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  2. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    The use of different model parameters and different corpus sizes can greatly affect the quality of a word2vec model. Accuracy can be improved in a number of ways, including the choice of model architecture (CBOW or Skip-Gram), increasing the training data set, increasing the number of vector dimensions, and increasing the window size of words ...

  3. Gensim - Wikipedia

    en.wikipedia.org/wiki/Gensim

    Gensim is an open-source library for unsupervised topic modeling, document indexing, retrieval by similarity, and other natural language processing functionalities, using modern statistical machine learning. Gensim is implemented in Python and Cython for performance. Gensim is designed to handle large text collections using data streaming and ...

  4. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]

  5. Vector space model - Wikipedia

    en.wikipedia.org/wiki/Vector_space_model

    Gensim is a Python+NumPy framework for Vector Space modelling. It contains incremental (memory-efficient) algorithms for term frequency-inverse document frequency, latent semantic indexing, random projections and latent Dirichlet allocation. Weka. Weka is a popular data mining package for Java including WordVectors and Bag Of Words models ...

  6. Latent semantic analysis - Wikipedia

    en.wikipedia.org/wiki/Latent_semantic_analysis

    The probabilistic model of LSA does not match observed data: LSA assumes that words and documents form a joint Gaussian model (ergodic hypothesis), while a Poisson distribution has been observed. Thus, a newer alternative is probabilistic latent semantic analysis, based on a multinomial model, which is reported to give better results than ...

  7. System dynamics - Wikipedia

    en.wikipedia.org/wiki/System_dynamics

    System dynamics is a methodology and mathematical modeling technique to frame, understand, and discuss complex issues and problems. Originally developed in the 1950s to help corporate managers improve their understanding of industrial processes, SD is currently being used throughout the public and private sector for policy analysis and design.

  8. Sanger sequencing - Wikipedia

    en.wikipedia.org/wiki/Sanger_sequencing

    Fluorescent ddNTP molecules. The classical chain-termination method requires a single-stranded DNA template, a DNA primer, a DNA polymerase, normal deoxynucleotide triphosphates (), and modified di-deoxynucleotide triphosphates (), the latter of which terminate DNA strand elongation.

  9. Document Object Model - Wikipedia

    en.wikipedia.org/wiki/Document_Object_Model

    The Document Object Model (DOM) is a cross-platform and language-independent interface that treats an HTML or XML document as a tree structure wherein each node is an object representing a part of the document. The DOM represents a document with a logical tree.