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  2. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    The word with embeddings most similar to the topic vector might be assigned as the topic's title, whereas far away word embeddings may be considered unrelated. As opposed to other topic models such as LDA , top2vec provides canonical ‘distance’ metrics between two topics, or between a topic and another embeddings (word, document, or otherwise).

  3. Spark NLP - Wikipedia

    en.wikipedia.org/wiki/Spark_NLP

    Spark NLP for Healthcare is a commercial extension of Spark NLP for clinical and biomedical text mining. [10] It provides healthcare-specific annotators, pipelines, models, and embeddings for clinical entity recognition, clinical entity linking, entity normalization, assertion status detection, de-identification, relation extraction, and spell checking and correction.

  4. Comparison of programming languages (string functions)

    en.wikipedia.org/wiki/Comparison_of_programming...

    String functions are used in computer programming languages to manipulate a string or query information about a string (some do both).. Most programming languages that have a string datatype will have some string functions although there may be other low-level ways within each language to handle strings directly.

  5. Approximate string matching - Wikipedia

    en.wikipedia.org/wiki/Approximate_string_matching

    With the availability of large amounts of DNA data, matching of nucleotide sequences has become an important application. [1] Approximate matching is also used in spam filtering. [5] Record linkage is a common application where records from two disparate databases are matched. String matching cannot be used for most binary data, such as images ...

  6. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Features extracted include word stems. Distractor features included. 2600 Text Classification 2008 [91] Reuters: Google Books N-grams N-grams from a very large corpus of books None. 2.2 TB of text Text Classification, clustering, regression 2011 [92] [93] Google Personae Corpus Collected for experiments in Authorship Attribution and Personality ...

  7. Matching wildcards - Wikipedia

    en.wikipedia.org/wiki/Matching_wildcards

    In computer science, an algorithm for matching wildcards (also known as globbing) is useful in comparing text strings that may contain wildcard syntax. [1] Common uses of these algorithms include command-line interfaces, e.g. the Bourne shell [2] or Microsoft Windows command-line [3] or text editor or file manager, as well as the interfaces for some search engines [4] and databases. [5]

  8. Record linkage - Wikipedia

    en.wikipedia.org/wiki/Record_linkage

    Record linkage (also known as data matching, data linkage, entity resolution, and many other terms) is the task of finding records in a data set that refer to the same entity across different data sources (e.g., data files, books, websites, and databases).

  9. Pattern matching - Wikipedia

    en.wikipedia.org/wiki/Pattern_matching

    Thus, to match "any amount of trailing characters", a new wildcard ___ is needed in contrast to _ that would match only a single character. In Haskell and functional programming languages in general, strings are represented as functional lists of characters. A functional list is defined as an empty list, or an element constructed on an existing ...