GETTING STARTED
SearchAssist Overview
SearchAssist Introduction
Onboarding SearchAssist
Build your first App
Glossary
Release Notes
What's new in SearchAssist
Previous Versions

CONCEPTS
Managing Sources
Introduction
Files
Web Pages
FAQs
Structured Data 
Connectors
Introduction to Connectors
Azure Storage Connector
Confluence Cloud Connector
Confluence Server Connector
Custom Connector
DotCMS Connector
Dropbox Connector
Google Drive Connector
Oracle Knowledge Connector
Salesforce Connector
ServiceNow Connector
SharePoint Connector
Zendesk Connector
RACL
Virtual Assistants
Managing Indices
Introduction
Index Fields
Traits
Workbench
Introduction to Workbench
Field Mapping
Entity Extraction
Traits Extraction
Keyword Extraction
Exclude Document
Semantic Meaning
Snippet Extraction
Custom LLM Prompts
Index Settings
Index Languages
Managing Chunks
Chunk Browser
Managing Relevance
Introduction
Weights
Highlighting
Presentable
Synonyms
Stop Words
Search Relevance
Spell Correction
Prefix Search
Custom Configurations
Personalizing Results
Introduction
Answer Snippets
Introduction
Extractive Model
Generative Model
Enabling Both Models
Simulation and Testing
Debugging
Best Practices and Points to Remember
Troubleshooting Answers
Answer Snippets Support Across Content Sources
Result Ranking
Facets
Business Rules
Introduction
Contextual Rules
NLP Rules
Engagement
Small Talk
Bot Actions
Designing Search Experience
Introduction
Search Interface
Result Templates
Testing
Preview and Test
Debug Tool
Running Experiments
Introduction
Experiments
Analyzing Search Performance
Overview
Dashboard
User Engagement
Search Insights
Result Insights
Answer Insights

ADMINISTRATION
General Settings
Credentials
Channels
Team
Collaboration
Integrations
OpenAI Integration
Azure OpenAI Integration
Custom Integration
Billing and Usage
Plan Details
Usage Logs
Order and Invoices
Smart Hibernation

SearchAssist APIs
API Introduction
API List

SearchAssist SDK

HOW TOs
Use Custom Fields to Filter Search Results and Answers
Add Custom Metadata to Ingested Content
Write Painless Scripts
Configure Business Rules for Generative Answers

Keyword Extraction

Keyword Extraction is a technique to automatically detect important words from the text stored in a field.

The Keyword Extraction stage in Index Pipeline allows you to identify a set of keywords from a source field and save the identified keywords in a target field so that it can be used to identify the intention of the search user better. SearchAssist supports various NLP algorithms to extract keywords.

You can:

  • Define a condition for the keyword extraction stage. The keywords will be extracted only from the documents that satisfy the given condition.
  • Re-order or delete keyword extractions.
  • Simulate the changes before saving them.

Ensure to Train your app each time you make changes to any index configuration. This builds the index based on the updated configurations.

Configuration

To configure keyword extraction, follow the below steps:

  1. Click the Indices tab on the top.
  2. On the left pane, under the Index Configuration section, click Workbench.
  3. On the Workbench (Index Configuration) page, on the Stages column, click the + icon.
  4. On the right column, select Keyword Extraction from the Stage Type drop-down list.
  5. Enter a name in the Stage Name field.
  6. Enter a condition in the Condition field.  You can add multiple conditions using the AND/OR connectors. Documents that satisfy the condition will be executed as part of the stage. See below for details.
  7. Select the field you want to extract keyword from as Source Field
  8. Define where you want to store the extracted keyword as Target Field. This field is created by the application.
  9. Choose a model from the Choose Model drop-down list. See below for details.
  10. Click Simulate to verify the configurations. The simulator displays the Source and the number of documents to which the mapping was applied, and the result. You can change the Source (if not mentioned in the condition) and the number of documents.
  11. Once done, click Save Configuration on the top-right.

Models

The following models are supported:

  • Topic Rank – It is a method to extract keyphrases from the most important topics of a document.
  • Position Rank – It is a method to capture both highly frequent words or phrases and their position in a document. 
  • Multi-partite Rank – It is a keyphrase extraction method that encodes topical information within a multi-partite graph structure.

Conditions

Condition is of the following format: ctx.field_name==value or ctx.field_name!=value. The field_name can be obtained from the Fields table under Index Configuration.

For example, ctx.contentType=="web" to restrict the extraction from the content from a web source.

Keyword Extraction

Keyword Extraction is a technique to automatically detect important words from the text stored in a field.

The Keyword Extraction stage in Index Pipeline allows you to identify a set of keywords from a source field and save the identified keywords in a target field so that it can be used to identify the intention of the search user better. SearchAssist supports various NLP algorithms to extract keywords.

You can:

  • Define a condition for the keyword extraction stage. The keywords will be extracted only from the documents that satisfy the given condition.
  • Re-order or delete keyword extractions.
  • Simulate the changes before saving them.

Ensure to Train your app each time you make changes to any index configuration. This builds the index based on the updated configurations.

Configuration

To configure keyword extraction, follow the below steps:

  1. Click the Indices tab on the top.
  2. On the left pane, under the Index Configuration section, click Workbench.
  3. On the Workbench (Index Configuration) page, on the Stages column, click the + icon.
  4. On the right column, select Keyword Extraction from the Stage Type drop-down list.
  5. Enter a name in the Stage Name field.
  6. Enter a condition in the Condition field.  You can add multiple conditions using the AND/OR connectors. Documents that satisfy the condition will be executed as part of the stage. See below for details.
  7. Select the field you want to extract keyword from as Source Field
  8. Define where you want to store the extracted keyword as Target Field. This field is created by the application.
  9. Choose a model from the Choose Model drop-down list. See below for details.
  10. Click Simulate to verify the configurations. The simulator displays the Source and the number of documents to which the mapping was applied, and the result. You can change the Source (if not mentioned in the condition) and the number of documents.
  11. Once done, click Save Configuration on the top-right.

Models

The following models are supported:

  • Topic Rank – It is a method to extract keyphrases from the most important topics of a document.
  • Position Rank – It is a method to capture both highly frequent words or phrases and their position in a document. 
  • Multi-partite Rank – It is a keyphrase extraction method that encodes topical information within a multi-partite graph structure.

Conditions

Condition is of the following format: ctx.field_name==value or ctx.field_name!=value. The field_name can be obtained from the Fields table under Index Configuration.

For example, ctx.contentType=="web" to restrict the extraction from the content from a web source.