Misplaced Pages

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44-534: Elasticsearch is a search engine based on Apache Lucene . It provides a distributed, multitenant -capable full-text search engine with an HTTP web interface and schema-free JSON documents. Official clients are available in Java , .NET ( C# ), PHP , Python , Ruby and many other languages. According to the DB-Engines ranking , Elasticsearch is the most popular enterprise search engine. Shay Banon created

88-440: A memex . Bush regarded the notion of “associative indexing” as his key conceptual contribution. As he explained, this was “a provision whereby any item may be caused at will to select immediately and automatically another. This is the essential feature of the memex. The process of tying two items together is the important thing. All of the documents used in the memex would be in the form of microfilm copy acquired as such or, in

132-415: A coordinator to delegate operations to the correct shard(s). Rebalancing and routing are done automatically". Related data is often stored in the same index, which consists of one or more primary shards, and zero or more replica shards. Once an index has been created, the number of primary shards cannot be changed. Elasticsearch is developed alongside the data collection and log -parsing engine Logstash,

176-422: A large, nebulous blob of unstructured resources. They are engineered to follow a multi-stage process: crawling the infinite stockpile of pages and documents to skim the figurative foam from their contents, indexing the foam/buzzwords in a sort of semi-structured form (database or something), and at last, resolving user entries/queries to return mostly relevant results and links to those skimmed documents or pages from

220-611: A popularity rank is older than PageRank. However, In October 2014, Google’s John Mueller confirmed that Google is not going to be updating it (Page Rank) going forward. Other variants of the same idea are currently in use – grade schoolers do the same sort of computations in picking kickball teams. These ideas can be categorized into three main categories: rank of individual pages and nature of web site content. Search engines often differentiate between internal links and external links, because web content creators are not strangers to shameless self-promotion. Link map data structures typically store

264-409: A probabilistic context. To provide a set of matching items that are sorted according to some criteria quickly, a search engine will typically collect metadata about the group of items under consideration beforehand through a process referred to as indexing . The index typically requires a smaller amount of computer storage , which is why some search engines only store the indexed information and not

308-423: A read/write circuit. Concurrent comparison of 64 stored strings with variable length was achieved in 50 ns for an input text stream of 10 million characters/s, permitting performance despite the presence of single character errors in the form of character codes. Furthermore, the chip allowed nonanchor string search and variable-length `don't care' (VLDC) string search. Real-time search The real-time web

352-538: A set of words that identify the desired concept that one or more documents may contain. There are several styles of search query syntax that vary in strictness. It can also switch names within the search engines from previous sites. Whereas some text search engines require users to enter two or three words separated by white space , other search engines may enable users to specify entire documents, pictures, sounds, and various forms of natural language . Some search engines apply improvements to search queries to increase

396-496: Is a network web using technologies and practices that enable users to receive information as soon as it is published by its authors, rather than requiring that they or their software check a source periodically for updates. The real-time web is different from real-time computing in that there is no knowing when, or if, a response will be received. The information types transmitted this way are often short messages, status updates, news alerts, or links to longer documents. The content

440-479: Is available under the “Elastic License”, a source-available license. In addition, Elasticsearch now offers SIEM and Machine Learning as part of its offered services. Search engine (computing) A search engine normally consists of four components, as follows: a search interface, a crawler (also known as a spider or bot), an indexer, and a database. The crawler traverses a document collection, deconstructs document text, and assigns surrogates for storage in

484-406: Is finding relevant information. One approach, known as real-time search , is the concept of searching for and finding information online as it is produced. Advancements in web search technology coupled with growing use of social media enable online activities to be queried as they occur. A traditional web search crawls and indexes web pages periodically, returning results based on relevance to

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528-510: Is no crawling necessary for a database since the data is already structured. However, it is often necessary to index the data in a more economized form to allow a more expeditious search. Sometimes, data searched contains both database content and web pages or documents. Search engine technology has developed to respond to both sets of requirements. Most mixed search engines are large Web search engines, like Google. They search both through structured and unstructured data sources. Take for example,

572-507: Is often "soft" in that it is based on the social web —people's opinions, attitudes, thoughts, and interests—as opposed to hard news or facts. Examples of real-time web are Facebook's newsfeed, and Twitter, implemented in social networking, search, and news sites. Benefits are said to include increased user engagement ("flow") and decreased server loads. In December 2009 real-time search facilities were added to Google Search . The absolutely first realtime web implementation worldwide have been

616-573: The Google Knowledge Graph has had wider ramifications for the Internet, possibly even limiting certain websites traffic, for example Misplaced Pages. By pulling information and presenting it on Google's page, some argue that it can negatively affect other sites. However, there have been no major concerns. Search engines that are expressly designed for searching web pages, documents, and images were developed to facilitate searching through

660-518: The Elastic License, neither of which is recognized as an open-source license . Elastic blamed Amazon Web Services (AWS) for this change, objecting to AWS offering Elasticsearch and Kibana as a service directly to consumers and claiming that AWS was not appropriately collaborating with Elastic. Critics of the re-licensing decision predicted that it would harm Elastic's ecosystem and noted that Elastic had previously promised to "never....change

704-951: The Elasticsearch Service, as well as Elastic App Search Service, and Elastic Site Search Service which were developed from Elastic's acquisition of Swiftype . In late 2017, Elastic formed partnerships with Google to offer Elastic Cloud in Google Cloud Platform (GCP) , and Alibaba to offer Elasticsearch and Kibana in Alibaba Cloud . Elasticsearch Service users can create secure deployments with partners, Google Cloud Platform (GCP) and Alibaba Cloud. In January 2021, Elastic announced that starting with version 7.11, they would be relicensing their Apache 2.0 licensed code in Elasticsearch and Kibana to be dual licensed under Server Side Public License and

748-473: The SMART informational retrieval system. Salton's Magic Automatic Retriever of Text included important concepts like the vector space model , Inverse Document Frequency (IDF), Term Frequency (TF), term discrimination values, and relevancy feedback mechanisms. He authored a 56-page book called A Theory of Indexing which explained many of his tests, upon which search is still largely based. In 1987, an article

792-702: The WIMS true-realtime server and its web apps in 2001-2011 (WIMS = Web Interactive Management System); based on the True-RealTime Web (WEB-r) model of above; built in WIMS++ (server built in Java) (serverside) and Adobe Flash (ex Macromedia Flash) (clientside). The true-realtime web model was born in 2000 at mc2labs.net by an Italian independent researcher. A problem created by the rapid pace and huge volume of information created by real-time web technologies and practices

836-645: The analytics and visualization platform Kibana , and the collection of lightweight data shippers called Beats. The four products are designed for use as an integrated solution, referred to as the "Elastic Stack". (Formerly the "ELK stack", short for "Elasticsearch, Logstash, Kibana".) Elasticsearch uses Lucene and tries to make all its features available through the JSON and Java API . It supports facetting and percolating (a form of prospective search ),  which can be useful for notifying if new documents match for registered queries. Another feature, "gateway", handles

880-468: The anchor text embedded in the links as well, because anchor text can often provide a “very good quality” summary of a web page's content. Searching for text-based content in databases presents a few special challenges from which a number of specialized search engines flourish. Databases can be slow when solving complex queries (with multiple logical or string matching arguments). Databases allow pseudo-logical queries which full-text searches do not use. There

924-453: The case of personal records, transformed to microfilm by the machine itself. Memex would also employ new retrieval techniques based on a new kind of associative indexing the basic idea of which is a provision whereby any item may be caused at will to select immediately and automatically another to create personal "trails" through linked documents. The new procedures, that Bush anticipated facilitating information storage and retrieval would lead to

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968-527: The company Elasticsearch changed its name to Elastic . In June 2018, Elastic filed for an initial public offering with an estimated valuation of between 1.5 and 3 billion dollars. On 5 October 2018, Elastic was listed on the New York Stock Exchange . Developed from the Found acquisition by Elastic in 2015, Elastic Cloud is a family of Elasticsearch-powered SaaS offerings which include

1012-466: The development of wholly new forms of the encyclopedia. The most important mechanism, conceived by Bush, is the associative trail. It would be a way to create a new linear sequence of microfilm frames across any arbitrary sequence of microfilm frames by creating a chained sequence of links in the way just described, along with personal comments and side trails. In 1965, Bush took part in the project INTREX of MIT, for developing technology for mechanization

1056-414: The early 2000s, was similarly displaced by emphasis on relevancy ranking, the methods by which search engines attempt to sort the best results first. Relevancy ranking first became a major issue c.  1996 , when it became apparent that it was impractical to review full lists of results. Consequently, algorithms for relevancy ranking have continuously improved. Google's PageRank method for ordering

1100-542: The first version of Elasticsearch in February 2010. Elastic NV was founded in 2012 to provide commercial services and products around Elasticsearch and related software. In June 2014, the company announced raising $ 70 million in a Series C funding round, just 18 months after forming the company. The round was led by New Enterprise Associates (NEA). Additional funders include Benchmark Capital and Index Ventures . This round brought total funding to $ 104M. In March 2015,

1144-523: The full content of each item, and instead provide a method of navigating to the items in the search engine result page . Alternatively, the search engine may store a copy of each item in a cache so that users can see the state of the item at the time it was indexed or for archive purposes or to make repetitive processes work more efficiently and quickly. Other types of search engines do not store an index. Crawler , or spider type search engines (a.k.a. real-time search engines) may collect and assess items at

1188-461: The inventory. In the case of a wholly textual search, the first step in classifying web pages is to find an ‘index item’ that might relate expressly to the ‘search term.’ In the past, search engines began with a small list of URLs as a so-called seed list, fetched the content, and parsed the links on those pages for relevant information, which subsequently provided new links. The process was highly cyclical and continued until enough pages were found for

1232-479: The license of the Apache 2.0 code of Elasticsearch, Kibana, Beats, and Logstash". Amazon responded with plans to fork the projects and continue development under Apache License 2.0. Other users of the Elasticsearch ecosystem, including Logz.io , CrateDB and Aiven , also committed to the need for a fork, leading to a discussion of how to coordinate the open source efforts. Due to potential trademark issues with using

1276-478: The likelihood of providing a quality set of items through a process known as query expansion . Query understanding methods can be used as standardized query language. The list of items that meet the criteria specified by the query is typically sorted, or ranked. Ranking items by relevance (from highest to lowest) reduces the time required to find the desired information. Probabilistic search engines rank items based on measures of similarity (between each item and

1320-657: The long-term persistence of the index; for example, an index can be recovered from the gateway in the event of a server crash. Elasticsearch supports real-time GET requests , which makes it suitable as a NoSQL datastore, but it lacks distributed transactions . On 20 May 2019, Elastic made the core security features of the Elastic Stack available free of charge, including TLS for encrypted communications, file and native realm for creating and managing users, and role-based access control for controlling user access to cluster APIs and indexes. The corresponding source code

1364-670: The name "Elasticsearch", AWS rebranded their fork as OpenSearch in April 2021. In August 2024 the GNU Affero General Public Licence was added as an option, making it free and open-source once again. Elasticsearch can be used to search any kind of document. It provides scalable search, has near real-time search , and supports multitenancy . "Elasticsearch is distributed, which means that indices can be divided into shards and each shard can have zero or more replicas. Each node hosts one or more shards and acts as

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1408-435: The pages. The excess of data is stored in multiple data structures that permit quick access to said data by certain algorithms that compute the popularity score of pages on the web based on how many links point to a certain web page, which is how people can access any number of resources concerned with diagnosing psychosis. Another example would be the accessibility/rank of web pages containing information on Mohamed Morsi versus

1452-416: The precursor to Elasticsearch, called Compass, in 2004. While thinking about the third version of Compass he realized that it would be necessary to rewrite big parts of Compass to "create a scalable search solution". So he created "a solution built from the ground up to be distributed" and used a common interface, JSON over HTTP , suitable for programming languages other than Java as well. Shay Banon released

1496-434: The processing of information for library use. In his 1967 essay titled "Memex Revisited", he pointed out that the development of the digital computer, the transistor, the video, and other similar devices had heightened the feasibility of such mechanization, but costs would delay its achievements. Gerard Salton, who died on August 28 of 1995, was the father of modern search technology. His teams at Harvard and Cornell developed

1540-403: The query, typically on a scale of 1 to 0, 1 being most similar) and sometimes popularity or authority (see Bibliometrics ) or use relevance feedback . Boolean search engines typically only return items which match exactly without regard to order, although the term Boolean search engine may simply refer to the use of Boolean-style syntax (the use of operators AND , OR , NOT, and XOR ) in

1584-612: The results according to “rules.” The concept of hypertext and a memory extension originates from an article that was published in The Atlantic Monthly in July 1945 written by Vannevar Bush , titled " As We May Think ". Within this article Vannevar urged scientists to work together to help build a body of knowledge for all mankind. He then proposed the idea of a virtually limitless, fast, reliable, extensible, associative memory storage and retrieval system. He named this device

1628-718: The results has received the most press, but all major search engines continually refine their ranking methodologies with a view toward improving the ordering of results. As of 2006, search engine rankings are more important than ever, so much so that an industry has developed (" search engine optimizers ", or "SEO") to help web-developers improve their search ranking, and an entire body of case law has developed around matters that affect search engine rankings, such as use of trademarks in metatags . The sale of search rankings by some search engines has also created controversy among librarians and consumer advocates. Search engine experience for users continues to be enhanced. Google's addition of

1672-400: The search engine index. Online search engines store images, link data and metadata for the document. Search engines provide an interface to a group of items that enables users to specify criteria about an item of interest and have the engine find the matching items. The criteria are referred to as a search query . In the case of text search engines, the search query is typically expressed as

1716-579: The searcher's use. These days, a continuous crawl method is employed as opposed to an incidental discovery based on a seed list. The crawl method is an extension of aforementioned discovery method. Most search engines use sophisticated scheduling algorithms to “decide” when to revisit a particular page, to appeal to its relevance. These algorithms range from constant visit-interval with higher priority for more frequently changing pages to adaptive visit-interval based on several criteria such as frequency of change, popularity, and overall quality of site. The speed of

1760-436: The time of the search query, dynamically considering additional items based on the contents of a starting item (known as a seed, or seed URL in the case of an Internet crawler). Meta search engines store neither an index nor a cache and instead simply reuse the index or results of one or more other search engine to provide an aggregated, final set of results. Database size, which had been a significant marketing feature through

1804-465: The very best attractions to visit in Cairo after simply entering ‘Egypt’ as a search term. One such algorithm, PageRank , proposed by Google founders Larry Page and Sergey Brin, is well known and has attracted a lot of attention because it highlights repeat mundanity of web searches courtesy of students that don't know how to properly research subjects on Google. The idea of doing link analysis to compute

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1848-402: The web server running the page as well as resource constraints like amount of hardware or bandwidth also figure in. Pages that are discovered by web crawls are often distributed and fed into another computer that creates a map of resources uncovered. The bunchy clustermass looks a little like a graph, on which the different pages are represented as small nodes that are connected by links between

1892-407: The word ‘ball.’ In its simplest terms, it returns more than 40 variations on Misplaced Pages alone. Did you mean a ball, as in the social gathering/dance? A soccer ball? The ball of the foot? Pages and documents are crawled and indexed in a separate index. Databases are indexed also from various sources. Search results are then generated for users by querying these multiple indices in parallel and compounding

1936-534: Was published detailing the development of a character string search engine (SSE) for rapid text retrieval on a double-metal 1.6-μm n-well CMOS solid-state circuit with 217,600 transistors lain out on a 8.62x12.76-mm die area. The SSE accommodated a novel string-search architecture which combines a 512-stage finite-state automaton (FSA) logic with a content addressable memory (CAM) to achieve an approximate string comparison of 80 million strings per second. The CAM cell consisted of four conventional static RAM (SRAM) cells and

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