free_text_search
Search a inverted positional index and return ranked references to documents relevant to the search phrase.
THIS PACKAGE IS IN BETA DEVELOPMENT AND SUBJECT TO DAILY BREAKING CHANGES.
Objective
The compoments of this library:
- parse a free-text phrase to a query;
- search the
dictionary
andpostings
of a textindex
for the queryterms
; - perform iterative scoring and ranking of the returned dictionary entries and postings; and
- return ranked references to documents relevant to the search phrase.
API
class FreeTextQuery
class QueryParser
Usage
TODO: describe usage.
Definitions
The following definitions are used throughout the documentation:
corpus
– the collection ofdocuments
for which anindex
is maintained.dictionary
– is a hash ofterms
(vocabulary
) to the frequency of occurence in thecorpus
documents.document
– a record in thecorpus
, that has a unique identifier (docId
) in thecorpus
‘s primary key and that contains one or more text fields that are indexed.index
– an inverted index used to look updocument
references from thecorpus
against avocabulary
ofterms
. The implementation in this package builds and maintains a positional inverted index, that also includes the positions of the indexedterm
in eachdocument
.postings
– a separate index that records whichdocuments
thevocabulary
occurs in. In this implementation we also record the positions of eachterm
in thetext
to create a positional invertedindex
.postings list
– a record of the positions of aterm
in adocument
. A position of aterm
refers to the index of theterm
in an array that contains all theterms
in thetext
.term
– a word or phrase that is indexed from thecorpus
. Theterm
may differ from the actual word used in the corpus depending on thetokenizer
used.text
– the indexable content of adocument
.token
– representation of aterm
in a text source returned by atokenizer
. The token may include information about theterm
such as its position(s) in the text or frequency of occurrence.tokenizer
– a function that returns a collection oftoken
s fromtext
, after applying a character filter,term
filter, stemmer and / or lemmatizer.vocabulary
– the collection ofterms
indexed from thecorpus
.
References
- Manning, Raghavan and Schütze, “Introduction to Information Retrieval“, Cambridge University Press, 2008
- University of Cambridge, 2016 “Information Retrieval“, course notes, Dr Ronan Cummins, 2016
- Wikipedia (1), “Inverted Index“, from Wikipedia, the free encyclopedia
- Wikipedia (2), “Lemmatisation“, from Wikipedia, the free encyclopedia
- Wikipedia (3), “Stemming“, from Wikipedia, the free encyclopedia
Issues
If you find a bug please fill an issue.
This project is a supporting package for a revenue project that has priority call on resources, so please be patient if we don’t respond immediately to issues or pull requests.