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Full-text
In text retrieval, full-text search refers to techniques for searching a single computer-stored document or a collection in a full-text database. Full-text search is distinguished from searches based on metadata or on parts of the original texts represented in databases (such as titles, abstracts, selected sections, or bibliographical references). In a full-text search, a search engine examines all of the words in every stored document as it tries to match search criteria (for example, text specified by a user). Full-text-searching techniques became common in online bibliographic databases in the 1990s. Many websites and application programs (such as word processing software) provide full-text-search capabilities. Some web search engines, such as AltaVista, employ full-text-search techniques, while others index only a portion of the web pages examined by their indexing systems. Indexing When dealing with a small number of documents, it is possible for the full-text-search engine ...
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Search Index
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 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 engines ...
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Full-text Database
A full-text database or a complete-text database is a database that contains the complete text of books, dissertations, journals, magazines, newspapers or other kinds of textual documents. They differ from bibliographic databases (which contain only bibliographical metadata, including abstracts in some cases) and non-bibliographic databases (such as directories and numeric databases). One of the earliest systems was IBM STAIRS, introduced in 1973. Full-text databases became common about 1990 when computer storage technology made them economic and technologically possible. There are two main classes: an extension of the classical bibliographical databases into full-text databases (e.g. on hosts such as BRS, Dialog, LexisNexis and Westlaw) and Internet-based full-text databases (based on search engines or XML). See also * Digital library * Full-text search In text retrieval, full-text search refers to techniques for searching a single computer-stored document or a coll ...
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Information Retrieval
Information retrieval (IR) in computing and information science is the process of obtaining information system resources that are relevant to an information need from a collection of those resources. Searches can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds. Automated information retrieval systems are used to reduce what has been called information overload. An IR system is a software system that provides access to books, journals and other documents; stores and manages those documents. Web search engines are the most visible IR applications. Overview An information retrieval process begins when a user or searcher enters a query into the system. Queries are formal statements of information needs, for example search strings in web search engines. In ...
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Concordance (publishing)
A concordance is an alphabetical list of the principal words used in a book or body of work, listing every instance of each word with its immediate context. Concordances have been compiled only for works of special importance, such as the Vedas, Bible, Qur'an or the works of Shakespeare, James Joyce or classical Latin and Greek authors, because of the time, difficulty, and expense involved in creating a concordance in the pre- computer era. A concordance is more than an index, with additional material such as commentary, definitions and topical cross-indexing which makes producing one a labor-intensive process even when assisted by computers. In the precomputing era, search technology was unavailable, and a concordance offered readers of long works such as the Bible something comparable to search results for every word that they would have been likely to search for. Today, the ability to combine the result of queries concerning multiple terms (such as searching for words ne ...
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Search Engine
A search engine is a software system designed to carry out web searches. They search the World Wide Web in a systematic way for particular information specified in a textual web search query. The search results are generally presented in a line of results, often referred to as search engine results pages (SERPs). When a user enters a query into a search engine, the engine scans its index of web pages to find those that are relevant to the user's query. The results are then ranked by relevancy and displayed to the user. The information may be a mix of links to web pages, images, videos, infographics, articles, research papers, and other types of files. Some search engines also mine data available in databases or open directories. Unlike web directories and social bookmarking sites, which are maintained by human editors, search engines also maintain real-time information by running an algorithm on a web crawler. Any internet-based content that can't be indexed and sea ...
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AltaVista
AltaVista was a Web search engine established in 1995. It became one of the most-used early search engines, but lost ground to Google and was purchased by Yahoo! in 2003, which retained the brand, but based all AltaVista searches on its own search engine. On July 8, 2013, the service was shut down by Yahoo!, and since then the domain has redirected to Yahoo!'s own search site. Etymology The word "AltaVista" is formed from the words for "high view" or "upper view" in Spanish (alta + vista); thus, it colloquially translates to "overview". Origins AltaVista was created by researchers at Digital Equipment Corporation's Network Systems Laboratory and Western Research Laboratory who were trying to provide services to make finding files on the public network easier. Paul Flaherty came up with the original idea, along with Louis Monier and Michael Burrows, who wrote the Web crawler and indexer, respectively. The name "AltaVista" was chosen in relation to the surroundings of th ...
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Document Retrieval
Document retrieval is defined as the matching of some stated user query against a set of free-text records. These records could be any type of mainly unstructured text, such as newspaper articles, real estate records or paragraphs in a manual. User queries can range from multi-sentence full descriptions of an information need to a few words. Document retrieval is sometimes referred to as, or as a branch of, text retrieval. Text retrieval is a branch of information retrieval where the information is stored primarily in the form of text. Text databases became decentralized thanks to the personal computer. Text retrieval is a critical area of study today, since it is the fundamental basis of all internet search engines. Description Document retrieval systems find information to given criteria by matching text records (''documents'') against user queries, as opposed to expert systems that answer questions by inferring over a logical knowledge database. A document retrieval syst ...
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Tag (metadata)
In information systems, a tag is a keyword or term assigned to a piece of information (such as an Internet bookmark, multimedia, database record, or computer file). This kind of metadata helps describe an item and allows it to be found again by browsing or searching. Tags are generally chosen informally and personally by the item's creator or by its viewer, depending on the system, although they may also be chosen from a controlled vocabulary. Tagging was popularized by websites associated with Web 2.0 and is an important feature of many Web 2.0 services. It is now also part of other database systems, desktop applications, and operating systems. Overview People use tags to aid classification, mark ownership, note boundaries, and indicate online identity. Tags may take the form of words, images, or other identifying marks. An analogous example of tags in the physical world is museum object tagging. People were using textual keywords to classify information and obje ...
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Relevance (information Retrieval)
In information science and information retrieval, relevance denotes how well a retrieved document or set of documents meets the information need of the user. Relevance may include concerns such as timeliness, authority or novelty of the result. History The concern with the problem of finding relevant information dates back at least to the first publication of scientific journals in the 17th century. The formal study of relevance began in the 20th Century with the study of what would later be called bibliometrics. In the 1930s and 1940s, S. C. Bradford used the term "relevant" to characterize articles relevant to a subject (cf., Bradford's law). In the 1950s, the first information retrieval systems emerged, and researchers noted the retrieval of irrelevant articles as a significant concern. In 1958, B. C. Vickery made the concept of relevance explicit in an address at the International Conference on Scientific Information. Since 1958, information scientists have explored and ...
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Type I And Type II Errors
In statistical hypothesis testing, a type I error is the mistaken rejection of an actually true null hypothesis (also known as a "false positive" finding or conclusion; example: "an innocent person is convicted"), while a type II error is the failure to reject a null hypothesis that is actually false (also known as a "false negative" finding or conclusion; example: "a guilty person is not convicted"). Much of statistical theory revolves around the minimization of one or both of these errors, though the complete elimination of either is a statistical impossibility if the outcome is not determined by a known, observable causal process. By selecting a low threshold (cut-off) value and modifying the alpha (α) level, the quality of the hypothesis test can be increased. The knowledge of type I errors and type II errors is widely used in medical science, biometrics and computer science. Intuitively, type I errors can be thought of as errors of ''commission'', i.e. the researcher unlu ...
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Electronic Discovery
Electronic discovery (also ediscovery or e-discovery) refers to discovery in legal proceedings such as litigation, government investigations, or Freedom of Information Act requests, where the information sought is in electronic format (often referred to as electronically stored information or ESI). Electronic discovery is subject to rules of civil procedure and agreed-upon processes, often involving review for privilege and relevance before data are turned over to the requesting party. Electronic information is considered different from paper information because of its intangible form, volume, transience and persistence. Electronic information is usually accompanied by metadata that is not found in paper documents and that can play an important part as evidence (e.g. the date and time a document was written could be useful in a copyright case). The preservation of metadata from electronic documents creates special challenges to prevent spoliation. In the United States, at ...
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Bayesian Inference
Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. Bayesian inference is an important technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the Sequential analysis, dynamic analysis of a sequence of data. Bayesian inference has found application in a wide range of activities, including science, engineering, philosophy, medicine, sport, and law. In the philosophy of decision theory, Bayesian inference is closely related to subjective probability, often called "Bayesian probability". Introduction to Bayes' rule Formal explanation Bayesian inference derives the posterior probability as a consequence relation, consequence of two Antecedent (logic), antecedents: a prior probability and a "likelihood function" derived from a statistical model for the observed data. Bayesian inference computes ...
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