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package org.ansj.recognition.arrimpl;

import java.util.ArrayList;
import java.util.List;

import org.ansj.domain.Nature;
import org.ansj.domain.NewWord;
import org.ansj.domain.PersonNatureAttr;
import org.ansj.domain.Term;
import org.ansj.domain.TermNatures;
import org.ansj.library.NgramLibrary;
import org.ansj.recognition.TermArrRecognition;
import org.ansj.util.TermUtil;
import org.ansj.util.TermUtil.InsertTermType;

/**
 * 人名识别工具类
 * 
 * @author ansj
 * 
 */
public class AsianPersonRecognition implements TermArrRecognition{
	private static final double[] FACTORY = { 0.16271366224044456, 0.8060521860870434, 0.031234151672511947 };
	private boolean skip = false;
	private Term[] terms;

	// 名称是否有歧异
	// public int B = -1;//0 姓氏
	// public int C = -1;//1 双名的首字
	// public int D = -1;//2 双名的末字
	// public int E = -1;//3 单名
	// public int N = -1; //4任意字
	// public int L = -1;//11 人名的下文
	// public int M = -1;//12 两个中国人名之间的成分
	// public int m = -1;//44 可拆分的姓名
	// double[] factory = {"BC", "BCD", "BCDE"}

	public void recognition(Term[] terms) {
		this.terms = terms;
		List termList = recogntion_();
		for (Term term2 : termList) {
			TermUtil.insertTerm(terms, term2, InsertTermType.SCORE_ADD_SORT);
		}
	}

	private List recogntion_() {
		Term term = null;
		Term tempTerm = null;
		List termList = new ArrayList();
		int beginFreq = 10;
		for (int i = 0; i < terms.length; i++) {
			term = terms[i];
			if (term == null || !term.termNatures().personAttr.flag) {
				continue;
			}
			term.score(0);
			term.selfScore(0);
			int freq = 0;
			for (int j = 2; j > -1; j--) {
				freq = term.termNatures().personAttr.getFreq(j, 0);
				if ((freq > 10) || (term.getName().length() == 2 && freq > 10)) {
					tempTerm = nameFind(i, beginFreq, j);
					if (tempTerm != null) {
						termList.add(tempTerm);
						// 如果是无争议性识别
						if (skip) {
							for (int j2 = i; j2 < tempTerm.toValue(); j2++) {
								if (terms[j2] != null) {
									terms[j2].score(0);
									terms[j2].selfScore(0);
								}
							}
							i = tempTerm.toValue() - 1;
							break;
						}
					}
				}
			}
			beginFreq = term.termNatures().personAttr.begin + 1;
		}
		return termList;
	}

	/**
	 * 人名识别
	 * 
	 * @param term
	 * @param offe
	 * @param freq
	 */

	private Term nameFind(int offe, int beginFreq, int size) {
		StringBuilder sb = new StringBuilder();
		int undefinite = 0;
		skip = false;
		PersonNatureAttr pna = null;
		int index = 0;
		int freq = 0;
		double allFreq = 0;
		Term term = null;
		int i = offe;
		for (; i < terms.length; i++) {
			// 走到结尾处识别出来一个名字.
			if (terms[i] == null) {
				continue;
			}
			term = terms[i];
			pna = term.termNatures().personAttr;
			// 在这个长度的这个位置的词频,如果没有可能就干掉,跳出循环
			if ((freq = pna.getFreq(size, index)) == 0) {
				return null;
			}

			if (pna.allFreq > 0) {
				undefinite++;
			}
			sb.append(term.getName());
			allFreq += Math.log(term.termNatures().allFreq + 1);
			allFreq += -Math.log((freq));
			index++;

			if (index == size + 2) {
				break;
			}
		}

		double score = -Math.log(FACTORY[size]);
		score += allFreq;
		double endFreq = 0;
		// 开始寻找结尾词
		boolean flag = true;
		while (flag) {
			i++;
			if (i >= terms.length) {
				endFreq = 10;
				flag = false;
			} else if (terms[i] != null) {
				int twoWordFreq = NgramLibrary.getTwoWordFreq(term, terms[i]);
				if (twoWordFreq > 3) {
					return null;
				}
				endFreq = terms[i].termNatures().personAttr.end + 1;
				flag = false;
			}
		}

		score -= Math.log(endFreq);
		score -= Math.log(beginFreq);

		if (score > -3) {
			return null;
		}

		if (allFreq > 0 && undefinite > 0) {
			return null;
		}

		skip = undefinite == 0;
		term = new Term(sb.toString(), offe, TermNatures.NR);
		term.selfScore(score);

		return term;

	}

	public List getNewWords(Term[] terms) {
		this.terms = terms ;
		List all = new ArrayList();
		List termList = recogntion_();
		for (Term term2 : termList) {
			all.add(new NewWord(term2.getName(), Nature.NR));
		}
		return all;
	}

	public List getNewTerms() {
		return recogntion_();
	}

}