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Later research on short-term memory and working memory revealed that memory span is not a constant even when measured in a number of chunks. The number of chunks a human can recall immediately after presentation depends on the category of chunks used (e.g., span is around seven for digits, around six for letters, and around five for words), and even on features of the chunks within a category.
In data deduplication, data synchronization and remote data compression, Chunking is a process to split a file into smaller pieces called chunks by the chunking algorithm. It can help to eliminate duplicate copies of repeating data on storage, or reduces the amount of data sent over the network by only selecting changed chunks.
Whenever a match occurs, the redundant chunk is replaced with a small reference that points to the stored chunk. Given that the same byte pattern may occur dozens, hundreds, or even thousands of times (the match frequency is dependent on the chunk size), the amount of data that must be stored or transferred can be greatly reduced.
A modality effect is present in chunking. That is, the mechanism used to convey the list of items to the individual affects how much "chunking" occurs. Experimentally, it has been found that auditory presentation results in a larger amount of grouping in the responses of individuals than visual presentation does. Previous literature, such as George Miller's The Magical Number Seven, Plus or ...
Chunking may mean: . Chunking (division), an approach for doing simple mathematical division sums, by repeated subtraction Chunking (computational linguistics), a method for parsing natural language sentences into partial syntactic structures
A memory address a is said to be n-byte aligned when a is a multiple of n (where n is a power of 2). In this context, a byte is the smallest unit of memory access, i.e. each memory address specifies a different byte.
A column family is a database object that contains columns of related data. It is a tuple (pair) that consists of a key–value pair , where the key is mapped to a value that is a set of columns. In analogy with relational databases, a column family is as a "table", each key-value pair being a "row".
It can be used directly as the hash code, or a hash function applied to it to map the potentially large value to the hash table size. The value of a is usually a prime number large enough to hold the number of different characters in the character set of potential keys. Radix conversion hashing of strings minimizes the number of collisions. [15]