コード例 #1
0
ファイル: Vertex.java プロジェクト: ColinChenMaster/HanLP
 /**
  * 生成线程安全的终止节点
  *
  * @return
  */
 public static Vertex newE() {
   return new Vertex(
       Predefine.TAG_END,
       " ",
       new CoreDictionary.Attribute(Nature.end, Predefine.MAX_FREQUENCY / 10),
       CoreDictionary.getWordID(Predefine.TAG_END));
 }
コード例 #2
0
ファイル: Vertex.java プロジェクト: ColinChenMaster/HanLP
 /**
  * 生成线程安全的起始节点
  *
  * @return
  */
 public static Vertex newB() {
   return new Vertex(
       Predefine.TAG_BIGIN,
       " ",
       new CoreDictionary.Attribute(Nature.begin, Predefine.MAX_FREQUENCY / 10),
       CoreDictionary.getWordID(Predefine.TAG_BIGIN));
 }
コード例 #3
0
ファイル: Vertex.java プロジェクト: ColinChenMaster/HanLP
 /**
  * 自动构造一个合理的顶点
  *
  * @param realWord
  */
 public Vertex(String realWord) {
   this(null, realWord, CoreDictionary.get(realWord));
 }
コード例 #4
0
ファイル: Vertex.java プロジェクト: ColinChenMaster/HanLP
/**
 * 顶点
 *
 * @author hankcs
 */
public class Vertex {
  /** 节点对应的词或等效词(如未##数) */
  public String word;
  /** 节点对应的真实词,绝对不含## */
  public String realWord;
  /**
   * 词的属性,谨慎修改属性内部的数据,因为会影响到字典<br>
   * 如果要修改,应当new一个Attribute
   */
  public CoreDictionary.Attribute attribute;
  /** 等效词ID,也是Attribute的下标 */
  public int wordID;

  /** 在一维顶点数组中的下标,可以视作这个顶点的id */
  public int index;

  /** 始##始 */
  public static Vertex B =
      new Vertex(
          Predefine.TAG_BIGIN,
          " ",
          new CoreDictionary.Attribute(Nature.begin, Predefine.MAX_FREQUENCY / 10),
          CoreDictionary.getWordID(Predefine.TAG_BIGIN));
  /** 末##末 */
  public static Vertex E =
      new Vertex(
          Predefine.TAG_END,
          " ",
          new CoreDictionary.Attribute(Nature.begin, Predefine.MAX_FREQUENCY / 10),
          CoreDictionary.getWordID(Predefine.TAG_END));

  //////// 在最短路相关计算中用到的几个变量,之所以放在这里,是为了避免再去生成对象,浪费时间////////
  /** 到该节点的最短路径的前驱节点 */
  public Vertex from;
  /** 最短路径对应的权重 */
  public double weight;

  public void updateFrom(Vertex from) {
    double weight = from.weight + MathTools.calculateWeight(from, this);
    if (this.from == null || this.weight > weight) {
      this.from = from;
      this.weight = weight;
    }
  }

  /**
   * 最复杂的构造函数
   *
   * @param word 编译后的词
   * @param realWord 真实词
   * @param attribute 属性
   */
  public Vertex(String word, String realWord, CoreDictionary.Attribute attribute) {
    this(word, realWord, attribute, -1);
  }

  public Vertex(String word, String realWord, CoreDictionary.Attribute attribute, int wordID) {
    if (attribute == null) attribute = new CoreDictionary.Attribute(Nature.n, 1); // 安全起见
    this.wordID = wordID;
    this.attribute = attribute;
    if (word == null) word = compileRealWord(realWord, attribute);
    assert realWord.length() > 0 : "构造空白节点会导致死循环!";
    this.word = word;
    this.realWord = realWord;
  }

  /**
   * 将原词转为等效词串
   *
   * @param realWord 原来的词
   * @param attribute 等效词串
   * @return
   */
  private String compileRealWord(String realWord, CoreDictionary.Attribute attribute) {
    if (attribute.nature.length == 1) {
      switch (attribute.nature[0]) {
        case nr:
        case nr1:
        case nr2:
        case nrf:
        case nrj:
          {
            wordID = CoreDictionary.NR_WORD_ID;
            //                    this.attribute = CoreDictionary.get(CoreDictionary.NR_WORD_ID);
            return Predefine.TAG_PEOPLE;
          }
        case ns:
        case nsf:
          {
            wordID = CoreDictionary.NS_WORD_ID;
            // 在地名识别的时候,希望类似"河镇"的词语保持自己的词性,而不是未##地的词性
            //                    this.attribute = CoreDictionary.get(CoreDictionary.NS_WORD_ID);
            return Predefine.TAG_PLACE;
          }
          //                case nz:
        case nx:
          {
            wordID = CoreDictionary.NX_WORD_ID;
            this.attribute = CoreDictionary.get(CoreDictionary.NX_WORD_ID);
            return Predefine.TAG_PROPER;
          }
        case nt:
        case ntc:
        case ntcf:
        case ntcb:
        case ntch:
        case nto:
        case ntu:
        case nts:
        case nth:
        case nit:
          {
            wordID = CoreDictionary.NT_WORD_ID;
            this.attribute = CoreDictionary.get(CoreDictionary.NT_WORD_ID);
            return Predefine.TAG_GROUP;
          }
        case m:
        case mq:
          {
            wordID = CoreDictionary.M_WORD_ID;
            this.attribute = CoreDictionary.get(CoreDictionary.M_WORD_ID);
            return Predefine.TAG_NUMBER;
          }
        case x:
          {
            wordID = CoreDictionary.X_WORD_ID;
            this.attribute = CoreDictionary.get(CoreDictionary.X_WORD_ID);
            return Predefine.TAG_CLUSTER;
          }
          //                case xx:
          //                case w:
          //                {
          //                    word= Predefine.TAG_OTHER;
          //                }
          //                break;
        case t:
          {
            wordID = CoreDictionary.T_WORD_ID;
            this.attribute = CoreDictionary.get(CoreDictionary.T_WORD_ID);
            return Predefine.TAG_TIME;
          }
      }
    }

    return realWord;
  }

  /**
   * 真实词与编译词相同时候的构造函数
   *
   * @param realWord
   * @param attribute
   */
  public Vertex(String realWord, CoreDictionary.Attribute attribute) {
    this(null, realWord, attribute);
  }

  public Vertex(String realWord, CoreDictionary.Attribute attribute, int wordID) {
    this(null, realWord, attribute, wordID);
  }

  /**
   * 通过一个键值对方便地构造节点
   *
   * @param entry
   */
  public Vertex(Map.Entry<String, CoreDictionary.Attribute> entry) {
    this(entry.getKey(), entry.getValue());
  }

  /**
   * 自动构造一个合理的顶点
   *
   * @param realWord
   */
  public Vertex(String realWord) {
    this(null, realWord, CoreDictionary.get(realWord));
  }

  public Vertex(char realWord, CoreDictionary.Attribute attribute) {
    this(String.valueOf(realWord), attribute);
  }

  /**
   * 获取真实词
   *
   * @return
   */
  public String getRealWord() {
    return realWord;
  }

  /**
   * 获取词的属性
   *
   * @return
   */
  public CoreDictionary.Attribute getAttribute() {
    return attribute;
  }

  /**
   * 将属性的词性锁定为nature
   *
   * @param nature 词性
   * @return 如果锁定词性在词性列表中,返回真,否则返回假
   */
  public boolean confirmNature(Nature nature) {
    if (attribute.nature.length == 1 && attribute.nature[0] == nature) {
      return true;
    }
    boolean result = true;
    int frequency = attribute.getNatureFrequency(nature);
    if (frequency == 0) {
      frequency = 1000;
      result = false;
    }
    attribute = new CoreDictionary.Attribute(nature, frequency);
    return result;
  }

  /**
   * 将属性的词性锁定为nature,此重载会降低性能
   *
   * @param nature 词性
   * @param updateWord 是否更新预编译字串
   * @return 如果锁定词性在词性列表中,返回真,否则返回假
   */
  public boolean confirmNature(Nature nature, boolean updateWord) {
    switch (nature) {
      case m:
        word = Predefine.TAG_NUMBER;
        break;
      case t:
        word = Predefine.TAG_TIME;
        break;
      default:
        logger.warning("没有与" + nature + "对应的case");
        break;
    }

    return confirmNature(nature);
  }

  /**
   * 获取该节点的词性,如果词性还未确定,则返回null
   *
   * @return
   */
  public Nature getNature() {
    if (attribute.nature.length == 1) {
      return attribute.nature[0];
    }

    return null;
  }

  /**
   * 猜测最可能的词性,也就是这个节点的词性中出现频率最大的那一个词性
   *
   * @return
   */
  public Nature guessNature() {
    return attribute.nature[0];
  }

  public boolean hasNature(Nature nature) {
    return attribute.getNatureFrequency(nature) > 0;
  }

  /**
   * 复制自己
   *
   * @return 自己的备份
   */
  public Vertex copy() {
    return new Vertex(word, realWord, attribute);
  }

  public Vertex setWord(String word) {
    this.word = word;
    return this;
  }

  public Vertex setRealWord(String realWord) {
    this.realWord = realWord;
    return this;
  }

  /**
   * 创建一个数词实例
   *
   * @param realWord 数字对应的真实字串
   * @return 数词顶点
   */
  public static Vertex newNumberInstance(String realWord) {
    return new Vertex(Predefine.TAG_NUMBER, realWord, new CoreDictionary.Attribute(Nature.m, 1000));
  }

  /**
   * 创建一个地名实例
   *
   * @param realWord 数字对应的真实字串
   * @return 地名顶点
   */
  public static Vertex newAddressInstance(String realWord) {
    return new Vertex(Predefine.TAG_PLACE, realWord, new CoreDictionary.Attribute(Nature.ns, 1000));
  }

  /**
   * 创建一个标点符号实例
   *
   * @param realWord 标点符号对应的真实字串
   * @return 标点符号顶点
   */
  public static Vertex newPunctuationInstance(String realWord) {
    return new Vertex(realWord, new CoreDictionary.Attribute(Nature.w, 1000));
  }

  /**
   * 创建一个人名实例
   *
   * @param realWord
   * @return
   */
  public static Vertex newPersonInstance(String realWord) {
    return newPersonInstance(realWord, 1000);
  }

  /**
   * 创建一个音译人名实例
   *
   * @param realWord
   * @return
   */
  public static Vertex newTranslatedPersonInstance(String realWord, int frequency) {
    return new Vertex(
        Predefine.TAG_PEOPLE, realWord, new CoreDictionary.Attribute(Nature.nrf, frequency));
  }

  /**
   * 创建一个日本人名实例
   *
   * @param realWord
   * @return
   */
  public static Vertex newJapanesePersonInstance(String realWord, int frequency) {
    return new Vertex(
        Predefine.TAG_PEOPLE, realWord, new CoreDictionary.Attribute(Nature.nrj, frequency));
  }

  /**
   * 创建一个人名实例
   *
   * @param realWord
   * @param frequency
   * @return
   */
  public static Vertex newPersonInstance(String realWord, int frequency) {
    return new Vertex(
        Predefine.TAG_PEOPLE, realWord, new CoreDictionary.Attribute(Nature.nr, frequency));
  }

  /**
   * 创建一个地名实例
   *
   * @param realWord
   * @param frequency
   * @return
   */
  public static Vertex newPlaceInstance(String realWord, int frequency) {
    return new Vertex(
        Predefine.TAG_PLACE, realWord, new CoreDictionary.Attribute(Nature.ns, frequency));
  }

  /**
   * 创建一个机构名实例
   *
   * @param realWord
   * @param frequency
   * @return
   */
  public static Vertex newOrganizationInstance(String realWord, int frequency) {
    return new Vertex(
        Predefine.TAG_GROUP, realWord, new CoreDictionary.Attribute(Nature.nt, frequency));
  }

  /**
   * 创建一个时间实例
   *
   * @param realWord 时间对应的真实字串
   * @return 时间顶点
   */
  public static Vertex newTimeInstance(String realWord) {
    return new Vertex(Predefine.TAG_TIME, realWord, new CoreDictionary.Attribute(Nature.t, 1000));
  }

  /**
   * 生成线程安全的起始节点
   *
   * @return
   */
  public static Vertex newB() {
    return new Vertex(
        Predefine.TAG_BIGIN,
        " ",
        new CoreDictionary.Attribute(Nature.begin, Predefine.MAX_FREQUENCY / 10),
        CoreDictionary.getWordID(Predefine.TAG_BIGIN));
  }

  /**
   * 生成线程安全的终止节点
   *
   * @return
   */
  public static Vertex newE() {
    return new Vertex(
        Predefine.TAG_END,
        " ",
        new CoreDictionary.Attribute(Nature.end, Predefine.MAX_FREQUENCY / 10),
        CoreDictionary.getWordID(Predefine.TAG_END));
  }

  @Override
  public String toString() {
    return realWord;
    //        return "WordNode{" +
    //                "word='" + word + '\'' +
    //                (word.equals(realWord) ? "" : (", realWord='" + realWord + '\'')) +
    ////                ", attribute=" + attribute +
    //                '}';
  }
}
コード例 #5
0
ファイル: Vertex.java プロジェクト: ColinChenMaster/HanLP
  /**
   * 将原词转为等效词串
   *
   * @param realWord 原来的词
   * @param attribute 等效词串
   * @return
   */
  private String compileRealWord(String realWord, CoreDictionary.Attribute attribute) {
    if (attribute.nature.length == 1) {
      switch (attribute.nature[0]) {
        case nr:
        case nr1:
        case nr2:
        case nrf:
        case nrj:
          {
            wordID = CoreDictionary.NR_WORD_ID;
            //                    this.attribute = CoreDictionary.get(CoreDictionary.NR_WORD_ID);
            return Predefine.TAG_PEOPLE;
          }
        case ns:
        case nsf:
          {
            wordID = CoreDictionary.NS_WORD_ID;
            // 在地名识别的时候,希望类似"河镇"的词语保持自己的词性,而不是未##地的词性
            //                    this.attribute = CoreDictionary.get(CoreDictionary.NS_WORD_ID);
            return Predefine.TAG_PLACE;
          }
          //                case nz:
        case nx:
          {
            wordID = CoreDictionary.NX_WORD_ID;
            this.attribute = CoreDictionary.get(CoreDictionary.NX_WORD_ID);
            return Predefine.TAG_PROPER;
          }
        case nt:
        case ntc:
        case ntcf:
        case ntcb:
        case ntch:
        case nto:
        case ntu:
        case nts:
        case nth:
        case nit:
          {
            wordID = CoreDictionary.NT_WORD_ID;
            this.attribute = CoreDictionary.get(CoreDictionary.NT_WORD_ID);
            return Predefine.TAG_GROUP;
          }
        case m:
        case mq:
          {
            wordID = CoreDictionary.M_WORD_ID;
            this.attribute = CoreDictionary.get(CoreDictionary.M_WORD_ID);
            return Predefine.TAG_NUMBER;
          }
        case x:
          {
            wordID = CoreDictionary.X_WORD_ID;
            this.attribute = CoreDictionary.get(CoreDictionary.X_WORD_ID);
            return Predefine.TAG_CLUSTER;
          }
          //                case xx:
          //                case w:
          //                {
          //                    word= Predefine.TAG_OTHER;
          //                }
          //                break;
        case t:
          {
            wordID = CoreDictionary.T_WORD_ID;
            this.attribute = CoreDictionary.get(CoreDictionary.T_WORD_ID);
            return Predefine.TAG_TIME;
          }
      }
    }

    return realWord;
  }