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  2. Mnemonic peg system - Wikipedia

    en.wikipedia.org/wiki/Mnemonic_peg_system

    Several studies have investigated the use of this memory mnemonic as a form of an imagery-based memory system within the process of learning a second-language. [7] For example, if a native English speaker is attempting to learn Spanish, he will notice that the Spanish for duck is pato, which is pronounced similarly to the English word pot.

  3. List of mnemonics - Wikipedia

    en.wikipedia.org/wiki/List_of_mnemonics

    List of mnemonics for the cranial nerves, their respective type and foramen NERVE: Olfactory nerve Optic nerve Oculomotor nerve Pathic (Trochlear) nerve Trigeminal (dentist) nerve Abducens nerve Facial nerve Vestibulo-cochlear (Auditory) nerve Glosso-pharyngeal nerve Vagus nerve Spinal Accessory nerve Hypoglossal nerve Ophthalmic: Maxillary ...

  4. Trie - Wikipedia

    en.wikipedia.org/wiki/Trie

    Each terminal node is associated with a list of URLs—called occurrence list—to pages that match the keyword. The trie is stored in the main memory, whereas the occurrence is kept in an external storage, frequently in large clusters, or the in-memory index points to documents stored in an external location. [32]

  5. Log-structured merge-tree - Wikipedia

    en.wikipedia.org/wiki/Log-structured_merge-tree

    In LSM-trees, write operations are designed to optimize performance by reducing random I/O and leveraging sequential disk writes. When a write operation is initiated, the data is first buffered in an in-memory component, often implemented using a sorted data structure such as a Skip list or B+ tree.

  6. B-tree - Wikipedia

    en.wikipedia.org/wiki/B-tree

    A B-tree grows slower with growing data amount, than the linearity of a linked list. Compared to a skip list, both structures have the same performance, but the B-tree scales better for growing n. A T-tree, for main memory database systems, is similar but more compact.

  7. Linked list - Wikipedia

    en.wikipedia.org/wiki/Linked_list

    A balanced tree has similar memory access patterns and space overhead to a linked list while permitting much more efficient indexing, taking O(log n) time instead of O(n) for a random access. However, insertion and deletion operations are more expensive due to the overhead of tree manipulations to maintain balance.