RMMSeg comes with a script rmmseg. To get the basic usage, just execute it with -h option:

rmmseg -h

It reads from STDIN and print result to STDOUT. Here is a real example:

$ echo "我们都喜欢用 Ruby" | rmmseg
我们 都 喜欢 用 Ruby

RMMSeg include an analyzer for Ferret. It is simply ready to use. Just require it and pass it to Ferret. Here’s a complete example:

#!/usr/bin/env ruby
require 'rubygems'
require 'rmmseg'
require 'rmmseg/ferret'

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

$index = Ferret::Index::Index.new(:analyzer => analyzer)

$index << {
:title => "分词",
:content => "中文分词比较困难，不像英文那样，直接在空格和标点符号的地方断开就可以了。"
}
$index << {
:title => "RMMSeg",
:content => "RMMSeg 我近日做的一个 Ruby 中文分词实现，下一步是和 Ferret 进行集成。"
}
$index << {
:title => "Ruby 1.9",
:content => "Ruby 1.9.0 已经发布了，1.9 的一个重大改进就是对 Unicode 的支持。"
}
$index << {
:title => "Ferret",
:content => <<END
Ferret is a high-performance, full-featured text search engine library
written for Ruby. It is inspired by Apache Lucene Java project. With
the introduction of Ferret, Ruby users now have one of the fastest and
most flexible search libraries available. And it is surprisingly easy
to use.
END
}

def highlight_search(key)
$index.search_each(%Q!content:"#{key}"!) do |id, score|
puts "*** Document \"#{$index[id][:title]}\" found with a score of #{score}"
puts "-"*40
highlights = $index.highlight("content:#{key}", id,
                              :field => :content,
                              :pre_tag => "\033[36m",
                              :post_tag => "\033[m")
puts "#{highlights}"
puts ""
end
end

ARGV.each { |key|
puts "\033[33mSearching for #{key}...\033[m"
puts ""
highlight_search(key)
}

# Local Variables:
# coding: utf-8
# End:

execute it on the following key words:

$ ruby ferret_example.rb Ruby 中文

will generate the following results:

Searching for Ruby...

*** Document "RMMSeg" found with a score of 0.21875
----------------------------------------
RMMSeg 我近日做的一个 Ruby 中文分词实现，下一步是和 Ferret 进行集成。

*** Document "Ruby 1.9" found with a score of 0.21875
----------------------------------------
Ruby 1.9.0 已经发布了，1.9 的一个重大改进就是对 Unicode 的支持。

*** Document "Ferret" found with a score of 0.176776692271233
----------------------------------------
Ferret is a high-performance, full-featured text search engine library
written for Ruby. It is inspired by Apache Lucene Java project. With
the introduction of Ferret, Ruby users now have one of the fastest and
most flexible search libraries available. And it's surprisingly easy
to use.

Searching for 中文...

*** Document "分词" found with a score of 0.281680464744568
----------------------------------------
中文分词比较困难，不像英文那样，直接在空格和标点符号的地方断开就可以了。

*** Document "RMMSeg" found with a score of 0.281680464744568
----------------------------------------
RMMSeg 我近日做的一个 Ruby 中文分词实现，下一步是和 Ferret 进行集成。

And if you run the example in terminal, you’ll see the result highlighted as in Figure 1: Ferret Example Screenshot.

Figure 1.  Ferret Example Screenshot

RMMSeg can be customized through RMMSeg::Config. For example, to use your own dictionaries, just set it before starting to do segmentation:

RMMSeg::Config.dictionaries = [["dict1.dic", true],  # with frequency info
                               ["dict2.dic", false], # without
                               ["dict3.dic", false]]
RMMSeg::Config.max_word_length = 6

Or to use the simple algorithm for more efficient (and less accurate) segmenting:

RMMSeg::Config.algorithm = :simple

For more information on customization, please refer to the RDoc of RMMSeg::Config.