full-text-search: In-memory full text search engine
An in-memory full text search engine library. It lets you run full-text queries on a collection of your documents.
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.
|Versions [RSS] [faq]||0.2.0.0, 0.2.1.0, 0.2.1.1, 0.2.1.3, 0.2.1.4|
|Dependencies||array (==0.4.*), base (>=4.5 && <4.7), bytestring, Cabal (>=1.14 && <1.20), containers (>=0.4 && <0.6), directory, filepath, full-text-search, mtl, snowball (==1.0.*), split (==0.2.*), tar, text (>=0.11 && <1.2), time, tokenize (==0.1.*), transformers, vector (==0.10.*) [details]|
|Copyright||2013-2014 Duncan Coutts, 2014 Well-Typed LLP, 2014 IRIS Connect Ltd.|
|Maintainer||Duncan Coutts <email@example.com>|
|Category||Data, Text, Search|
|Source repo||head: darcs get http://code.haskell.org/full-text-search/|
|Uploaded||by DuncanCoutts at 2014-05-29T13:47:07Z|
|Downloads||4503 total (53 in the last 30 days)|
|Rating||(no votes yet) [estimated by Bayesian average]|
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