To install the gem remotely from RubyForge:

sudo gem install rmmseg-cpp

Or you can download the gem file manually from
RubyForge and
install it locally:

sudo gem install —local rmmseg-cpp-x.y.z.gem

To build the gem manually from the latest source code. You’ll
need to have git and rake installed.

The source code of rmmseg-cpp is hosted at
GitHub. You can get the
source code by git clone:

git clone git://github.com/pluskid/rmmseg-cpp.git

then you can use Rake to build and install the gem:

cd rmmseg-cpp rake gem:install

To use rmmseg-cpp in Ruby program, you’ll first load it with RubyGems:

require 'rubygems'
require 'rmmseg'

Then you may customize the dictionaries used by rmmseg-cpp
(see the rdoc on
how to add your own dictionaries) and load all dictionaries:

RMMSeg::Dictionary.load_dictionaries

Now rmmseg-cpp will be ready to do segmenting.

To use rmmseg-cpp with Ferret, you’ll need to require the
Ferret support of rmmseg-cpp (Of course you’ll also have to
got Ferret installed. If you have problems running the belowing
example, please try to update to the latest version of both
Ferret and rmmseg-cpp first):

require 'rmmseg/ferret'

rmmseg-cpp comes with a ready to use Ferret analyzer:

analyzer = RMMSeg::Ferret::Analyzer.new { |tokenizer|
  Ferret::Analysis::LowerCaseFilter.new(tokenizer)
}
index = Ferret::Index::Index.new(:analyzer => analyzer)

A complete example can be found in misc/ferret_example.rb. The result
of running that example is shown in Figure 1. Ferret Example Screenshot.

rmmseg-cpp can also be used in normal Ruby programs. Just create
an Algorithm object and call next_token until a nil is returned:

algor = RMMSeg::Algorithm.new(text)
loop do
  tok = algor.next_token
  break if tok.nil?
  puts "#{tok.text} [#{tok.start}..#{tok.end}]"
end