Introduction To Conditional Random Fields.ppt
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1、Introduction To Conditional Random Fields,Presentation by Yanbing Yu Oct.12, 2006,Outline,Why do we choose crf ?What is crf ?How to apply it ?,Application,HMM,joint probability,Disadvantages,Need to enumerate all possible observation sequencesNot practical to represent multiple interacting features
2、or long-range dependencies of the observationsVery strict independence assumptions on the observations,MEMM,Exponential modelGiven training set X with label sequence Y:Train a model that maximizes P(Y|X, )For a new data sequence x, the predicted label y maximizes P(y|x, )Notice the per-state normali
3、zation,MEMM,Disadvantages,per-state normalization,Global normalizationCRFs,Label bias problem,CRFs,Represent multiple interacting features or long-range dependencies of the observations,Solve the label bias problem,Comparison,HMM MEMM CRF,kuai ji shi,hui,会 计 师,Outline,Why do we choose crf ?What is c
4、rf ?How to apply it ?,Random Fields,Definition of CRFs,Conditional Distribution,If the graph G = (V, E) of Y is a tree, the conditional distribution over the label sequence Y = y, given X = x, by fundamental theorem of random fields is:,Z(x) is a normalization over the data sequence x,Outline,Why do
5、 we choose crf ?What is crf ?How to apply it ?,Experiment,Data sourceA CTP conversion on one years Peoples Daily of 1998 to prepare the corpus used in our experiments. SentencesThis experiment is based on 50,000 sentences with 746,761 couples of Chinese character and pinyin. 40000 of them are used t
6、o train and the left 10000 are used to test.,Format of Corpus,Traintou 投 biao 标 , ,shen 申 qing 请 。 。Testshi shi 十yi yi 亿, , ,OR ren ren 人min min 民。 。 。,How to train ?,Expectation: Correct tag sequence,Training Set xi, yi,Optimizing Goal,shi jie bei guan jun gui lai世 界 杯 冠 军 归 来,Example:x,y,Example,T
7、rain sentence:,shi jie bei guan jun gui lai世 界 杯 冠 军 归 来,x,y,Process:,Feature Extraction,LBFGS Optimization,Gradient Calculation,shi jie bei guan jun gui lai世 界 杯 冠 军 归 来,x,y,师 姐 悲 观 军 规 赖 使 节 被 官 军 贵 来 。,Template,U00:%x-2,0,U01:%x-1,0,U02:%x0,0,U03:%x1,0,U04:%x2,0,U05:%x-1,0/%x0,0,U06:%x0,0/%x1,0,U
8、00:shi:,U01:jie:,U02:bei:,U03:guan:,U04:jun:,U05:jie/bei:,U06:bei/guan:,Vertex Features,Weight,Sentence,Feature Extraction,shi jie bei guan jun gui lai世 界 杯 冠 军 归 来,x,y,Template,B00:%x-2,0,B01:%x-1,0,B02:%x0,0,B03:%x1,0,B04:%x2,0,B05:%x-1,0/%x0,0,B06:%x0,0/%x1,0,B00:shi:,B01:jie:,B02:bei guan:,B03:j
9、un:,B04:gui:,B05:jie/bei guan:,B06:bei guan/jun:,Edge Features,Weight,师 姐 悲 观 军 规 赖 使 节 被 官 军 贵 来 。,Sentence,Feature Extraction,B06:bei guan/jun:,Gradient Calculation,Lattice,shi jie bei guan jun gui lai,Gradient Calculation,Forward-Backward The goal is to get Z(x) and calculate the expectationViter
10、biGet the best optimizing path,Three parametresx Current weight vectorg Gradient (expectation)f Optimizing goal,LBFGS Optimization,Maximize,Some training weights,Org: 许多文艺理论家看到前人所建立的理论体系的不足, result: 许多文艺理论家看到前人所建立的理论体系的不足,(对:23,错:0)Org: 今天的会议向委员们印发了关于召开第六届全国人民代表大会第五次会议的决定草案, result: 今天的会议向委员们印发了关于召开
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