ElasticSearch based text analytics.

Implementation of:

• Single document significant terms - Trello board (private)
• Classification - Trello board (private)
• Sentiment analysis - Trello board (private)

There is currently partial experimental support for some linguistic analysis of Norwegian Bokmål. This support depends on the following resources:

• Norwegian Dependency Treebank (NDT) (freely available, permissive licensing).
• Norsk Ordbank (available on request, GPL or commercial licensing).

Norsk Ordbank must be obtained separately and unzipped in the data directory for it to be used automatically by linguistic processing components.

Currently a simple application of the UAX29 standard for Unicode tokenization. Will be expanded to handle hyphens in accordance with Norwegian norms.

tokenizer = NOTokenizer()
tokenizer.tokenize(u'Vi er konsulenter, med fokus på søk!')

[u'Vi',
 u'er',
 u'konsulenter',
 u',',
 u'med',
 u'fokus',
 u'på',
 u'søk',
 u'!']

Adds part of speech descriptions. THe default annotation is a very simplified version of the one used by Norsk Ordbank and NDT.

tagger = NOBTagger()
tagger.tag(u'Vi spiste lunsj ute i det fine været.')

[(u'Vi', 'PRON_PERS'),
 (u'spiste', 'VERB'),
 (u'lunsj', 'SUBST'),
 (u'ute', 'PREP'),
 (u'i', 'PREP'),
 (u'det', 'DET'),
 (u'fine', 'ADJ'),
 (u'været', 'SUBST'),
 (u'.', 'PUNKT')]

Evaluation of the tagger precision is forthcoming, but users should expect a reasonable error rate given the limited trraining data available.

Based on Norsk Ordbank. It is possible to pass the part of speech tag in order to disambiguate words which can have more than one lemma form.

sent = tagger.tag(u'Vi er godt forberedt.')
[(word, lem.lemmatize(word, tag)) for word, tag in sent]

[(u'Vi', u'vi'),
 (u'er', u'være'),
 (u'godt', u'god'),
 (u'forberedt', u'forberedt'),
 (u'.', u'.')]

Simple heuristics based decompounder based on the word forms in Norsk Ordbank. This can overgenerate so it should primarily be used on wellformed text.

dec = NOBDecompounder()
dec.decompound(u'lampekostbatteri'), dec.decompound(u'søkekonsulenter')

[u'lampe', u'kost', u'batteri'], [u'søke', u'konsulenter']

In order to set up up a Vagrant development server run:

vagrant up
fab vagrant provision_server

#Installation notes

To use the tagger, decompounder and lemmatizer you will need to download Norsk ordbank. You can download it by registering at http://www.edd.uio.no/prosjekt/ordbanken/

You will need to build models for the tagger, by running:

from es_text_analytics.tagger import install_hunpos
install_hunpos()
comperio-text-analytics\python-client\bin\build-all-models.bat