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In computer science, a list or sequence is a collection of items that are finite in number and in a particular order. An instance of a list is a computer representation of the mathematical concept of a tuple or finite sequence. A list may contain the same value more than once, and each occurrence is considered a distinct item.
Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words.
Computing the position of a particular unique tuple or matrix in a de Bruijn sequence or torus is known as the de Bruijn decoding problem. Efficient O ( n log n ) {\displaystyle \color {Blue}O(n\log n)} decoding algorithms exist for special, recursively constructed sequences [ 17 ] and extend to the two-dimensional case.
The data type should preferably be immutable if possible. It is common for implementations to handle equality testing, serialization and model binding. The strongly typed identifier commonly wraps the data type used as the primary key in the database, such as a string, an integer or universally unique identifier (UUID).
The first number of the pair indicates type: −1 – directive type, the second number is ignored, the following line is one of these keywords: BOT – beginning of tuple (start of row) EOD – end of data; 0 – numeric type, value is the second number, the following line is one of these keywords: V – valid; NA – not available; ERROR ...
The ordered sequential types are lists (dynamic arrays), tuples, and strings. All sequences are indexed positionally (0 through length - 1) and all but strings can contain any type of object, including multiple types in the same sequence. Both strings and tuples are immutable, making them perfect candidates for dictionary keys (see below).
It disregards word order (and thus most of syntax or grammar) but captures multiplicity. The bag-of-words model is commonly used in methods of document classification where, for example, the (frequency of) occurrence of each word is used as a feature for training a classifier. [1] It has also been used for computer vision. [2]
The empty list is the initial state, and f interprets one word at a time, either as a function name, taking two numbers from the head of the list and pushing the result back in, or parsing the word as a floating-point number and prepending it to the list.