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  2. Automatic item generation - Wikipedia

    en.wikipedia.org/wiki/Automatic_Item_Generation

    Automatic item generation (AIG), or automated item generation, is a process linking psychometrics with computer programming. It uses a computer algorithm to automatically create test items that are the basic building blocks of a psychological test .

  3. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.

  4. Artificial general intelligence - Wikipedia

    en.wikipedia.org/wiki/Artificial_general...

    The simulation model must be sufficiently faithful to the original, so that it behaves in practically the same way as the original brain. [118] Whole brain emulation is a type of brain simulation that is discussed in computational neuroscience and neuroinformatics , and for medical research purposes.

  5. Graph matching - Wikipedia

    en.wikipedia.org/wiki/Graph_matching

    The case of exact graph matching is known as the graph isomorphism problem. [1] The problem of exact matching of a graph to a part of another graph is called subgraph isomorphism problem . Inexact graph matching refers to matching problems when exact matching is impossible, e.g., when the number of vertices in the two graphs are different.

  6. Prediction by partial matching - Wikipedia

    en.wikipedia.org/wiki/Prediction_by_partial_matching

    Prediction by partial matching (PPM) is an adaptive statistical data compression technique based on context modeling and prediction. PPM models use a set of previous symbols in the uncompressed symbol stream to predict the next symbol in the stream. PPM algorithms can also be used to cluster data into predicted groupings in cluster analysis.

  7. Predictive mean matching - Wikipedia

    en.wikipedia.org/wiki/Predictive_mean_matching

    Predictive mean matching (PMM) [1] is a widely used [2] statistical imputation method for missing values, first proposed by Donald B. Rubin in 1986 [3] and R. J. A. Little in 1988. [ 4 ] It aims to reduce the bias introduced in a dataset through imputation, by drawing real values sampled from the data. [ 5 ]

  8. 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]

  9. Pattern matching - Wikipedia

    en.wikipedia.org/wiki/Pattern_matching

    will match elements such as A[1], A[2], or more generally A[x] where x is any entity. In this case, A is the concrete element, while _ denotes the piece of tree that can be varied. A symbol prepended to _ binds the match to that variable name while a symbol appended to _ restricts the matches to nodes of that