cases, but there are +exceptions. These exceptions can be dealt with by making additional +entries in the virtual table using the "soundslike" column. + +For example, many words of Greek origin begin with letters "ps" where +the "p" is silent. Ex: psalm, pseudonym, psoriasis, psyche. In +another example, many Scottish surnames can be spelled with an +initial "Mac" or "Mc". Thus, "MacKay" and "McKay" are both pronounced +the same. + +Accommodation can be made for words that are not spelled as they +sound by making additional entries into the virtual table for the +same word, but adding an alternative spelling in the "soundslike" +column. For example, the canonical entry for "psalm" would be this: + +
+  INSERT INTO demo(word) VALUES('psalm');
+
+ +To enhance the ability to correct the spelling of "salm" into +"psalm", make an addition entry like this: + +
+  INSERT INTO demo(word,soundslike) VALUES('psalm','salm');
+
+ +It is ok to make multiple entries for the same word as long as +each entry has a different soundslike value. Note that if no +soundslike value is specified, the soundslike defaults to the word +itself. + +Listed below are some cases where it might make sense to add additional +soundslike entries. The specific entries will depend on the application +and the target language. + + * Silent "p" in words beginning with "ps": psalm, psyche + + * Silent "p" in words beginning with "pn": pneumonia, pneumatic + + * Silent "p" in words beginning with "pt": pterodactyl, ptolemaic + + * Silent "d" in words beginning with "dj": djinn, Djikarta + + * Silent "k" in words beginning with "kn": knight, Knuthson + + * Silent "g" in words beginning with "gn": gnarly, gnome, gnat + + * "Mac" versus "Mc" beginning Scottish surnames + + * "Tch" sounds in Slavic words: Tchaikovsky vs. Chaykovsky + + * The letter "j" pronounced like "h" in Spanish: LaJolla + + * Words beginning with "wr" versus "r": write vs. rite + + * Miscellanous problem words such as "debt", "tsetse", + "Nguyen", "Van Nuyes". + +

Auxiliary Functions

+ +The source code module that implements the spellfix1 virtual table also +implements several SQL functions that might be useful to applications +that employ spellfix1 or for testing or diagnostic work while developing +applications that use spellfix1. The following auxiliary functions are +available: + +
+
editdist3(P,W)
editdist2(P,W,L)
editdist3(T)
+These routines provide direct access to the version of the Wagner +edit-distance function that allows for application-defined weights +on edit operations. The first two forms of this function compare +pattern P against word W and return the edit distance. In the first +function, the langid is assumed to be 0 and in the second, the +langid is given by the L parameter. The third form of this function +reloads edit distance coefficience from the table named by T. + +
spellfix1_editdist(P,W)
+This routine provides access to the built-in Wagner edit-distance +function that uses default, fixed costs. The value returned is +the edit distance needed to transform W into P. + +
spellfix1_phonehash(X)
+This routine constructs a phonetic hash of the pure ascii input word X +and returns that hash. This routine is used internally by spellfix1 in +order to transform the K1 column of the shadow table into the K2 +column. + +
spellfix1_scriptcode(X)
+Given an input string X, this routine attempts to determin the dominant +script of that input and returns the ISO-15924 numeric code for that +script. The current implementation understands the following scripts: +
    +
  • 215 - Latin +
  • 220 - Cyrillic +
  • 200 - Greek +
+Additional language codes might be added in future releases. + +
spellfix1_translit(X)
+This routine transliterates unicode text into pure ascii, returning +the pure ascii representation of the input text X. This is the function +that is used internally to transform vocabulary words into the K1 +column of the shadow table. + +