fundamentals of predictive text mining

fundamentals of predictive text mining

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时间:2018-02-10

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1、Contents1OverviewofTextMining.........................11.1What’sSpecialAboutTextMining?.................11.1.1StructuredorUnstructuredData?..............21.1.2IsTextDifferentfromNumbers?..............31.2WhatTypesofProblemsCanBeSolved?..............51.3DocumentClassific

2、ation.......................61.4InformationRetrieval........................61.5ClusteringandOrganizingDocuments...............71.6InformationExtraction........................81.7PredictionandEvaluation......................91.8TheNextChapters.........................

3、.101.9Summary...............................101.10HistoricalandBibliographicalRemarks...............111.11QuestionsandExercises.......................122FromTextualInformationtoNumericalVectors...........132.1CollectingDocuments........................132.2DocumentStan

4、dardization......................152.3Tokenization.............................162.4Lemmatization............................172.4.1InflectionalStemming....................192.4.2StemmingtoaRoot.....................192.5VectorGenerationforPrediction..................212

5、.5.1MultiwordFeatures.....................262.5.2LabelsfortheRightAnswers................282.5.3FeatureSelectionbyAttributeRanking...........292.6SentenceBoundaryDetermination.................292.7Part-of-SpeechTagging.......................312.8WordSenseDisambiguation

6、.....................322.9PhraseRecognition.........................322.10NamedEntityRecognition......................33ixxContents2.11Parsing................................332.12FeatureGeneration..........................352.13Summary...............................36

7、2.14HistoricalandBibliographicalRemarks...............362.15QuestionsandExercises.......................383UsingTextforPrediction.........................393.1RecognizingthatDocumentsFitaPattern..............413.2HowManyDocumentsAreEnough?................423.3DocumentC

8、lassification.......................433.4LearningtoPredictfromText....................443.4.1SimilarityandNearest-Neig

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