full-text-search
Version 0.2.1.4 revision 1 uploaded by MikolajKonarski.
Package meta
- Synopsis
- In-memory full text search engine
- Description
An in-memory full text search engine library. It lets you run full-text queries on a collection of your documents.
Features:
Keyword queries and auto-complete/auto-suggest queries.
Can search over any type of "document". (You explain how to extract search terms from them.)
Supports documents with multiple fields (e.g. title, body)
Supports documents with non-term features (e.g. quality score, page rank)
Uses the state of the art BM25F ranking function
Adjustable ranking parameters (including field weights and non-term feature scores)
In-memory but quite compact. It does not keep a copy of your original documents.
Quick incremental index updates, making it possible to keep your text search in-sync with your data.
It is independent of the document type, so you have to write the document-specific parts: extracting search terms and any stop words, case-normalisation or stemming. This is quite easy using libraries such as tokenize and snowball.
The source package includes a demo to illustrate how to use the library. The demo is a simplified version of how the library is used in the hackage-server where it provides the backend for the package search feature.
- Author
- Duncan Coutts
- Bug reports
- https://github.com/well-typed/full-text-search/issues
- Category
- Data, Text, Search
- Copyright
- 2013-2014 Duncan Coutts, 2014 Well-Typed LLP, 2014 IRIS Connect Ltd.
- Homepage
- n/a
- Maintainer
- Duncan Coutts <duncan@well-typed.com>
- Package URL
- n/a
- Stability
- n/a