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Using InterSystems IRIS Natural Language Processing (NLP)
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Preface : 
 
Chapter 1: 
 
1.1 A Simple Use Case
1.2 What is NLP?
       1.2.1 What NLP Isn’t
1.3 Logical Text Units Identified by NLP
       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 NLP Globals
2.5 Input Data
2.6 Output Structures
2.7 Constants
2.8 Error Codes
Chapter 3: 
 
3.1 Accessing Architect
3.2 Creating 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 Domain Explorer
3.6 Indexing Results
       3.6.1 Indexed Sentences
       3.6.2 Concepts and CRCs
Chapter 4: 
 
4.1 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 NLP Domains
5.2 NLP Configurations
5.3 NLP UserDictionary
Chapter 6: 
 
6.1 Loader
       6.1.1 Loader Error Logging
       6.1.2 Loader Reset()
6.2 Lister
6.3 Listing and Loading Examples
6.4 Updating the Domain Contents
       6.4.1 Adding Sources
       6.4.2 Deleting Sources
6.5 Loading a Virtual Source
6.6 Copying and Re-indexing Loaded Source Data
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
8.7 CRC Queries
8.8 Listing Similar Entities
       8.8.1 Parts and N-grams
8.9 Listing Related Entities
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
9.2 Sentiment
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
11.2 Queries that Support Blacklists
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
12.6 Filtering by Indexing Date Metadata
12.7 Filtering by User-defined Metadata
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
13.2 Establishing a Training Set and a Test Set
13.3 Building a Text Classifier Programmatically
13.4 Testing a Text Classifier
13.5 Building a Text Classifier Using the UI
13.6 Using a Text Classifier
Chapter 14: 
 
14.1 Semantic Dominance
14.2 Semantic Proximity
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
16.3 Listing and 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
17.3 Matching Sources
17.4 Defining a Matching Profile
Chapter 18: 
 
18.1 How to Display NLP User Interfaces
18.2 Abstract Portal
18.3 Abstract Source Viewer
18.4 Loading Wizard
18.5 Domain Explorer
18.6 Basic Portal
18.7 Indexing Results
18.8 Matching Results
Chapter 19: 
 
19.1 NLP Shell Interface
19.2 NLP Data Upgrade Utility
Chapter 20: 
 
20.1 Available Web Services
20.2 Using an NLP Web Service
20.3 Example
20.4 Comparison of NLP Web Services with Primary NLP APIs
20.5 See Also
Chapter 21: 
 
21.1 KPI Terminology
21.2 Defining a KPI That Uses Text Analytics Query
21.3 Available KPI Filters
21.4 Overriding the KPI Properties
21.5 Example
21.6 Creating a Dashboard to Display the KPI
21.7 Providing Access to Dashboards
21.8 See Also
Chapter 22: 
 
22.1 Custom Lister
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
23.3 Overriding Automatic Language Identification
23.4 Language-Specific Issues
Appendix A: