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Type | Private |
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Industry | Search Engine |
Founded | Samara, Russian Federation (2006) |
Headquarters | London , UK, Russian Federation |
Products | Web search engine, Image search |
Website | www.recogmission.com [ dead link ] |
Picollator is an Internet search engine that performs searches for web sites and multimedia by visual query (image) or text, or a combination of visual query and text. Picollator recognizes objects in the image, obtains their relevance to the text and vice versa, and searches in accordance with all information provided.
Picollator identifies human faces in the images and creates a database of people's faces. This allows the user to search for other images of the submitted person, lookalikes and/or similar images in images found on websites. Picollator can be used in any language.
2006– Recogmission LLC developed a desktop application for photo collections management. The system automatically classifies, manages and retrieves photographs stored locally or in corporate databases.
2007– Recogmission started Picollator multimedia search engine project, now in Beta stage.
2008– Picollator.mobi is launched—a new universal search engine for mobile phones.
2009– Recogmission opens the web based content filter service piFilter.com, which inherited some pattern recognition technologies from Picollator.
Most image search engines match user textual query and picture tags. Picollator is based on a different approach. Patterns and objects found in the image are stored in its database, therefore it is able to recognise the contents of the image and compare it to other images to find similarities.
To search for multimedia information, the user may submit
ru:Recogmission LLC has developed an indexing engine for multimedia information search based on the visual query.
Recogmission develops solutions for multimedia information (image, text and video) indexing and searching on the web and in corporate environments.
Google Search is a search engine provided and operated by Google. Handling more than 3.5 billion searches per day, it has a 92% share of the global search engine market. It is the most-visited website in the world. Additionally, it is the most searched and used search engine in the entire world.
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.
An image retrieval system is a computer system used for browsing, searching and retrieving images from a large database of digital images. Most traditional and common methods of image retrieval utilize some method of adding metadata such as captioning, keywords, title or descriptions to the images so that retrieval can be performed over the annotation words. Manual image annotation is time-consuming, laborious and expensive; to address this, there has been a large amount of research done on automatic image annotation. Additionally, the increase in social web applications and the semantic web have inspired the development of several web-based image annotation tools.
The deep web, invisible web, or hidden web are parts of the World Wide Web whose contents are not indexed by standard web search-engine programs. This is in contrast to the "surface web", which is accessible to anyone using the Internet. Computer scientist Michael K. Bergman is credited with inventing the term in 2001 as a search-indexing term.
Dogpile is a metasearch engine for information on the World Wide Web that fetches results from Google, Yahoo!, Yandex, Bing, and other popular search engines, including those from audio and video content providers such as Yahoo!.
Content-based image retrieval, also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases. Content-based image retrieval is opposed to traditional concept-based approaches.
Yahoo! Search is a Yahoo! web search provider that uses Microsoft's Bing search engine to power results.
A tag cloud is a visual representation of text data which is often used to depict keyword metadata on websites, or to visualize free form text. Tags are usually single words, and the importance of each tag is shown with font size or color. When used as website navigation aids, the terms are hyperlinked to items associated with the tag.
A video search engine is a web-based search engine which crawls the web for video content. Some video search engines parse externally hosted content while others allow content to be uploaded and hosted on their own servers. Some engines also allow users to search by video format type and by length of the clip. The video search results are usually accompanied by a thumbnail view of the video.
Google Images is a search engine owned by Google that allows users to search the World Wide Web for images. It was introduced on July 12, 2001, due to a demand for pictures of the green Versace dress of Jennifer Lopez worn in February 2000. In 2011, reverse image search functionality was added.
Multimedia search enables information search using queries in multiple data types including text and other multimedia formats. Multimedia search can be implemented through multimodal search interfaces, i.e., interfaces that allow to submit search queries not only as textual requests, but also through other media. We can distinguish two methodologies in multimedia search:
An audio search engine is a web-based search engine which crawls the web for audio content. The information can consist of web pages, images, audio files, or another type of document. Various techniques exist for research on these engines.
A concept search is an automated information retrieval method that is used to search electronically stored unstructured text for information that is conceptually similar to the information provided in a search query. In other words, the ideas expressed in the information retrieved in response to a concept search query are relevant to the ideas contained in the text of the query.
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.
MicrosoftEncarta is a discontinued digital multimedia encyclopedia published by Microsoft from 1993 to 2009. Originally sold on CD-ROM or DVD, it was also available online via annual subscription, although later articles could also be viewed for free online with advertisements. By 2008, the complete English version, Encarta Premium, consisted of more than 62,000 articles, numerous photos and illustrations, music clips, videos, interactive content, timelines, maps, atlases and homework tools.
Reverse image search is a content-based image retrieval (CBIR) query technique that involves providing the CBIR system with a sample image that it will then base its search upon; in terms of information retrieval, the sample image is very useful. In particular, reverse image search is characterized by a lack of search terms. This effectively removes the need for a user to guess at keywords or terms that may or may not return a correct result. Reverse image search also allows users to discover content that is related to a specific sample image or the popularity of an image, and to discover manipulated versions and derivative works.
Learning to rank or machine-learned ranking (MLR) is the application of machine learning, typically supervised, semi-supervised or reinforcement learning, in the construction of ranking models for information retrieval systems. Training data consists of lists of items with some partial order specified between items in each list. This order is typically induced by giving a numerical or ordinal score or a binary judgment for each item. The goal of constructing the ranking model is to rank new, unseen lists in a similar way to rankings in the training data.
Yandex Search is a search engine. It is owned by Yandex, based in Russia. In January 2015, Yandex Search generated 51.2% of all of the search traffic in Russia according to LiveInternet.
Multimodal search is a type of search that uses different methods to get relevant results. They can use any kind of search, search by keyword, search by concept, search by example, etc.
Searx is a free and open-source metasearch engine, available under the GNU Affero General Public License version 3, with the aim of protecting the privacy of its users. To this end, Searx does not share users' IP addresses or search history with the search engines from which it gathers results. Tracking cookies served by the search engines are blocked, preventing user-profiling-based results modification. By default, Searx queries are submitted via HTTP POST, to prevent users' query keywords from appearing in webserver logs. Searx was inspired by the Seeks project, though it does not implement Seeks' peer-to-peer user-sourced results ranking.