Transcription
Introduction to IBM SPSS Modeler Text Analytics (v15)Varighet: 2 DaysKurskode: 0A104GBeskrivelse:Introduction to IBM SPSS Modeler Text Analytics is a two-day instructor led classroom course that teaches you how to analyze text data usingIBM SPSS Modeler Text Analytics. You will see the complete set of steps involved in working with text data, from reading the text data tocreating the final categories for additional analysis. After the final model has been created, there is an example of how to apply the model toperform Churn analysis. Topics include how to automatically and manually create and modify categories, how to edit synonym, type, andexclude dictionaries, and how to perform Text Link Analysis and Cluster Analysis with text data. Also included are examples of how to createresource templates and Text Analysis packages to share work with other projects and other users.Målgruppe:This course is for: anyone who needs to analyze text data for the purpose of creating predictive models or reports based in part on text datausers of IBM SPSS Modeler Text AnalyticsAgenda:Please refer to course overview for description information.Forkunnskaper:You should have completed:Introduction to "IBM SPSS Modeler and Data Mining" course orhave experience with IBM SPSS ModelerYou should have:General computer literacyPractical experience with coding text data is not a prerequisite butwould be wledge.no22 95 66 00
Innhold:Introduction to Text MininglineDescribe text mining and its relationship todata miningLinguistic ResourceslineDescribe the resource templatelineExplain CRISP-DM methodology as itapplies to text miningDescribe the steps in a text mining projectComplete a typical text mining modelingsessionView text from documents within ModelerRead text from Web FeedsDescribe the process of text extractionDescribe categorization of terms andconceptsDescribe Templates and LibrariesDescribe Text Analysis PackagesCompare models based on using differentResource TemplatesScore model dataAnalyze model resultsReview extracted conceptsReview extracted typesUpdate the modeling nodeReview librariesReview DictionariesManage librariesDevelop editing strategyAdd Type definitionsAdd Synonym definitionsAdd Exclusion definitionsText re-extraction to review modificationsAdd fuzzy grouping exceptionsReview Text Link RulesUse visualization paneUse Text Link Analysis nodeCreate categories from a patternUse visualization paneCreate categories from a clusterDescribe linguistic based categorizationDescribe frequency based categorizationDescribe results of different categorizationmethodsCreate categories automaticallyCreate categories manuallyUse conditional rules to create categoriesAssess category overlapExtend categoriesImport coding framesSave resource templatesDescribe local and public librariesPublishing librariesShare librariesShare templatesCreate Text Analysis PackagesBackup resourcesDevelop a model with quantitative andqualitative dataScore new datalineExplain CRISP-DM methodology as itapplies to text miningDescribe the steps in a text miningprojectComplete a typical text mining modelingsessionView text from documents within ModelerRead text from Web FeedsDescribe the process of text extractionDescribe categorization of terms andconceptsDescribe Templates and LibrariesDescribe Text Analysis PackagesCompare models based on usingdifferent Resource TemplatesScore model dataAnalyze model resultsReview extracted conceptsReview extracted typesUpdate the modeling nodeReview librariesReview DictionariesManage librariesDevelop editing strategyAdd Type definitionsAdd Synonym definitionsAdd Exclusion definitionsText re-extraction to review modificationsAdd fuzzy grouping exceptionsReview Text Link RulesUse visualization paneUse Text Link Analysis nodeCreate categories from a patternUse visualization paneCreate categories from a clusterDescribe linguistic based categorizationDescribe frequency based categorizationDescribe results of differentcategorization methodsCreate categories automaticallyCreate categories manuallyUse conditional rules to create categoriesAssess category overlapExtend categoriesImport coding framesSave resource templatesDescribe local and public librariesPublishing librariesShare librariesShare templatesCreate Text Analysis PackagesBackup resourcesDevelop a model with quantitative andqualitative dataScore new n CRISP-DM methodology as itapplies to text miningDescribe the steps in a text mining projectComplete a typical text mining modelingsessionView text from documents within ModelerRead text from Web FeedsDescribe the process of text extractionDescribe categorization of terms andconceptsDescribe Templates and LibrariesDescribe Text Analysis PackagesCompare models based on using differentResource TemplatesScore model dataAnalyze model resultsReview extracted conceptsReview extracted typesUpdate the modeling nodeReview librariesReview DictionariesManage librariesDevelop editing strategyAdd Type definitionsAdd Synonym definitionsAdd Exclusion definitionsText re-extraction to review modificationsAdd fuzzy grouping exceptionsReview Text Link RulesUse visualization paneUse Text Link Analysis nodeCreate categories from a patternUse visualization paneCreate categories from a clusterDescribe linguistic based categorizationDescribe frequency based categorizationDescribe results of different categorizationmethodsCreate categories automaticallyCreate categories manuallyUse conditional rules to create categoriesAssess category overlapExtend categoriesImport coding framesSave resource templatesDescribe local and public librariesPublishing librariesShare librariesShare templatesCreate Text Analysis PackagesBackup resourcesDevelop a model with quantitative andqualitative dataScore new datalineExplain CRISP-DM methodology as itapplies to text miningDescribe the steps in a text mining projectComplete a typical text mining modelingsessioninfo@globalknowledge.no22 95 66 00
Explain CRISP-DM methodology as itapplies to text miningDescribe the steps in a text mining projectComplete a typical text mining modelingsessionView text from documents within ModelerRead text from Web FeedsDescribe the process of text extractionDescribe categorization of terms andconceptsDescribe Templates and LibrariesDescribe Text Analysis PackagesCompare models based on using differentResource TemplatesScore model dataAnalyze model resultsReview extracted conceptsReview extracted typesUpdate the modeling nodeReview librariesReview DictionariesManage librariesDevelop editing strategyAdd Type definitionsAdd Synonym definitionsAdd Exclusion definitionsText re-extraction to review modificationsAdd fuzzy grouping exceptionsReview Text Link RulesUse visualization paneUse Text Link Analysis nodeCreate categories from a patternUse visualization paneCreate categories from a clusterDescribe linguistic based categorizationDescribe frequency based categorizationDescribe results of different categorizationmethodsCreate categories automaticallyCreate categories manuallyUse conditional rules to create categoriesAssess category overlapExtend categoriesImport coding framesSave resource templatesDescribe local and public librariesPublishing librariesShare librariesShare templatesCreate Text Analysis PackagesBackup resourcesDevelop a model with quantitative andqualitative dataScore new dataA Text Mining ExamplelineExplain the text mining nodes available inModelerlineExplain CRISP-DM methodology as itapplies to text miningDescribe the steps in a text mining projectComplete a typical text mining modeling0A104GExplain CRISP-DM methodology as itapplies to text miningDescribe the steps in a text miningprojectComplete a typical text mining modelingsessionView text from documents within ModelerRead text from Web FeedsDescribe the process of text extractionDescribe categorization of terms andconceptsDescribe Templates and LibrariesDescribe Text Analysis PackagesCompare models based on usingdifferent Resource TemplatesScore model dataAnalyze model resultsReview extracted conceptsReview extracted typesUpdate the modeling nodeReview librariesReview DictionariesManage librariesDevelop editing strategyAdd Type definitionsAdd Synonym definitionsAdd Exclusion definitionsText re-extraction to review modificationsAdd fuzzy grouping exceptionsReview Text Link RulesUse visualization paneUse Text Link Analysis nodeCreate categories from a patternUse visualization paneCreate categories from a clusterDescribe linguistic based categorizationDescribe frequency based categorizationDescribe results of differentcategorization methodsCreate categories automaticallyCreate categories manuallyUse conditional rules to create categoriesAssess category overlapExtend categoriesImport coding framesSave resource templatesDescribe local and public librariesPublishing librariesShare librariesShare templatesCreate Text Analysis PackagesBackup resourcesDevelop a model with quantitative andqualitative dataScore new datalineExplain CRISP-DM methodology as itapplies to text miningDescribe the steps in a text miningprojectComplete a typical text mining modelingsessionView text from documents within ModelerRead text from Web Feedswww.globalknowledge.noView text from documents within ModelerRead text from Web FeedsDescribe the process of text extractionDescribe categorization of terms andconceptsDescribe Templates and LibrariesDescribe Text Analysis PackagesCompare models based on using differentResource TemplatesScore model dataAnalyze model resultsReview extracted conceptsReview extracted typesUpdate the modeling nodeReview librariesReview DictionariesManage librariesDevelop editing strategyAdd Type definitionsAdd Synonym definitionsAdd Exclusion definitionsText re-extraction to review modificationsAdd fuzzy grouping exceptionsReview Text Link RulesUse visualization paneUse Text Link Analysis nodeCreate categories from a patternUse visualization paneCreate categories from a clusterDescribe linguistic based categorizationDescribe frequency based categorizationDescribe results of different categorizationmethodsCreate categories automaticallyCreate categories manuallyUse conditional rules to create categoriesAssess category overlapExtend categoriesImport coding framesSave resource templatesDescribe local and public librariesPublishing librariesShare librariesShare templatesCreate Text Analysis PackagesBackup resourcesDevelop a model with quantitative andqualitative dataScore new datalineExplain CRISP-DM methodology as itapplies to text miningDescribe the steps in a text mining projectComplete a typical text mining modelingsessionView text from documents within ModelerRead text from Web FeedsDescribe the process of text extractionDescribe categorization of terms andconceptsDescribe Templates and LibrariesDescribe Text Analysis PackagesCompare models based on using differentResource Templatesinfo@globalknowledge.no22 95 66 00
sessionView text from documents within ModelerRead text from Web FeedsDescribe the process of text extractionDescribe categorization of terms andconceptsDescribe Templates and LibrariesDescribe Text Analysis PackagesCompare models based on using differentResource TemplatesScore model dataAnalyze model resultsReview extracted conceptsReview extracted typesUpdate the modeling nodeReview librariesReview DictionariesManage librariesDevelop editing strategyAdd Type definitionsAdd Synonym definitionsAdd Exclusion definitionsText re-extraction to review modificationsAdd fuzzy grouping exceptionsReview Text Link RulesUse visualization paneUse Text Link Analysis nodeCreate categories from a patternUse visualization paneCreate categories from a clusterDescribe linguistic based categorizationDescribe frequency based categorizationDescribe results of different categorizationmethodsCreate categories automaticallyCreate categories manuallyUse conditional rules to create categoriesAssess category overlapExtend categoriesImport coding framesSave resource templatesDescribe local and public librariesPublishing librariesShare librariesShare templatesCreate Text Analysis PackagesBackup resourcesDevelop a model with quantitative andqualitative dataScore new dataReading Text DatalineRead text from documentslineExplain CRISP-DM methodology as itapplies to text miningDescribe the steps in a text mining projectComplete a typical text mining modelingsessionView text from documents within ModelerRead text from Web FeedsDescribe the process of text extractionDescribe categorization of terms and0A104GDescribe the process of text extractionDescribe categorization of terms andconceptsDescribe Templates and LibrariesDescribe Text Analysis PackagesCompare models based on usingdifferent Resource TemplatesScore model dataAnalyze model resultsReview extracted conceptsReview extracted typesUpdate the modeling nodeReview librariesReview DictionariesManage librariesDevelop editing strategyAdd Type definitionsAdd Synonym definitionsAdd Exclusion definitionsText re-extraction to review modificationsAdd fuzzy grouping exceptionsReview Text Link RulesUse visualization paneUse Text Link Analysis nodeCreate categories from a patternUse visualization paneCreate categories from a clusterDescribe linguistic based categorizationDescribe frequency based categorizationDescribe results of differentcategorization methodsCreate categories automaticallyCreate categories manuallyUse conditional rules to create categoriesAssess category overlapExtend categoriesImport coding framesSave resource templatesDescribe local and public librariesPublishing librariesShare librariesShare templatesCreate Text Analysis PackagesBackup resourcesDevelop a model with quantitative andqualitative dataScore new dataEditing DictionarieslineLinguistic Editing PreparationlineExplain CRISP-DM methodology as itapplies to text miningDescribe the steps in a text miningprojectComplete a typical text mining modelingsessionView text from documents within ModelerRead text from Web FeedsDescribe the process of text extractionDescribe categorization of terms andconceptsDescribe Templates and Librarieswww.globalknowledge.noScore model dataAnalyze model resultsReview extracted conceptsReview extracted typesUpdate the modeling nodeReview librariesReview DictionariesManage librariesDevelop editing strategyAdd Type definitionsAdd Synonym definitionsAdd Exclusion definitionsText re-extraction to review modificationsAdd fuzzy grouping exceptionsReview Text Link RulesUse visualization paneUse Text Link Analysis nodeCreate categories from a patternUse visualization paneCreate categories from a clusterDescribe linguistic based categorizationDescribe frequency based categorizationDescribe results of different categorizationmethodsCreate categories automaticallyCreate categories manuallyUse conditional rules to create categoriesAssess category overlapExtend categoriesImport coding framesSave resource templatesDescribe local and public librariesPublishing librariesShare librariesShare templatesCreate Text Analysis PackagesBackup resourcesDevelop a model with quantitative andqualitative dataScore new dataCreating CategorieslineDevelop categorization strategylineExplain CRISP-DM methodology as itapplies to text miningDescribe the steps in a text mining projectComplete a typical text mining modelingsessionView text from documents within ModelerRead text from Web FeedsDescribe the process of text extractionDescribe categorization of terms andconceptsDescribe Templates and LibrariesDescribe Text Analysis PackagesCompare models based on using differentResource TemplatesScore model dataAnalyze model resultsReview extracted conceptsReview extracted typesUpdate the modeling nodeinfo@globalknowledge.no22 95 66 00
conceptsDescribe Templates and LibrariesDescribe Text Analysis PackagesCompare models based on using differentResource TemplatesScore model dataAnalyze model resultsReview extracted conceptsReview extracted typesUpdate the modeling nodeReview librariesReview DictionariesManage librariesDevelop editing strategyAdd Type definitionsAdd Synonym definitionsAdd Exclusion definitionsText re-extraction to review modificationsAdd fuzzy grouping exceptionsReview Text Link RulesUse visualization paneUse Text Link Analysis nodeCreate categories from a patternUse visualization paneCreate categories from a clusterDescribe linguistic based categorizationDescribe frequency based categorizationDescribe results of different categorizationmethodsCreate categories automaticallyCreate categories manuallyUse conditional rules to create categoriesAssess category overlapExtend categoriesImport coding framesSave resource templatesDescribe local and public librariesPublishing librariesShare librariesShare templatesCreate Text Analysis PackagesBackup resourcesDevelop a model with quantitative andqualitative dataScore new datalineExplain CRISP-DM methodology as itapplies to text miningDescribe the steps in a text mining projectComplete a typical text mining modelingsessionView text from documents within ModelerRead text from Web FeedsDescribe the process of text extractionDescribe categorization of terms andconceptsDescribe Templates and LibrariesDescribe Text Analysis PackagesCompare models based on using differentResource TemplatesScore model dataAnalyze model resultsReview extracted conceptsReview extracted types0A104GDescribe Text Analysis PackagesCompare models based on usingdifferent Resource TemplatesScore model dataAnalyze model resultsReview extracted conceptsReview extracted typesUpdate the modeling nodeReview librariesReview DictionariesManage librariesDevelop editing strategyAdd Type definitionsAdd Synonym definitionsAdd Exclusion definitionsText re-extraction to review modificationsAdd fuzzy grouping exceptionsReview Text Link RulesUse visualization paneUse Text Link Analysis nodeCreate categories from a patternUse visualization paneCreate categories from a clusterDescribe linguistic based categorizationDescribe frequency based categorizationDescribe results of differentcategorization methodsCreate categories automaticallyCreate categories manuallyUse conditional rules to create categoriesAssess category overlapExtend categoriesImport coding framesSave resource templatesDescribe local and public librariesPublishing librariesShare librariesShare templatesCreate Text Analysis PackagesBackup resourcesDevelop a model with quantitative andqualitative dataScore new datalineExplain CRISP-DM methodology as itapplies to text miningDescribe the steps in a text miningprojectComplete a typical text mining modelingsessionView text from documents within ModelerRead text from Web FeedsDescribe the process of text extractionDescribe categorization of terms andconceptsDescribe Templates and LibrariesDescribe Text Analysis PackagesCompare models based on usingdifferent Resource TemplatesScore model dataAnalyze model resultsReview extracted conceptsReview extracted typesUpdate the modeling nodewww.globalknowledge.noReview librariesReview DictionariesManage librariesDevelop editing strategyAdd Type definitionsAdd Synonym definitionsAdd Exclusion definitionsText re-extraction to review modificationsAdd fuzzy grouping exceptionsReview Text Link RulesUse visualization paneUse Text Link Analysis nodeCreate categories from a patternUse visualization paneCreate categories from a clusterDescribe linguistic based categorizationDescribe frequency based categorizationDescribe results of different categorizationmethodsCreate categories automaticallyCreate categories manuallyUse conditional rules to create categoriesAssess category overlapExtend categoriesImport coding framesSave resource templatesDescribe local and public librariesPublishing librariesShare librariesShare templatesCreate Text Analysis PackagesBackup resourcesDevelop a model with quantitative andqualitative dataScore new datalineExplain CRISP-DM methodology as itapplies to text miningDescr
IBM SPSS Modeler Text Analytics. You will see the complete set of steps involved in working with text data, from reading the text data to creating the final categories for additional analysis. After the final model has been
