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  2. Interval tree - Wikipedia

    en.wikipedia.org/wiki/Interval_tree

    In a simple case, the intervals do not overlap and they can be inserted into a simple binary search tree and queried in (⁡) time. However, with arbitrarily overlapping intervals, there is no way to compare two intervals for insertion into the tree since orderings sorted by the beginning points or the ending points may be different.

  3. Comparison of programming languages (list comprehension)

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

    List comprehension is a syntactic construct available in some programming languages for creating a list based on existing lists. It follows the form of the mathematical set-builder notation (set comprehension) as distinct from the use of map and filter functions.

  4. Interval scheduling - Wikipedia

    en.wikipedia.org/wiki/Interval_scheduling

    A subset of intervals is compatible if no two intervals overlap on the machine/resource. For example, the subset {A,C} is compatible, as is the subset {B}; but neither {A,B} nor {B,C} are compatible subsets, because the corresponding intervals within each subset overlap. The interval scheduling maximization problem (ISMP) is to find a

  5. Overlap coefficient - Wikipedia

    en.wikipedia.org/wiki/Overlap_coefficient

    The overlap coefficient, [note 1] or Szymkiewicz–Simpson coefficient, [citation needed] [3] [4] [5] is a similarity measure that measures the overlap between two finite sets.It is related to the Jaccard index and is defined as the size of the intersection divided by the size of the smaller of two sets:

  6. Lexical similarity - Wikipedia

    en.wikipedia.org/wiki/Lexical_similarity

    In linguistics, lexical similarity is a measure of the degree to which the word sets of two given languages are similar. A lexical similarity of 1 (or 100%) would mean a total overlap between vocabularies, whereas 0 means there are no common words. There are different ways to define the lexical similarity and the results vary accordingly.

  7. Longest common substring - Wikipedia

    en.wikipedia.org/wiki/Longest_common_substring

    One can find the lengths and starting positions of the longest common substrings of and in (+) time with the help of a generalized suffix tree. A faster algorithm can be achieved in the word RAM model of computation if the size σ {\displaystyle \sigma } of the input alphabet is in 2 o ( log ⁡ ( n + m ) ) {\displaystyle 2^{o\left({\sqrt {\log ...

  8. Packing problems - Wikipedia

    en.wikipedia.org/wiki/Packing_problems

    Each packing problem has a dual covering problem, which asks how many of the same objects are required to completely cover every region of the container, where objects are allowed to overlap. In a bin packing problem, people are given: A container, usually a two- or three-dimensional convex region, possibly of infinite size. Multiple containers ...

  9. Merge algorithm - Wikipedia

    en.wikipedia.org/wiki/Merge_algorithm

    A list containing a single element is, by definition, sorted. Repeatedly merge sublists to create a new sorted sublist until the single list contains all elements. The single list is the sorted list. The merge algorithm is used repeatedly in the merge sort algorithm. An example merge sort is given in the illustration.