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Incremental Encoding
Incremental encoding, also known as front compression, back compression, or front coding, is a type of delta encoding compression algorithm whereby common prefixes or suffixes and their lengths are recorded so that they need not be duplicated. This algorithm is particularly well-suited for compressing sorted data, e.g., a list of words from a dictionary. For example: The encoding used to store the common prefix length itself varies from application to application. Typical techniques are storing the value as a single byte; delta encoding, which stores only the change in the common prefix length; and various universal codes. It may be combined with other general lossless data compression techniques such as entropy encoding and dictionary coders to compress the remaining suffixes. Applications Incremental encoding is widely used in information retrieval to compress the lexicons used in search indexes; these list all the words found in all the documents and a pointer for each ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Delta Encoding
Delta encoding is a way of storing or transmitting data in the form of '' differences'' (deltas) between sequential data rather than complete files; more generally this is known as data differencing. Delta encoding is sometimes called delta compression, particularly where archival histories of changes are required (e.g., in revision control software). The differences are recorded in discrete files called "deltas" or "diffs". In situations where differences are small – for example, the change of a few words in a large document or the change of a few records in a large table – delta encoding greatly reduces data redundancy. Collections of unique deltas are substantially more space-efficient than their non-encoded equivalents. From a logical point of view the difference between two data values is the information required to obtain one value from the other – see relative entropy. The difference between identical values (under some equivalence) is often called ''0'' or the neut ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Compression Algorithm
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder. The process of reducing the size of a data file is often referred to as data compression. In the context of data transmission, it is called source coding; encoding done at the source of the data before it is stored or transmitted. Source coding should not be confused with channel coding, for error detection and correction or line coding, the means for mapping data onto a signal. Co ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Prefix (linguistics)
A prefix is an affix which is placed before the stem of a word. Adding it to the beginning of one word changes it into another word. For example, when the prefix ''un-'' is added to the word ''happy'', it creates the word ''unhappy''. Particularly in the study of languages, a prefix is also called a preformative, because it alters the form of the words to which it is affixed. Prefixes, like other affixes, can be either inflectional, creating a new form of the word with the same basic meaning and same lexical category (but playing a different role in the sentence), or derivational, creating a new word with a new semantic meaning and sometimes also a different lexical category. Prefixes, like all other affixes, are usually bound morphemes. In English, there are no inflectional prefixes; English uses suffixes instead for that purpose. The word ''prefix'' is itself made up of the stem ''fix'' (meaning "attach", in this case), and the prefix ''pre-'' (meaning "before"), both of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Affix
In linguistics, an affix is a morpheme that is attached to a word stem to form a new word or word form. Affixes may be derivational, like English ''-ness'' and ''pre-'', or inflectional, like English plural ''-s'' and past tense ''-ed''. They are bound morphemes by definition; prefixes and suffixes may be separable affixes. Affixation is the linguistic process that speakers use to form different words by adding morphemes at the beginning (prefixation), the middle (infixation) or the end (suffixation) of words. Positional categories of affixes ''Prefix'' and ''suffix'' may be subsumed under the term ''adfix'', in contrast to ''infix.'' When marking text for interlinear glossing, as in the third column in the chart above, simple affixes such as prefixes and suffixes are separated from the stem with hyphens. Affixes which disrupt the stem, or which themselves are discontinuous, are often marked off with angle brackets. Reduplication is often shown with a tilde. Affixes which c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sorting
Sorting refers to ordering data in an increasing or decreasing manner according to some linear relationship among the data items. # ordering: arranging items in a sequence ordered by some criterion; # categorizing: grouping items with similar properties. Ordering items is the combination of categorizing them based on equivalent order, and ordering the categories themselves. Sorting information or data In , arranging in an ordered sequence is called "sorting". Sorting is a common operation in many applications, and efficient algorithms to perform it have been developed. The most common uses of sorted sequences are: * making lookup or search efficient; * making merging of sequences efficient. * enable processing of data in a defined order. The opposite of sorting, rearranging a sequence of items in a random or meaningless order, is called shuffling. For sorting, either a weak order, "should not come after", can be specified, or a strict weak order, "should come before" (specif ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data
In the pursuit of knowledge, data (; ) is a collection of discrete values that convey information, describing quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures. Data may be used as variables in a computational process. Data may represent abstract ideas or concrete measurements. Data is commonly used in scientific research, economics, and in virtually every other form of human organizational activity. Examples of data sets include price indices (such as consumer price index), unemployment rates, literacy rates, and census data. In this context, data represents the raw facts and figures which can be used in such a manner in order to capture the useful information out of it. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Word
A word is a basic element of language that carries an semantics, objective or pragmatics, practical semantics, meaning, can be used on its own, and is uninterruptible. Despite the fact that language speakers often have an intuitive grasp of what a word is, there is no consensus among linguistics, linguists on its definition and numerous attempts to find specific criteria of the concept remain controversial. Different standards have been proposed, depending on the theoretical background and descriptive context; these do not converge on a single definition. Some specific definitions of the term "word" are employed to convey its different meanings at different levels of description, for example based on phonology, phonological, grammar, grammatical or orthography, orthographic basis. Others suggest that the concept is simply a convention used in everyday situations. The concept of "word" is distinguished from that of a morpheme, which is the smallest unit of language that has a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dictionary
A dictionary is a listing of lexemes from the lexicon of one or more specific languages, often arranged alphabetically (or by radical and stroke for ideographic languages), which may include information on definitions, usage, etymologies, pronunciations, translation, etc.Webster's New World College Dictionary, Fourth Edition, 2002 It is a lexicographical reference that shows inter-relationships among the data. A broad distinction is made between general and specialized dictionaries. Specialized dictionaries include words in specialist fields, rather than a complete range of words in the language. Lexical items that describe concepts in specific fields are usually called terms instead of words, although there is no consensus whether lexicology and terminology are two different fields of study. In theory, general dictionaries are supposed to be semasiological, mapping word to definition, while specialized dictionaries are supposed to be onomasiological, first identifying ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Universal Code (data Compression)
In data compression, a universal code for integers is a prefix code that maps the positive integers onto binary codewords, with the additional property that whatever the true probability distribution on integers, as long as the distribution is monotonic (i.e., ''p''(''i'') ≥ ''p''(''i'' + 1) for all positive ''i''), the expected lengths of the codewords are within a constant factor of the expected lengths that the optimal code for that probability distribution would have assigned. A universal code is ''asymptotically optimal'' if the ratio between actual and optimal expected lengths is bounded by a function of the information entropy of the code that, in addition to being bounded, approaches 1 as entropy approaches infinity. In general, most prefix codes for integers assign longer codewords to larger integers. Such a code can be used to efficiently communicate a message drawn from a set of possible messages, by simply ordering the set of messages b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lossless Data Compression
Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. Lossless compression is possible because most real-world data exhibits statistical redundancy. By contrast, lossy compression permits reconstruction only of an approximation of the original data, though usually with greatly improved compression rates (and therefore reduced media sizes). By operation of the pigeonhole principle, no lossless compression algorithm can efficiently compress all possible data. For this reason, many different algorithms exist that are designed either with a specific type of input data in mind or with specific assumptions about what kinds of redundancy the uncompressed data are likely to contain. Therefore, compression ratios tend to be stronger on human- and machine-readable documents and code in comparison to entropic binary data (random bytes). Lossless data compression is used in many ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Entropy Encoding
In information theory, an entropy coding (or entropy encoding) is any lossless data compression method that attempts to approach the lower bound declared by Shannon's source coding theorem, which states that any lossless data compression method must have expected code length greater or equal to the entropy of the source. More precisely, the source coding theorem states that for any source distribution, the expected code length satisfies \mathbb E_ (d(x))\geq \mathbb E_ \log_b(P(x))/math>, where l is the number of symbols in a code word, d is the coding function, b is the number of symbols used to make output codes and P is the probability of the source symbol. An entropy coding attempts to approach this lower bound. Two of the most common entropy coding techniques are Huffman coding and arithmetic coding. If the approximate entropy characteristics of a data stream are known in advance (especially for signal compression), a simpler static code may be useful. These static codes in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dictionary Coder
A dictionary coder, also sometimes known as a substitution coder, is a class of lossless data compression algorithms which operate by searching for matches between the text to be compressed and a set of strings contained in a data structure (called the 'dictionary') maintained by the encoder. When the encoder finds such a match, it substitutes a reference to the string's position in the data structure. Methods and applications Some dictionary coders use a 'static dictionary', one whose full set of strings is determined before coding begins and does not change during the coding process. This approach is most often used when the message or set of messages to be encoded is fixed and large; for instance, an application that stores the contents of a book in the limited storage space of a PDA generally builds a static dictionary from a concordance of the text and then uses that dictionary to compress the verses. This scheme of using Huffman coding to represent indices into a concordanc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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