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  2. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    For example, the data mining step might identify multiple groups in the data, which can then be used to obtain more accurate prediction results by a decision support system. Neither the data collection, data preparation, nor result interpretation and reporting is part of the data mining step, although they do belong to the overall KDD process ...

  3. Examples of data mining - Wikipedia

    en.wikipedia.org/wiki/Examples_of_data_mining

    [6] Data mining can be helpful to organizations. Organizational Data Mining (ODM) is defined as leveraging data mining (DM) tools and technologies to enhance organizational decision-making process by transforming data into valuable and actionable knowledge in order to gain a strategic and business competitive advantage.

  4. Cross-industry standard process for data mining - Wikipedia

    en.wikipedia.org/wiki/Cross-industry_standard...

    Daimler-Benz had a significant data mining team. OHRA was starting to explore the potential use of data mining. The first version of the methodology was presented at the 4th CRISP-DM SIG Workshop in Brussels in March 1999, [5] and published as a step-by-step data mining guide later that year. [6]

  5. Data preprocessing - Wikipedia

    en.wikipedia.org/wiki/Data_Preprocessing

    Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...

  6. SEMMA - Wikipedia

    en.wikipedia.org/wiki/SEMMA

    The phases of SEMMA and related tasks are the following: [2] Sample.The process starts with data sampling, e.g., selecting the data set for modeling.The data set should be large enough to contain sufficient information to retrieve, yet small enough to be used efficiently.

  7. List of text mining methods - Wikipedia

    en.wikipedia.org/wiki/List_of_text_mining_methods

    Different text mining methods are used based on their suitability for a data set. Text mining is the process of extracting data from unstructured text and finding patterns or relations. Below is a list of text mining methodologies. Centroid-based Clustering: Unsupervised learning method. Clusters are determined based on data points. [1]

  8. Online analytical processing - Wikipedia

    en.wikipedia.org/wiki/Online_analytical_processing

    [6]: 402–403 Consolidation involves the aggregation of data that can be accumulated and computed in one or more dimensions. For example, all sales offices are rolled up to the sales department or sales division to anticipate sales trends. By contrast, the drill-down is a technique that allows users to navigate through the details.

  9. Text mining - Wikipedia

    en.wikipedia.org/wiki/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, reviews, and ...