Project

Reverse Dependencies for fast-stemmer

The projects listed here declare fast-stemmer as a runtime or development dependency

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Hoatzin is a text classifier in Ruby that uses SVM for it's classification.
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The Huginn Naive Bayes agent uses some incoming Events as a training set for Naive Bayes Machine Learning. Then it classifies Events from other sources accordingly using tags. Acts as a Huginn Agent front end to the NBayes gem (https://github.com/oasic/nbayes).
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Same as hunt, but excluding mongo_mapper as a dependency
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Jekyll plugin to show related posts based on the content, tags, and categories. The similarity is calculated using TF-IDF(term frequency-inverted document frequency). Since tags and categories are use-defined values, those are considered with higher weights than a content while calculating.
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enable mongodb's new fulltext simply and quickly on your mongoid models, including pagination.
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Bayesian and Latent Semantic Indexing classification of text.
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Jekyll plugin to show related posts based on the content, tags, and categories. The similarity is calculated using TF-IDF(term frequency-inverted document frequency). Since tags and categories are use-defined values, those are considered with higher weights than a content while calculating.
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Simple text processing for small data sets.
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Calculate TF-IDF out of a text, resulting in a hash with term as key, frequency as value. Sorry for taking the convenient name for myself! See examples/demo_tf.rb for usage
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Metapackage to install gems provided by Turbot.
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Yet Another Naive Bayes Implementation
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