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NLP Python Toolkit for TIBCO Spotfire®
This Python toolkit contains natural language processing (NLP) functions that provide exploratory analysis of text data.
Supported version TIBCO Spotfire 10.7 and higher, tested on 11.3 (Created in TIBCO Spotfire 11.3 with Python 3.8, library versions: pandas-1.2.3, nltk-3.6.2, scipy-1.6.3, spacy-3.0.6, spacytextblob-3.0, scikit-learn-0.24.2 numpy-1.20.1)
Supported version TIBCO Spotfire 10.7 and higher, tested on 11.3
(Created in TIBCO Spotfire 11.3 with Python 3.8, library versions: pandas-1.2.3, nltk-3.6.2, scipy-1.6.3, spacy-3.0.6, spacytextblob-3.0, scikit-learn-0.24.2 numpy-1.20.1)
This release includes data functions that preprocess or clean text, extract n-gram features, and tag entities in any English text using a combination of NLP methods and algorithms. The preprocessing steps include removing stop words, removing special characters, removing numbers, and performing text normalization like stemming or lemmatization. The n-gram features show the most frequent n-grams and top keywords per document. The tagging functions perform named entity recognition, part-of-speech tagging, and sentiment analysis.
Installing the data function
Follow the online guide available here to register a data function in Spotfire
Configuring the data function
Each data function may require inputs from the Spotfire analysis and will return outputs to the Spotfire analysis. For each data function these need to be configured once the data function is registered. To learn about how to configure data functions in Spotfire please view this YouTube Data Function guide, and for more information on Spotfire visit the Spotfire Enablement Hub
Published: May 2022
- Fixes to minor bugs
- Remove N-gram Keywords that don't appear in original text
- Options to Choose any Langauge Model
- Make more Parameters Optional
- Data function
- Dxp with example usage
- License information
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