use of org.nlpcn.commons.lang.tire.domain.Forest in project ansj_seg by NLPchina.
the class AnsjAnalyzer method getTokenizer.
/**
* 获得一个tokenizer
*
* @param reader
* @param type
* @param filter
* @return
*/
public static Tokenizer getTokenizer(Reader reader, Map<String, String> args) {
if (LOG.isDebugEnabled()) {
LOG.debug("to create tokenizer " + args);
}
Analysis analysis = null;
String temp = null;
String type = args.get("type");
if (type == null) {
type = AnsjAnalyzer.TYPE.base_ansj.name();
}
switch(AnsjAnalyzer.TYPE.valueOf(type)) {
case base_ansj:
analysis = new BaseAnalysis();
break;
case index_ansj:
analysis = new IndexAnalysis();
break;
case dic_ansj:
analysis = new DicAnalysis();
break;
case query_ansj:
analysis = new ToAnalysis();
break;
case nlp_ansj:
analysis = new NlpAnalysis();
if (StringUtil.isNotBlank(temp = args.get(CrfLibrary.DEFAULT))) {
((NlpAnalysis) analysis).setCrfModel(CrfLibrary.get(temp));
}
break;
default:
analysis = new BaseAnalysis();
}
if (reader != null) {
analysis.resetContent(reader);
}
if (StringUtil.isNotBlank(temp = args.get(DicLibrary.DEFAULT))) {
//用户自定义词典
String[] split = temp.split(",");
Forest[] forests = new Forest[split.length];
for (int i = 0; i < forests.length; i++) {
if (StringUtil.isBlank(split[i])) {
continue;
}
forests[i] = DicLibrary.get(split[i]);
}
analysis.setForests(forests);
}
List<StopRecognition> filters = null;
if (StringUtil.isNotBlank(temp = args.get(StopLibrary.DEFAULT))) {
//用户自定义词典
String[] split = temp.split(",");
filters = new ArrayList<StopRecognition>();
for (String key : split) {
StopRecognition stop = StopLibrary.get(key.trim());
if (stop != null)
filters.add(stop);
}
}
List<SynonymsRecgnition> synonyms = null;
if (StringUtil.isNotBlank(temp = args.get(SynonymsLibrary.DEFAULT))) {
//同义词词典
String[] split = temp.split(",");
synonyms = new ArrayList<SynonymsRecgnition>();
for (String key : split) {
SmartForest<List<String>> sf = SynonymsLibrary.get(key.trim());
if (sf != null)
synonyms.add(new SynonymsRecgnition(sf));
}
}
if (StringUtil.isNotBlank(temp = args.get(AmbiguityLibrary.DEFAULT))) {
//歧义词典
analysis.setAmbiguityForest(AmbiguityLibrary.get(temp.trim()));
}
if (StringUtil.isNotBlank(temp = args.get("isNameRecognition"))) {
// 是否开启人名识别
analysis.setIsNameRecognition(Boolean.valueOf(temp));
}
if (StringUtil.isNotBlank(temp = args.get("isNumRecognition"))) {
// 是否开启数字识别
analysis.setIsNumRecognition(Boolean.valueOf(temp));
}
if (StringUtil.isNotBlank(temp = args.get("isQuantifierRecognition"))) {
//量词识别
analysis.setIsQuantifierRecognition(Boolean.valueOf(temp));
}
if (StringUtil.isNotBlank(temp = args.get("isRealName"))) {
//是否保留原字符
analysis.setIsRealName(Boolean.valueOf(temp));
}
return new AnsjTokenizer(analysis, filters, synonyms);
}
use of org.nlpcn.commons.lang.tire.domain.Forest in project ansj_seg by NLPchina.
the class AnsjAnalyzer method getTokenizer.
/**
* 获得一个tokenizer
*
* @param reader
* @param type
* @param filter
* @return
*/
public static Tokenizer getTokenizer(Reader reader, Map<String, String> args) {
if (LOG.isDebugEnabled()) {
LOG.debug("to create tokenizer " + args);
}
Analysis analysis = null;
String temp = null;
String type = args.get("type");
if (type == null) {
type = AnsjAnalyzer.TYPE.base_ansj.name();
}
switch(AnsjAnalyzer.TYPE.valueOf(type)) {
case base_ansj:
analysis = new BaseAnalysis();
break;
case index_ansj:
analysis = new IndexAnalysis();
break;
case dic_ansj:
analysis = new DicAnalysis();
break;
case query_ansj:
analysis = new ToAnalysis();
break;
case nlp_ansj:
analysis = new NlpAnalysis();
if (StringUtil.isNotBlank(temp = args.get(CrfLibrary.DEFAULT))) {
((NlpAnalysis) analysis).setCrfModel(CrfLibrary.get(temp));
}
break;
default:
analysis = new BaseAnalysis();
}
if (reader != null) {
analysis.resetContent(reader);
}
if (StringUtil.isNotBlank(temp = args.get(DicLibrary.DEFAULT))) {
//用户自定义词典
String[] split = temp.split(",");
Forest[] forests = new Forest[split.length];
for (int i = 0; i < forests.length; i++) {
if (StringUtil.isBlank(split[i])) {
continue;
}
forests[i] = DicLibrary.get(split[i]);
}
analysis.setForests(forests);
}
List<StopRecognition> filters = null;
if (StringUtil.isNotBlank(temp = args.get(StopLibrary.DEFAULT))) {
//用户自定义词典
String[] split = temp.split(",");
filters = new ArrayList<StopRecognition>();
for (String key : split) {
StopRecognition stop = StopLibrary.get(key.trim());
if (stop != null)
filters.add(stop);
}
}
List<SynonymsRecgnition> synonyms = null;
if (StringUtil.isNotBlank(temp = args.get(SynonymsLibrary.DEFAULT))) {
//同义词词典
String[] split = temp.split(",");
synonyms = new ArrayList<SynonymsRecgnition>();
for (String key : split) {
SmartForest<List<String>> sf = SynonymsLibrary.get(key.trim());
if (sf != null)
synonyms.add(new SynonymsRecgnition(sf));
}
}
if (StringUtil.isNotBlank(temp = args.get(AmbiguityLibrary.DEFAULT))) {
//歧义词典
analysis.setAmbiguityForest(AmbiguityLibrary.get(temp.trim()));
}
if (StringUtil.isNotBlank(temp = args.get("isNameRecognition"))) {
// 是否开启人名识别
analysis.setIsNameRecognition(Boolean.valueOf(temp));
}
if (StringUtil.isNotBlank(temp = args.get("isNumRecognition"))) {
// 是否开启数字识别
analysis.setIsNumRecognition(Boolean.valueOf(temp));
}
if (StringUtil.isNotBlank(temp = args.get("isQuantifierRecognition"))) {
//量词识别
analysis.setIsQuantifierRecognition(Boolean.valueOf(temp));
}
if (StringUtil.isNotBlank(temp = args.get("isRealName"))) {
//是否保留原字符
analysis.setIsRealName(Boolean.valueOf(temp));
}
return new AnsjTokenizer(analysis, filters, synonyms);
}
use of org.nlpcn.commons.lang.tire.domain.Forest in project ansj_seg by NLPchina.
the class AmbiguityLibrary method insert.
/**
* 插入到树种
*
* @param key
* @param value
*/
public static void insert(String key, Value value) {
Forest forest = get(key);
Library.insertWord(forest, value);
}
use of org.nlpcn.commons.lang.tire.domain.Forest in project ansj_seg by NLPchina.
the class AmbiguityLibrary method insert.
/**
* 插入到树中呀
*
* @param key
* @param split
* @return
*/
public static void insert(String key, String... split) {
Forest forest = get(key);
StringBuilder sb = new StringBuilder();
if (split.length % 2 != 0) {
LOG.error("init ambiguity error in line :" + Arrays.toString(split) + " format err !");
return;
}
for (int i = 0; i < split.length; i += 2) {
sb.append(split[i]);
}
forest.addBranch(sb.toString(), split);
}
use of org.nlpcn.commons.lang.tire.domain.Forest in project ansj_seg by NLPchina.
the class AmbiguityLibrary method get.
/**
* 根据key获取
*
*/
public static Forest get(String key) {
KV<String, Forest> kv = AMBIGUITY.get(key);
if (kv == null) {
if (MyStaticValue.ENV.containsKey(key)) {
putIfAbsent(key, MyStaticValue.ENV.get(key));
return get(key);
}
LOG.warn("crf " + key + " not found in config ");
return null;
}
Forest sw = (Forest) kv.getV();
if (sw == null) {
try {
sw = init(key, kv);
} catch (Exception e) {
}
}
return sw;
}
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