Forward index
A forward index is a data structure that maps each document to the terms, features, or fields it contains.
Natural Language Processing in Action, Second Edition
A forward index maps each document to the words or features it contains.
- How it is used
- Supports full-text search by organizing document contents before retrieval structures are created.
- How deep it goes
- Defines document-word listings and their inversion, but stops short of detailed implementation or storage design.
- Examples
- Uses documents containing “cat” and “cats,” word positions, and direct lookup versus document-by-document scanning.
- What you can do after
- Evaluate how document-first listings become inverted structures for faster keyword retrieval.
Read how Natural Language Processing in Action, Second Edition explains forward index →
AI-Powered Search
A forward index is a data structure that maps each document and field to the terms contained in that document.
- How it is used
- Supports faceting, aggregations, semantic traversal, and ranking over indexed search results.
- How deep it goes
- Defines document-to-term mapping and describes doc values and query-time uninversion, without detailing storage internals.
- Examples
- Uses three documents with job_title, desc, and skills fields to contrast forward and inverted mappings.
- What you can do after
- Understand how search engines generate facets and support relationship traversal from document-field term data.
Related concepts
- inverted indexproduces · An inverted index is a data structure that maps terms or tokens to the documents, records, or locations in which they occur.
- knowledge graphused by · A knowledge graph is a graph-structured representation of entities and their semantically meaningful relationships, often including associated attributes or facts.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.