 | This article has multiple issues. Please help improve it or discuss these issues on the talk page . (Learn how and when to remove these template messages)
|
 | |
| Formerly | Vertical Search Works |
|---|---|
| Industry | Technology |
| Founded | 2010 |
| Founders |
|
| Headquarters | , |
Key people |
|
| Website | ntent |
NTENT is a semantic search and natural language understanding technology company based in New York City. It was founded in 2010 as a result of a merger between Convera Corporation and Firstlight ERA.
NTENT was founded in February 2010 as the result of a merger between Convera Corporation and Firstlight ERA, with roots in semantic search and natural language processing technologies dating back to the early 1980s. [3]
NTENT applied the contextual ad platform technology from Firstlight ERA to enter the advertising sector. [4] Utilizing semantic analysis and advanced targeting capabilities, NTENT partnered with digital publishers, brands, and marketers Meredith Corporation, NBC, Scripps, and Viacom to launch a native, contextual ad platform that automatically matched advertisements to the concept of an article without the need of a complex keyword management, thereby providing end-users with a native advertising experience. [5] [6] [7] [8]
In June 2016, NTENT announced the expansion of its semantic search and natural language processing technologies, including support for the Russian language. This marked a key milestone for NTENT, whose core technology stack has evolved to include branches of Artificial Intelligence (AI) such as machine learning, knowledge representation and natural language understanding, to create a proprietary ontology with the ability to interpret taxonomic relationships and organize concepts regardless of language. [9] [10] [11]
In the autumn of 2016, NTENT further widened its international presence by opening an office in Barcelona. [12] The office operated as a Spanish private limited company. [13] Allegedly due to the COVID-19 recession, all the Spanish office's employees were furloughed in the spring of 2020, and the office eventually went into liquidation. [13] [14]
In Match 2021, NTENT's CEO Pat Condo founded a new company called Seekr Technologies. [15] Since December 2021, NTENT website automatically redirects to Seekr News homepage. [16]
Co-founder Pat Condo is the company's CEO and Chairman. [1] In July 2016, Ricardo Baeza-Yates was named as the company's CTO, having come from Yahoo! where he served as the Chief Research Scientist. [2] He held the CTO position at NTENT until 2020. [17]
NTENT's platform uses enhanced semantic ranking and knowledge base technologies. By applying advanced semantic ranking algorithms across a vast lexicon and custom ontology using machine learning and natural language understanding, NTENT's semantic and knowledge base technologies disambiguate complex queries to detect user intention and deliver relevant results for users. [18]
Cyc is a long-term artificial intelligence project that aims to assemble a comprehensive ontology and knowledge base that spans the basic concepts and rules about how the world works.
The Semantic Web, sometimes known as Web 3.0, is an extension of the World Wide Web through standards set by the World Wide Web Consortium (W3C). The goal of the Semantic Web is to make Internet data machine-readable.
In information science, an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the concepts, data, or entities that pertain to one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of terms and relational expressions that represent the entities in that subject area. The field which studies ontologies so conceived is sometimes referred to as applied ontology.
Yahoo! Japan is a Japanese web portal. It was the most-visited website in Japan, nearing monopolistic status.
Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between items is based on the likeness of their meaning or semantic content as opposed to lexicographical similarity. These are mathematical tools used to estimate the strength of the semantic relationship between units of language, concepts or instances, through a numerical description obtained according to the comparison of information supporting their meaning or describing their nature. The term semantic similarity is often confused with semantic relatedness. Semantic relatedness includes any relation between two terms, while semantic similarity only includes "is a" relations. For example, "car" is similar to "bus", but is also related to "road" and "driving".
Ricardo A. Baeza-Yates is a Chilean-Catalan-American computer scientist that currently is the Director of Research of the Institute for Experiential AI at Northeastern University in the Silicon Valley campus. He is also part-time professor at Universitat Pompeu Fabra in Barcelona and Universidad de Chile in Santiago. He is an expert member of the Global Partnership on Artificial Intelligence, a member of the Association for Computing Machinery's US Technology Policy Committee as well as IEEE's Ethics Committee.
Sphere was a blog search engine. The Sphere search engine delivered blog posts based on algorithms that combine semantic matching with authority factors to deliver results relevant to the search query.
Semantic search denotes search with meaning, as distinguished from lexical search where the search engine looks for literal matches of the query words or variants of them, without understanding the overall meaning of the query. Semantic search seeks to improve search accuracy by understanding the searcher's intent and the contextual meaning of terms as they appear in the searchable dataspace, whether on the Web or within a closed system, to generate more relevant results.
NEPOMUK is an open-source software specification that is concerned with the development of a social semantic desktop that enriches and interconnects data from different desktop applications using semantic metadata stored as RDF. Between 2006 and 2008 it was funded by a European Union research project of the same name that grouped together industrial and academic actors to develop various Semantic Desktop technologies.
Powerset was an American company based in San Francisco, California, that, in 2006, was developing a natural language search engine for the Internet. On July 1, 2008, Powerset was acquired by Microsoft for an estimated $100 million.
Convera was formed in December 2000 by the merger of Intel's Interactive Services division and Excalibur Technologies Corporation. Until 2007, Convera's primary focus was the enterprise search market through its flagship product, RetrievalWare, which is widely used within the secure government sector in the United States, UK, Canada and a number of other countries. Convera sold its enterprise search business to FAST Search & Transfer in August 2007 for $23 million, at which point RetrievalWare was officially retired. Microsoft Corporation continues to maintain RetrievalWare for its existing customer base.
hakia was an Internet search engine. Launched in March 2004 and based in New York City, hakia attempted to pioneer a semantic search engine in contrast to keyword search engines that were established at that time. The search engine ceased operations in 2014. Since 2015 the domain has been owned by HughesNet.
Natural-language user interface is a type of computer human interface where linguistic phenomena such as verbs, phrases and clauses act as UI controls for creating, selecting and modifying data in software applications.
RetrievalWare is an enterprise search engine emphasizing natural language processing and semantic networks which was commercially available from 1992 to 2007 and is especially known for its use by government intelligence agencies.
The Allen Institute for AI is a 501(c)3 non-profit research institute founded by late Microsoft co-founder and philanthropist Paul Allen in 2014. The institute seeks to conduct high-impact AI research and engineering in service of the common good. Oren Etzioni was appointed by Paul Allen in September 2013 to direct the research at the institute. After leading the organization for nine years, Oren Etzioni stepped down from his role as CEO on September 30, 2022. He was replaced in an interim capacity by the leading researcher of the company's Aristo project, Peter Clark. On June 20, 2023, AI2 announced Ali Farhadi as its next CEO starting July 31, 2023. The company's board formed a search committee for a new CEO. AI2 also has an active office in Tel Aviv, Israel.
The following outline is provided as an overview of and topical guide to natural-language processing:
Semantic Scholar is a research tool for scientific literature powered by artificial intelligence. It is developed at the Allen Institute for AI and was publicly released in November 2015. Semantic Scholar uses modern techniques in natural language processing to support the research process, for example by providing automatically generated summaries of scholarly papers. The Semantic Scholar team is actively researching the use of artificial intelligence in natural language processing, machine learning, human–computer interaction, and information retrieval.
In natural language processing, linguistics, and neighboring fields, Linguistic Linked Open Data (LLOD) describes a method and an interdisciplinary community concerned with creating, sharing, and (re-)using language resources in accordance with Linked Data principles. The Linguistic Linked Open Data Cloud was conceived and is being maintained by the Open Linguistics Working Group (OWLG) of the Open Knowledge Foundation, but has been a point of focal activity for several W3C community groups, research projects, and infrastructure efforts since then.
AnswerDash is a B2B software company that facilitates customer service for e-commerce businesses. AnswerDash was founded in Seattle, Washington in 2012 as a spin-off from the Information school of the University of Washington. Its software-as-a-service utilizes machine learning to create databases of context-sensitive support answers for end-users of webpages and mobile applications, thus reducing the need for human customer service. AnswerDash claims to be the first, and as of 2015, the world's leading provider of contextual point-and-click answer technology. In June 2020, AnswerDash was acquired by CloudEngage.
In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics or relationships underlying these entities.
