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Search Engine Indexing
Search engine indexing is the collecting, parsing, and storing of data to facilitate fast and accurate information retrieval. Index design incorporates interdisciplinary concepts from linguistics, cognitive psychology, mathematics, informatics, and computer science. An alternate name for the process, in the context of search engines designed to find web pages on the Internet, is ''web indexing''. Popular search engines focus on the full-text indexing of online, natural language documents. Media types such as pictures, video, audio, and graphics are also searchable. Meta search engines reuse the indices of other services and do not store a local index whereas cache-based search engines permanently store the index along with the corpus. Unlike full-text indices, partial-text services restrict the depth indexed to reduce index size. Larger services typically perform indexing at a predetermined time interval due to the required time and processing costs, while agent-based search en ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parsing
Parsing, syntax analysis, or syntactic analysis is a process of analyzing a String (computer science), string of Symbol (formal), symbols, either in natural language, computer languages or data structures, conforming to the rules of a formal grammar by breaking it into parts. The term ''parsing'' comes from Latin ''pars'' (''orationis''), meaning Part of speech, part (of speech). The term has slightly different meanings in different branches of linguistics and computer science. Traditional Sentence (linguistics), sentence parsing is often performed as a method of understanding the exact meaning of a sentence or word, sometimes with the aid of devices such as sentence diagrams. It usually emphasizes the importance of grammatical divisions such as subject (grammar), subject and predicate (grammar), predicate. Within computational linguistics the term is used to refer to the formal analysis by a computer of a sentence or other string of words into its constituents, resulting in a par ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lexical Analysis
Lexical tokenization is conversion of a text into (semantically or syntactically) meaningful ''lexical tokens'' belonging to categories defined by a "lexer" program. In case of a natural language, those categories include nouns, verbs, adjectives, punctuations etc. In case of a programming language, the categories include identifiers, operators, grouping symbols, data types and language keywords. Lexical tokenization is related to the type of tokenization used in large language models (LLMs) but with two differences. First, lexical tokenization is usually based on a lexical grammar, whereas LLM tokenizers are usually probability-based. Second, LLM tokenizers perform a second step that converts the tokens into numerical values. Rule-based programs A rule-based program, performing lexical tokenization, is called ''tokenizer'', or ''scanner'', although ''scanner'' is also a term for the first stage of a lexer. A lexer forms the first phase of a compiler frontend in processing. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Extendible Hashing
Extendible hashing is a type of hash system which treats a hash as a bit string and uses a trie for bucket lookup. Because of the hierarchical nature of the system, re-hashing is an incremental operation (done one bucket at a time, as needed). This means that time-sensitive applications are less affected by table growth than by standard full-table rehashes. Extendible hashing was described by Ronald Fagin in 1979. Practically all modern filesystems use either extendible hashing or B-trees. In particular, the Global File System, ZFS, and the SpadFS filesystem use extendible hashing. "Section 4.1.6 Extendible hashing: ZFS and GFS" and "Table 4.1: Directory organization in filesystems" Example Assume that the hash function h(k) returns a string of bits. The first i bits of each string will be used as indices to figure out where they will go in the "directory" (hash table), where i is the smallest number such that the index of every item in the table is unique. Keys to be used ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Trie
In computer science, a trie (, ), also known as a digital tree or prefix tree, is a specialized search tree data structure used to store and retrieve strings from a dictionary or set. Unlike a binary search tree, nodes in a trie do not store their associated key. Instead, each node's ''position'' within the trie determines its associated key, with the connections between nodes defined by individual Character (computing), characters rather than the entire key. Tries are particularly effective for tasks such as autocomplete, spell checking, and IP routing, offering advantages over hash tables due to their prefix-based organization and lack of hash collisions. Every child node shares a common prefix (computer science), prefix with its parent node, and the root node represents the empty string. While basic trie implementations can be memory-intensive, various optimization techniques such as compression and bitwise representations have been developed to improve their efficiency. A n ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Suffix Tree
In computer science, a suffix tree (also called PAT tree or, in an earlier form, position tree) is a compressed trie containing all the suffixes of the given text as their keys and positions in the text as their values. Suffix trees allow particularly fast implementations of many important string operations. The construction of such a tree for the string S takes time and space linear in the length of S. Once constructed, several operations can be performed quickly, such as locating a substring in S, locating a substring if a certain number of mistakes are allowed, and locating matches for a regular expression pattern. Suffix trees also provided one of the first linear-time solutions for the longest common substring problem. These speedups come at a cost: storing a string's suffix tree typically requires significantly more space than storing the string itself. History The concept was first introduced by . Rather than the suffix S ..n/math>, Weiner stored in his trie the ''prefix ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Replication (computer Science)
Replication in computing refers to maintaining multiple copies of data, processes, or resources to ensure consistency across redundant components. This fundamental technique spans database management system, databases, file system, file systems, and distributed computing, distributed systems, serving to improve high availability, availability, fault-tolerance, accessibility, and performance. Through replication, systems can continue operating when components fail (failover), serve requests from geographically distributed locations, and balance load across multiple machines. The challenge lies in maintaining consistency between replicas while managing the fundamental tradeoffs between data consistency, system availability, and Network partition, network partition tolerance – constraints known as the CAP theorem. Terminology Replication in computing can refer to: * ''Data replication'', where the same data is stored on multiple data storage device, storage devices * ''Computation ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hash Function
A hash function is any Function (mathematics), function that can be used to map data (computing), data of arbitrary size to fixed-size values, though there are some hash functions that support variable-length output. The values returned by a hash function are called ''hash values'', ''hash codes'', (''hash/message'') ''digests'', or simply ''hashes''. The values are usually used to index a fixed-size table called a ''hash table''. Use of a hash function to index a hash table is called ''hashing'' or ''scatter-storage addressing''. Hash functions and their associated hash tables are used in data storage and retrieval applications to access data in a small and nearly constant time per retrieval. They require an amount of storage space only fractionally greater than the total space required for the data or records themselves. Hashing is a computationally- and storage-space-efficient form of data access that avoids the non-constant access time of ordered and unordered lists and s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Partition (database)
A partition is a division of a logical database or its constituent elements into distinct independent parts. Database partitioning refers to intentionally breaking a large database into smaller ones for scalability purposes, distinct from network partitions which are a type of network fault between nodes. In a partitioned database, each piece of data belongs to exactly one partition, effectively making each partition a small database of its own. Database partitioning is normally done for manageability, performance or availability reasons, or for load balancing. It is popular in distributed database management systems, where each partition may be spread over multiple nodes, with users at the node performing local transactions on the partition. This increases performance for sites that have regular transactions involving certain views of data, whilst maintaining availability and security. Partitioning enables distribution of datasets across multiple disks and query loads across mu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Inverted Index
In computer science, an inverted index (also referred to as a postings list, postings file, or inverted file) is a database index storing a mapping from content, such as words or numbers, to its locations in a table, or in a document or a set of documents (named in contrast to a forward index, which maps from documents to content). The purpose of an inverted index is to allow fast full-text searches, at a cost of increased processing when a document is added to the database. The inverted file may be the database file itself, rather than its index. It is the most popular data structure used in document retrieval systems, used on a large scale for example in search engines. Additionally, several significant general-purpose mainframe-based database management systems have used inverted list architectures, including ADABAS, DATACOM/DB, and Model 204. There are two main variants of inverted indexes: A record-level inverted index (or inverted file index or just inverted file) contain ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer Data Storage
Computer data storage or digital data storage is a technology consisting of computer components and Data storage, recording media that are used to retain digital data. It is a core function and fundamental component of computers. The central processing unit (CPU) of a computer is what manipulates data by performing computations. In practice, almost all computers use a storage hierarchy, which puts fast but expensive and small storage options close to the CPU and slower but less expensive and larger options further away. Generally, the fast technologies are referred to as "memory", while slower persistent technologies are referred to as "storage". Even the first computer designs, Charles Babbage's Analytical Engine and Percy Ludgate's Analytical Machine, clearly distinguished between processing and memory (Babbage stored numbers as rotations of gears, while Ludgate stored numbers as displacements of rods in shuttles). This distinction was extended in the Von Neumann archite ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data
Data ( , ) are a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data are usually organized into structures such as tables that provide additional context and meaning, and 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 are commonly used in scientific research, economics, and virtually every other form of human organizational activity. Examples of data sets include price indices (such as the consumer price index), unemployment rates, literacy rates, and census data. In this context, data represent the raw facts and figures from which useful information can be extracted. Data are collected using technique ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Merge (SQL)
A relational database management system uses SQL (also called ''upsert'') statements to INSERT new records or UPDATE or DELETE existing records depending on whether condition matches. It was officially introduced in the SQL:2003 standard, and expanded in the SQL:2008 standard. Usage MERGE INTO tablename USING table_reference ON (condition) WHEN MATCHED THEN UPDATE SET column1 = value1 column2 = value2 ... WHEN NOT MATCHED THEN INSERT (column1 column2 ... VALUES (value1 value2 ...; A right join is employed over the Target (the INTO table) and the Source (the USING table / view / sub-query)--where Target is the left table and Source is the right one. The four possible combinations yield these rules: * If the ON field(s) in the Source matches the ON field(s) in the Target, then UPDATE * If the ON field(s) in the Source does not match the ON field(s) in the Target, then INSERT * If the ON field(s) does not exist in the Source but does exist in the Target, t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
