Project
Reverse Dependencies for fast-stemmer
The projects listed here declare fast-stemmer as a runtime or development dependency
0.33
A general classifier module to allow Bayesian and other types of classifications.
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0.33
A general classifier module to allow Bayesian and other types of classifications.
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Pismo extracts and retrieves content-related metadata from HTML pages - you can use the resulting data in an organized way, such as a summary/first paragraph, body text, keywords, RSS feed URL, favicon, etc.
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0.24
Simple full text search implementation.
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0.24
2 methods are provided for now - (1) naive bayes implementation + (2) tf-idf weights
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0.07
A document vector search with flexible matrix transforms. Currently supports Latent semantic analysis and Term frequency - inverse document frequency
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0.06
Text classifier with HBase, Cassandra, or Mongo storage
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0.03
Markov chains for all your friends~
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0.02
Really basic search for MongoMapper models.
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0.02
Proper related posts plugin for Jekyll - uses document correlation matrix on TF-IDF (optionally with Latent Semantic Indexing).
Each document is tokenized and stemmed, every word found is treated as keyword for analysis (except for some stop words).
TF-IDF matrix for the whole site is calculated (including extra provided weights), then if given accuraccy is lower than 1.0, LSI algorithm is used to compute new simplified vector space. Document correlation matrix is created using dot product of the matrix and its transpose.
For each of the post' related documents are inserted into priority queue (sorted by score from document correlation matrix), assuming the score is greater than minimal required score. Selected few bests related posts are retrieven from the queue.
Liquid template for each post is rendered and <related-posts /> is replaced with the outcomes of algorithm.
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0.01
Chimera is an object mapper for Riak and Redis. The idea is to mix the advantages of Riak
(scalability, massive data storage) with Redis (atomicity, performance, data structures).
You should store the bulk of your data in Riak, and then use Redis data structures where
appropriate (for example, a counter or set of keys).
Internally, Chimera uses Redis for any indexes you define as well as some default indexes
that are automatically created. There's no built in sharding for Redis, but since it's
only being used for key storage and basic data elements you should be able to go a long
way with one Redis server (especially if you use the new Redis VM).
!! Chimera is alpha. It's not production tested and needs a better test suite. !!
!! It's also only tested in Ruby 1.9. !!
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0.01
GloVe is an unsupervised learning algorithm for obtaining vector representations for words. Training is performed on aggregated global word-word co-occurrence statistics from a corpus, and the resulting representations showcase interesting linear substructures of the word vector space. This is a pure Ruby implementation of GloVe utilizing GSL.
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0.01
Bayesian and Latent Semantic Indexing classification of text.
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0.0
Allows for reverse indexing selected ActiveRecord models. Handles searching and return of objects
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0.0
A framework for building interactive twitterbots which generate tweets based on pseudo-Markov texts models and respond to mentions/DMs/favs/rts.
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0.0
A general classifier module to allow Bayesian and other types of classifications.
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0.0
Classifier module using Bayesian's theorem.
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0.0
Interface for API on machinelearning.devingaffney.com
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0.0
Simple POP3 and SMTP implementation in EventMachine for use in the Rubot framework
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0.0
A naive bayes text classification algorithm built in C++, with a Ruby interface using Rice
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