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Media queries allow content rendering to adapt to different conditions such as screen resolution. Learn the history, usage, media types and features of media queries, and see examples of CSS code.
Similarly, the documents that should be retrieved for a query of the form A and B, should be in the fuzzy set associated with the intersection of the two sets. Hence, it is possible to define the similarity of a document to the or query to be max(d A, d B) and the similarity of the document to the and query to be min(d A, d B).
Evaluation measures for an information retrieval (IR) system assess how well an index, search engine, or database returns results from a collection of resources that satisfy a user's query. They are therefore fundamental to the success of information systems and digital platforms.
Feature scaling is a method to normalize the range of features of data for machine learning algorithms. Learn about rescaling (min-max normalization), mean normalization, standardization, and scaling to unit length, and how they affect convergence and performance.
Learn about the range query problem in computer science, which involves finding values or statistics in a given interval of an array. Explore different solutions, examples and applications of range queries for various functions and data structures.
A large database index would typically use B-tree algorithms. BRIN is not always a substitute for B-tree, it is an improvement on sequential scanning of an index, with particular (and potentially large) advantages when the index meets particular conditions for being ordered and for the search target to be a narrow set of these values.
Learn about the problem of finding the minimal value in a sub-array of an array of comparable objects, and how to solve it efficiently using various algorithms. See definitions, examples, and applications of range minimum queries in computer science.
In computing, the count–min sketch (CM sketch) is a probabilistic data structure that serves as a frequency table of events in a stream of data. It uses hash functions to map events to frequencies, but unlike a hash table uses only sub-linear space , at the expense of overcounting some events due to collisions .