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  2. Text mining - Wikipedia

    en.wikipedia.org/wiki/Text_mining

    Text mining. Text mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." [1] Written resources may include websites, books, emails ...

  3. Sentiment analysis - Wikipedia

    en.wikipedia.org/wiki/Sentiment_analysis

    Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as ...

  4. Web scraping - Wikipedia

    en.wikipedia.org/wiki/Web_scraping

    Web scraping is the process of automatically mining data or collecting information from the World Wide Web. It is a field with active developments sharing a common goal with the semantic web vision, an ambitious initiative that still requires breakthroughs in text processing, semantic understanding, artificial intelligence and human-computer interactions.

  5. Data extraction - Wikipedia

    en.wikipedia.org/wiki/Data_extraction

    Data extraction. Data extraction is the act or process of retrieving data out of (usually unstructured or poorly structured) data sources for further data processing or data storage (data migration). The import into the intermediate extracting system is thus usually followed by data transformation and possibly the addition of metadata prior to ...

  6. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is "a concept to unify statistics, data analysis, informatics, and their related methods " to "understand and analyze actual phenomena " with data. [5] It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. [6]

  7. Randomness extractor - Wikipedia

    en.wikipedia.org/wiki/Randomness_extractor

    A randomness extractor, often simply called an "extractor", is a function, which being applied to output from a weak entropy source, together with a short, uniformly random seed, generates a highly random output that appears independent from the source and uniformly distributed. [1] Examples of weakly random sources include radioactive decay or ...

  8. List of file signatures - Wikipedia

    en.wikipedia.org/wiki/List_of_file_signatures

    List of file signatures. This is a list of file signatures, data used to identify or verify the content of a file. Such signatures are also known as magic numbers or Magic Bytes. Many file formats are not intended to be read as text. If such a file is accidentally viewed as a text file, its contents will be unintelligible.

  9. WordStat - Wikipedia

    en.wikipedia.org/wiki/WordStat

    Relate unstructured text with structured data such as dates, numbers or categorical data for identifying temporal trends or differences between subgroups or for assessing relationship with ratings or other kind of categorical or numerical data. Visualization tools to visualize and interpret text analysis results: Dendrogram with optional bar chart