README
1$Id: README,v 1.3 2004/11/29 22:30:16 jose Exp $
2
3-----[ libdistance
4
5The distance library is used to compare pieces of data for similarity.
6Specifically, it contains a number of methods to find the "edit distance"
7between inputs, or the number of differences between them. These differ-
8ences are calculated using various mechanisms. The inputs to these functions
9can be character strings or arbitrary data.
10
11Inputs are operated on pairwise as *s and *t and the edit distance value
12is returned.
13
14----[ references
15
16http://www.merriampark.com/ld.htm
17http://www.nist.gov/dads/HTML/editdistance.html
18http://www.nist.gov/dads/HTML/hammingdist.html
19http://www.nist.gov/dads/HTML/bloomfilt.html
20
21-----[ installation
22
23Build libdistance using BSD make, it's been tested on OpenBSD and OS X.
24Install as root for system wide installations. Note that you need to
25install both libdistance and distance.h in the appropriate locations.
26
27If you want to access libdistance from either Tcl or Python, you can
28use the bindings built in the "swig" subdirectory. If you don't have SWIG,
29you can edit the top level Makefile to remove the subdirectory "swig" from
30the SUBDIR variable.
31
32If you're building this on Win32 using MinGW, rename the directory
33sys-needed-for-windows/ to sys/ and run "make".
34
35-----[ authors
36
37Lorenzo Seidenari wrote the Levenshtein distance implementation.
38
39Jose Nazario <jose@monkey.org> wrote the implementation of the Hamming
40distance algorithm and the original modifications to the Levenshtein
41distance algorithm and ported the software to Win32 using MinGW.
42
43Evan Cooke adapted the adler32 routine from Jean-loup Gailly and Mark
44Adler used in the bloom_distance() function.
45
46See the manpage for the full list of author credits.
47