NAME Text::Scan - Fast search for very large numbers of keys in a body of text. SYNOPSIS use Text::Scan; $dict = new Text::Scan; %terms = ( dog => 'canine', bear => 'ursine', pig => 'porcine' ); # load the dictionary with keys and values # (values can be any scalar, keys must be strings) while( ($key, $val) = each %terms ){ $dict->insert( $key, $val ); } # Scan a document for matches %found = $dict->scan( $document ); # Or, if you need to count number of occurrences of any given # key, use an array. This will give you a countable flat list # of key => value pairs. @found = $dict->scan( $document ); # Check for membership ($val is true) $val = $dict->has('pig'); # Retrieve all keys. This returns all inserted keys in ascending # char value, substrings first. @keys = $dict->keys(); # Retrieve all values (in same order as corresponding keys) # (new in v0.10) @vals = $dict->values(); # Like perl's index() but with multiple patterns (new in v0.07) # Scan for the starting positions of terms. @indices = $dict->mindex( $document ); # The hash version of mindex() records the position of the first # occurrences of each word %indices = $dict->mindex( $document ); # Turn on wildcard scanning. (New in v0.09) # This can be done anytime. Works for scan() and mindex() $dict->usewild(); DESCRIPTION This module provides facilities for fast searching on arbitrarily long texts with arbitrarily many search keys. The basic object behaves somewhat like a perl hash, except that you can retrieve based on a superstring of any keys stored. Simply scan a string as shown above and you will get back a perl hash (or list) of all keys found in the string (along with associated values (or positions if you use mindex() instead of scan())). Longest/first order is observed during matching (meaning, each subsequent match begins at the end of the last successful match, and matches are "greedy", as in perl regular expressions). IMPORTANT: As of this version, a single space is used as a delimiter for purposes of recognizing key boundaries. That's right, there is a bias in favor of processing natural language! In other words, if 'my dog' is a key and 'my dogs bite' is the text, 'my dog' will not be recognized. I plan to make this more configurable in the future, to have a different delimiter or none at all. For now, recognize that the key 'drunk' will not be found in the text 'gedrunk' or 'drunken' (or 'drunk.' for that matter). Properly tokenizing your corpus is essential. I know there is probably a better solution to the problem of substrings, and if anyone has suggestions, by all means contact me. To be honest, what I am leaning toward is simply having no implicit delimiter at all, and relying on the programmer to use a chosen delimiter when inserting keys, then tokenizing the target text properly so that the delimiter is present at boundaries as defined by your application. This would leave you free to have no delimiter if you really want "drunk" to match "gedrunk", "drunken", "drunk." etc. The chore of tokenizing the target would be mitigated by pattern matching capabilities (hmm..) NEW in v 0.09: Wildcards! A limited wildcard functionality is available. call usewild() to turn it on. Thereafter any asterisk (*) will be treated as "one or more non-space characters". Once this function is turned on, the scan will be approximately 50% slower than with literal strings. If you include '*' in any key without calling usewild(), the '*' will be treated literally. TO DO Some obvious things have not been implemented. Deletion of key/values, patterns as keys (kind of a big one), the abovementioned elimination of the default boundary marker ' ', possibility of calling scan() with a filehandle instead of a string scalar. CREDITS The basic framework for this code is borrowed from both Bentley & Sedgwick, and Leon Brocard's additions to it for "Tree::Ternary_XS". The differences are in the modified search algorithm to allow for scanning, the storage of keys/values, and an extra node-rotation for gradual self-adjusting optimization to the statistical characteristics of the target text. Many test scripts come directly from Rogaski's "Tree::Ternary" module. The C code interface was created using Ingerson's "Inline". SEE ALSO "Bentley & Sedgwick "Fast Algorithms for Sorting and Searching Strings", Proceedings ACM-SIAM (1997)" "Bentley & Sedgewick "Ternary Search Trees", Dr Dobbs Journal (1998)" "Sleator & Tarjan "Self-Adjusting Binary Search Trees", Journal of the ACM (1985)" "Tree::Ternary" "Tree::Ternary_XS" "Inline" COPYRIGHT Copyright 2001 Ira Woodhead, H5 Technologies. All rights reserved. This library is free software; you can redistribute it and/or modify it under the same terms as Perl itself AUTHOR Ira Woodhead, ira@h5technologies.com