我完成的C#关于在lucene下的中文切词

经过一天的研究,终于完成了在lucene.net下可以使用的中文切词方法。感到有些复杂,不过我还是拿下了。颇有点成就感的,发上来跟大家分享一下!
在实现了中文切词的基础方法上,我将其封装在继承lucene的Analyzer类下
chineseAnalzer的方法就不用多说了。
using  System;
using  System.Collections.Generic;
using  System.Text;

using  Lucene.Net.Analysis;
using  Lucene.Net.Analysis.Standard;

namespace  Lucene.Fanswo
{
    
/// <summary>
    
/// 
    
/// </summary>

    public class ChineseAnalyzer:Analyzer
    
{
        
//private System.Collections.Hashtable stopSet;
        public static readonly System.String[] CHINESE_ENGLISH_STOP_WORDS = new System.String[] "a""an""and""are""as""at""be""but""by""for""if""in""into""is""it""no""not""of""on""or""s""such""t""that""the""their""then""there""these""they""this""to""was""will""with""""我们" };

      
        
/// <summary>Constructs a {@link StandardTokenizer} filtered by a {@link
        
/// StandardFilter}, a {@link LowerCaseFilter} and a {@link StopFilter}. 
        
/// </summary>

        public override TokenStream TokenStream(System.String fieldName, System.IO.TextReader reader)
        
{
            TokenStream result 
= new ChineseTokenizer(reader);
            result 
= new StandardFilter(result);
            result 
= new LowerCaseFilter(result);
            result 
= new StopFilter(result, CHINESE_ENGLISH_STOP_WORDS);
            
return result;
        }


    }

}

ChineseTokenizer类的实现:
这里通过词典来正向匹配字符,返回lucene下定义的token流
using  System;
using  System.Collections.Generic;
using  System.Text;
using  Lucene.Net.Analysis;
using  System.Collections;
using  System.Text.RegularExpressions;
using  System.IO;

namespace  Lucene.Fanswo
{
    
class ChineseTokenizer : Tokenizer
    
{

        
private int offset = 0, bufferIndex = 0, dataLen = 0;//偏移量,当前字符的位置,字符长度

        
private int start;//开始位置
        /// <summary>
        
/// 存在字符内容
        
/// </summary>

        private string text;
       
        
/// <summary>
        
/// 切词所花费的时间
        
/// </summary>

        public double TextSeg_Span = 0;
   
          
/// <summary>Constructs a tokenizer for this Reader. </summary>
        public ChineseTokenizer(System.IO.TextReader reader)
        
{
            
this.input = reader;
            text 
= input.ReadToEnd();
            dataLen 
= text.Length;
        }


        
/// <summary>进行切词,返回数据流中下一个token或者数据流为空时返回null
        
/// </summary>
        
/// 

        public override Token Next()
        
{
            Token token 
= null;
            WordTree tree 
= new WordTree();
            
//读取词库
            tree.LoadDict();
            
//初始化词库,为树形
            Hashtable t_chartable = WordTree.chartable;
            
string ReWord = "";
            
string char_s;
            start 
= offset;
            bufferIndex 
= start;

            
while (true)
            
{
                
//开始位置超过字符长度退出循环
                if (start >= dataLen)
                
{
                    
break;
                }

                
//获取一个词
                char_s = text.Substring(start, 1);
                
if (string.IsNullOrEmpty(char_s.Trim()))
                
{
                    start
++;
                    
continue;
                }

                
//字符不在字典中
                if (!t_chartable.Contains(char_s))
                
{
                    
if (ReWord == "")
                    
{
                        
int j = start + 1;
                        
switch (tree.GetCharType(char_s))
                        
{
                            
case 0://中文单词
                                ReWord += char_s;
                                
break;
                            
case 1://英文单词
                                j = start + 1;
                                
while (j < dataLen)
                                
{
                                    
if (tree.GetCharType(text.Substring(j, 1)) != 1)
                                        
break;

                                    j
++;
                                }

                                ReWord 
+= text.Substring(start, j - offset);

                                
break;
                            
case 2://数字
                                j = start + 1;
                                
while (j < dataLen)
                                
{
                                    
if (tree.GetCharType(text.Substring(j, 1)) != 2)
                                        
break;

                                    j
++;
                                }

                                ReWord 
+= text.Substring(start, j - offset);

                                
break;

                            
default:
                                ReWord 
+= char_s;//其他字符单词
                                break;
                        }


                        offset 
= j;//设置取下一个词的开始位置
                    }

                    
else
                    
{
                        offset 
= start;//设置取下一个词的开始位置
                    }

                    
                    
//返回token对象
                    return new Token(ReWord, bufferIndex, bufferIndex + ReWord.Length - 1);
                }

                
//字符在字典中
                ReWord += char_s;
                
//取得属于当前字符的词典树
                t_chartable = (Hashtable)t_chartable[char_s];
                
//设置下一循环取下一个词的开始位置
                start++;
                
if (start == dataLen)
                
{
                    offset 
= dataLen;
                    
return new Token(ReWord, bufferIndex, bufferIndex + ReWord.Length - 1);
                }

            }

            
return token;
        }


    }

}

测试的代码:
using  System;
using  System.Collections.Generic;
using  System.Text;

using  Analyzer  =  Lucene.Net.Analysis.Analyzer;
using  SimpleAnalyzer  =  Lucene.Net.Analysis.SimpleAnalyzer;
using  StandardAnalyzer  =  Lucene.Net.Analysis.Standard.StandardAnalyzer;
using  Token  =  Lucene.Net.Analysis.Token;
using  TokenStream  =  Lucene.Net.Analysis.TokenStream;

namespace  MyLuceneTest
{
    
class Program
    
{
        [STAThread]
        
public static void Main(System.String[] args)
        
{
            
try
            
{
                Test(
"中华人民共和国在1949年建立,从此开始了新中国的伟大篇章。长春市长春节致词"true);
            }

            
catch (System.Exception e)
            
{
                System.Console.Out.WriteLine(
" caught a " + e.GetType() + "\n with message: " + e.Message + e.ToString());
            }

        }


        
internal static void Test(System.String text, bool verbose)
        
{
            System.Console.Out.WriteLine(
" Tokenizing string: " + text);
            Test(
new System.IO.StringReader(text), verbose, text.Length);
        }


        
internal static void Test(System.IO.TextReader reader, bool verbose, long bytes)
        
{
            
//Analyzer analyzer = new StandardAnalyzer();
            Analyzer analyzer = new Lucene.Fanswo.ChineseAnalyzer();
            TokenStream stream 
= analyzer.TokenStream(null, reader);
            
            System.DateTime start 
= System.DateTime.Now;

            
int count = 0;
            
for (Token t = stream.Next(); t != null; t = stream.Next())
            
{
                
if (verbose)
                
{
                    System.Console.Out.WriteLine(
"Token=" + t.ToString());
                }

                count
++;
            }


            System.DateTime end 
= System.DateTime.Now;

            
long time = end.Ticks - start.Ticks;
            System.Console.Out.WriteLine(time 
+ " milliseconds to extract " + count + " tokens");
            System.Console.Out.WriteLine((time 
* 1000.0/ count + " microseconds/token");
            System.Console.Out.WriteLine((bytes 
* 1000.0 * 60.0 * 60.0/ (time * 1000000.0+ " megabytes/hour");
        }

    }

}


测试结果:
我完成的C#关于在lucene下的中文切词

完毕!
分词的郊率上还有待在算法上提高。还有中文的标点符号没有处理,我将进一步完善。
本人文采不好,写不出很多文字,只有以代码代替一下我的言语。兄弟姐妹们给点意见哦。谢谢!
 
原码下载:http://files.cnblogs.com/harryguo/LucuneSearch.rar

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