Using iKnow
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Contents

Preface : 
 
 
Chapter 1: 
 
  • 1.1 A Simple Use Case
  • 1.2 What is iKnow?
  • 1.2.1 What iKnow Isn’t
  • 1.3 Logical Text Units Identified by iKnow
  • 1.3.1 Sentences
  • 1.3.2 Entities
  • 1.3.3 CRCs and CCs
  • 1.3.4 Paths
  • 1.4 Smart Indexing
  • 1.5 Smart Matching
  • Chapter 2: 
     
  • 2.1 A Note on Program Examples
  • 2.2 A Note on %Persistent Object Methods
  • 2.3 A Note on %iKnow and %SYSTEM.iKnow
  • 2.4 Space Requirements and iKnow Globals
  • 2.4.1 Batch Load Space Allocation
  • 2.5 Input Data
  • 2.5.1 File Formats
  • 2.5.2 SQL Record Format
  • 2.5.3 Text Normalization
  • 2.5.4 User-defined Source Normalization
  • 2.6 Output Structures
  • 2.7 Constants
  • 2.8 Error Codes
  • Chapter 3: 
     
  • 3.1 Accessing iKnow Architect
  • 3.1.1 Enabling a Namespace
  • 3.2 Creating a Domain
  • 3.2.1 Opening a Domain
  • 3.2.2 Changing the Domain Name and Check Boxes
  • 3.2.3 Deleting a Domain
  • 3.3 Model Elements
  • 3.3.1 Domain Settings
  • 3.3.2 Metadata Fields
  • 3.3.3 Data Locations
  • 3.3.4 Blacklists
  • 3.3.5 Matching
  • 3.4 Save, Compile, and Build
  • 3.5 Knowledge Portal
  • 3.5.1 Listing All Concepts
  • 3.5.2 Analyzing a Specified Entity
  • 3.5.3 Limiting the Data to Return
  • 3.6 Indexing Results
  • 3.6.1 Indexed Sentences
  • 3.6.2 Concepts and CRCs
  • Chapter 4: 
     
  • 4.1 Swagger
  • 4.1.1 Returning iKnow Data Using Swagger
  • 4.2 REST Operations
  • 4.2.1 Domains and Configurations
  • 4.2.2 Sources
  • 4.2.3 Entities
  • 4.2.4 Sentences
  • 4.2.5 Paths and CRCs
  • 4.2.6 Dictionaries and Matching
  • 4.2.7 Blacklists
  • Chapter 5: 
     
  • 5.1 iKnow Domains
  • 5.1.1 Defining a Domain as a Subclass
  • 5.1.2 Defining a Domain Programmatically
  • 5.1.3 Setting Domain Parameters
  • 5.1.4 Assigning to a Domain
  • 5.1.5 Deleting All Data from a Domain
  • 5.1.6 Listing All Domains
  • 5.1.7 Renaming a Domain
  • 5.1.8 Copying a Domain
  • 5.2 iKnow Configurations
  • 5.2.1 Defining a Configuration
  • 5.2.2 Setting Configuration Properties
  • 5.2.3 Using a Configuration
  • 5.2.4 Listing All Configurations
  • 5.2.5 Using a Configuration to Normalize a String
  • 5.3 iKnow UserDictionary
  • 5.3.1 UserDictionary Format
  • 5.3.2 Defining a UserDictionary as an Object Instance
  • 5.3.3 Defining a UserDictionary as a File
  • Chapter 6: 
     
  • 6.1 Loader
  • 6.1.1 Loader Error Logging
  • 6.1.2 Loader Reset()
  • 6.2 Lister
  • 6.2.1 Initializing a Lister
  • 6.2.2 Overriding Lister Instance Defaults
  • 6.2.3 Lister Assigns IDs to Sources
  • 6.2.4 Lister Defaults Example
  • 6.2.5 Lister Parameters
  • 6.2.6 Batch or List?
  • 6.3 Listing and Loading Examples
  • 6.3.1 Loading Files
  • 6.3.2 Loading SQL Records
  • 6.3.3 Loading Elements of a Subscripted Global
  • 6.3.4 Loading a String
  • 6.4 Updating the Domain Contents
  • 6.4.1 Adding Sources
  • 6.4.2 Deleting Sources
  • 6.5 Loading a Virtual Source
  • 6.5.1 Deleting a Virtual Source
  • 6.6 Copying and Re-indexing Loaded Source Data
  • 6.6.1 UserDictionary and Copied Sources
  • Chapter 7: 
     
    Chapter 8: 
     
  • 8.1 Types of Queries
  • 8.2 Queries Described in this Chapter
  • 8.3 Query Method Parameters
  • 8.4 Counting Sources and Sentences
  • 8.5 Counting Entities
  • 8.6 Listing Top Entities
  • 8.6.1 GetTop(): Most-Frequently-Occurring Entities
  • 8.6.2 GetTopTFIDF() and GetTopBM25()
  • 8.7 CRC Queries
  • 8.7.1 Listing CRCs that Contain Entities
  • 8.7.2 Counting Sources that Contain a CRC
  • 8.7.3 Listing Sources or Sentences that Fulfill a CRC Mask
  • 8.8 Listing Similar Entities
  • 8.8.1 Parts and N-grams
  • 8.9 Listing Related Entities
  • 8.9.1 Limiting by Position
  • 8.10 Counting Paths
  • 8.11 Listing Similar Sources
  • 8.12 Summarizing a Source
  • 8.12.1 Custom Summaries
  • 8.13 Querying a Subset of the Sources
  • Chapter 9: 
     
  • 9.1 Negation
  • 9.1.1 Properties of Formal Negation
  • 9.1.2 Using Negation Attributes
  • 9.1.3 Negation Attribute Structure
  • 9.1.4 Negation Bit Map
  • 9.1.5 Negation and Dictionary Matching
  • 9.1.6 Negation Examples
  • 9.1.7 Adding Negation Terms
  • 9.1.8 Negation Special Cases
  • 9.2 Sentiment
  • 9.2.1 Using Sentiment Attributes
  • Chapter 10: 
     
  • 10.1 Configuring Stemming
  • 10.1.1 Hunspell
  • 10.2 Stem Retrieval Methods
  • 10.3 Using Stems
  • Chapter 11: 
     
  • 11.1 Creating a Blacklist
  • 11.1.1 Blacklists and Domains
  • 11.2 Queries that Support Blacklists
  • 11.2.1 Blacklist Query Example
  • Chapter 12: 
     
  • 12.1 Supported Filters
  • 12.2 Filtering by the ID of the Source
  • 12.2.1 By External Id
  • 12.2.2 By Source Id
  • 12.3 Filtering a Random Selection of Sources
  • 12.4 Filtering by Number of Sentences
  • 12.5 Filtering by Entity Match
  • 12.5.1 Filtering by Dictionary Match
  • 12.6 Filtering by Indexing Date Metadata
  • 12.7 Filtering by User-defined Metadata
  • 12.7.1 Metadata Filter Operators
  • 12.8 Filtering by SQL Query
  • 12.9 Filter Modes
  • 12.10 Using GroupFilter to Combine Multiple Filters
  • Chapter 13: 
     
  • 13.1 Text Categorization Implementation
  • 13.1.1 Implementation Interfaces
  • 13.2 Establishing a Training Set and a Test Set
  • 13.3 Building a Text Classifier Programmatically
  • 13.3.1 Create a Text Classifier
  • 13.3.2 Populate the Terms Dictionary
  • 13.3.3 Run the Classification Optimizer
  • 13.3.4 Generate the Text Classifier
  • 13.4 Testing a Text Classifier
  • 13.4.1 Using Test Results
  • 13.5 Building a Text Classifier Using the UI
  • 13.5.1 Define a Data Set for the UI
  • 13.5.2 Build a Text Classifier
  • 13.5.3 Optimize the Text Classifier
  • 13.5.4 Test the Text Classifier against a Test Set of Data
  • 13.5.5 Test the Text Classifier on Uncategorized Data
  • 13.6 Using a Text Classifier
  • Chapter 14: 
     
  • 14.1 Semantic Dominance
  • 14.1.1 Dominance in Context
  • 14.1.2 Concepts of Semantic Dominance
  • 14.1.3 Semantic Dominance Examples
  • 14.2 Semantic Proximity
  • 14.2.1 Japanese Semantic Proximity
  • 14.2.2 Proximity Examples
  • Chapter 15: 
     
  • 15.1 Implementing Custom Metrics
  • 15.2 Types and Targets
  • 15.3 Copying Metrics
  • Chapter 16: 
     
  • 16.1 Introducing Dictionary Structure and Matching
  • 16.1.1 Terminology
  • 16.2 Creating a Dictionary
  • 16.2.1 Dictionaries and Domains
  • 16.2.2 Dictionary Creation Examples
  • 16.2.3 Defining a Format Term
  • 16.2.4 Multiple Formats in a Dictionary Term
  • 16.3 Listing and Copying Dictionaries
  • 16.3.1 Listing Existing Dictionaries
  • 16.3.2 Copying Dictionaries
  • 16.4 Extending Dictionary Constructs
  • Chapter 17: 
     
  • 17.1 How Dictionary Matching Works
  • 17.1.1 Match Scoring
  • 17.2 Matching A String
  • 17.2.1 Matching an Entity String
  • 17.2.2 Matching a Sentence String
  • 17.3 Matching Sources
  • 17.4 Defining a Matching Profile
  • 17.4.1 Matching Profile Properties
  • 17.4.2 Domain Default Matching Profile
  • Chapter 18: 
     
  • 18.1 How to Display iKnow User Interfaces
  • 18.2 Abstract Portal
  • 18.3 Abstract Source Viewer
  • 18.4 Loading Wizard
  • 18.5 Knowledge Portal
  • 18.6 Basic Portal
  • 18.7 Indexing Results
  • 18.8 Matching Results
  • Chapter 19: 
     
  • 19.1 iKnow Shell Interface
  • 19.1.1 List, Show, and Summarize Sources
  • 19.1.2 Filter Sources
  • 19.2 iKnow Data Upgrade Utility
  • 19.2.1 Notes on Specific Version Upgrades
  • Chapter 20: 
     
  • 20.1 Available Web Services
  • 20.2 Using an iKnow Web Service
  • 20.3 Example
  • 20.4 Comparison of iKnow Web Services with Primary iKnow APIs
  • 20.5 See Also
  • Chapter 21: 
     
  • 21.1 KPI Terminology
  • 21.2 Defining a KPI That Uses an iKnow Query
  • 21.3 Available KPI Filters
  • 21.4 Overriding the KPI Properties
  • 21.5 Example
  • 21.6 Creating a Dashboard to Display the KPI
  • 21.6.1 Creating Dashboards: Basics
  • 21.6.2 Changing the Series Names
  • 21.6.3 Configuring the Properties
  • 21.6.4 Adding Previous Page and Next Page Buttons
  • 21.6.5 Example Dashboard with iKnow KPI
  • 21.7 Providing Access to Dashboards
  • 21.8 See Also
  • Chapter 22: 
     
  • 22.1 Custom Lister
  • 22.1.1 Lister name
  • 22.1.2 SplitFullRef() and BuildFullRef()
  • 22.1.3 Default Processor
  • 22.1.4 Expand List
  • 22.2 Custom Processor
  • 22.2.1 Metadata
  • 22.3 Custom Converter
  • 22.3.1 %OnNew
  • 22.3.2 Buffer String
  • 22.3.3 Convert
  • 22.3.4 Next Converted Part
  • Chapter 23: 
     
  • 23.1 Configuring Automatic Language Identification
  • 23.2 Using Automatic Language Identification
  • 23.2.1 Language Identification Queries
  • 23.3 Overriding Automatic Language Identification
  • 23.4 Language-Specific Issues
  • Chapter 24: 
     
  • 24.1 Indexing Sources for iFind Search
  • 24.1.1 Indexing a JSON Object
  • 24.2 Performing iFind Search
  • 24.2.1 Validating a search-items String
  • 24.2.2 Fuzzy Search
  • 24.2.3 Stemming and Decompounding
  • 24.2.4 Languages Not Supported by the iKnow Engine
  • 24.3 iFind Examples
  • 24.3.1 Basic Syntax Examples
  • 24.3.2 Semantic Syntax Examples
  •  
    Appendix A: 
     
    Appendix B: 
     
  • B.1 Overview
  • B.1.1 Background
  • B.1.2 Relationship between a Cube and iKnow Sources
  • B.2 Generating iKnow Source Metadata Fields for an Associated DeepSee Cube
  • B.2.1 Prerequisites
  • B.2.2 Generating the Metadata Fields from the Cube
  • B.2.3 Using DeepSee Filters with an iKnow KPI
  • B.3 Generating DeepSee Cubes for an iKnow Domain
  • B.3.1 Generating the Cubes
  • B.3.2 A Brief Look at the Analyzer and the Cubes
  • B.3.3 Rebuilding the Cubes
  • B.4 See Also