Package smile.nlp.relevance

package smile.nlp.relevance
Term-document relevance ranking algorithms.
  • Class
    Description
    BM25
    The BM25 weighting scheme, often called Okapi weighting, after the system in which it was first implemented, was developed as a way of building a probabilistic model sensitive to term frequency and document length while not introducing too many additional parameters into the model.
    Relevance
    In the context of information retrieval, relevance denotes how well a retrieved set of documents meets the information need of the user.
    RelevanceRanker
    An interface to provide relevance ranking algorithm.
    TFIDF
    The tf-idf weight (term frequency-inverse document frequency) is a weight often used in information retrieval and text mining.