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Information retrieval (IR) is the activity 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.
Streaming media is multimedia that is constantly received by and presented to an end-user while being delivered by a provider. The verb to stream refers to the process of delivering or obtaining media in this manner. Streaming refers to the delivery method of the medium, rather than the medium itself. Distinguishing delivery method from the media distributed applies specifically to telecommunications networks, as most of the delivery systems are either inherently streaming or inherently non-streaming. There are challenges with streaming content on the Internet. For example, users whose Internet connection lacks sufficient bandwidth may experience stops, lags, or slow buffering of the content. And users lacking compatible hardware or software systems may be unable to stream certain content.
MPEG-7 is a multimedia content description standard. It was standardized in ISO/IEC 15938. This description will be associated with the content itself, to allow fast and efficient searching for material that is of interest to the user. MPEG-7 is formally called Multimedia Content Description Interface. Thus, it is not a standard which deals with the actual encoding of moving pictures and audio, like MPEG-1, MPEG-2 and MPEG-4. It uses XML to store metadata, and can be attached to timecode in order to tag particular events, or synchronise lyrics to a song, for example.
Personalized marketing, also known as one-to-one marketing or individual marketing, is a marketing strategy by which companies leverage data analysis and digital technology to deliver individualized messages and product offerings to current or prospective customers. Advancements in data collection methods, analytics, digital electronics, and digital economics, have enabled marketers to deploy more effective real-time and prolonged customer experience personalization tactics.
Music information retrieval (MIR) is the interdisciplinary science of retrieving information from music. MIR is a small but growing field of research with many real-world applications. Those involved in MIR may have a background in musicology, psychoacoustics, psychology, academic music study, signal processing, informatics, machine learning, optical music recognition, computational intelligence or some combination of these.
An image retrieval system is a computer system 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.
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.
Web mining is the application of data mining techniques to discover patterns from the World Wide Web. As the name proposes, this is information gathered by mining the web. It makes utilization of automated apparatuses to reveal and extricate data from servers and web2 reports, and it permits organizations to get to both organized and unstructured information from browser activities, server logs, website and link structure, page content and different sources.
The Text REtrieval Conference (TREC) is an ongoing series of workshops focusing on a list of different information retrieval (IR) research areas, or tracks. It is co-sponsored by the National Institute of Standards and Technology (NIST) and the Intelligence Advanced Research Projects Activity, and began in 1992 as part of the TIPSTER Text program. Its purpose is to support and encourage research within the information retrieval community by providing the infrastructure necessary for large-scale evaluation of text retrieval methodologies and to increase the speed of lab-to-product transfer of technology.
In computing, a news aggregator, also termed a feed aggregator, feed reader, news reader, RSS reader or simply an aggregator, is client software or a web application that aggregates syndicated web content such as online newspapers, blogs, podcasts, and video blogs (vlogs) in one location for easy viewing. The updates distributed may include journal tables of contents, podcasts, videos, and news items.
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:
CALO was an artificial intelligence project that attempted to integrate numerous AI technologies into a cognitive assistant. CALO is an acronym for "Cognitive Assistant that Learns and Organizes". The name was inspired by the Latin word "Calo" which means "soldier’s servant". The project started in May 2003 and ran for five years, ending in 2008.
Amit Sheth is a computer scientist at Wright State University in Dayton, Ohio. He is the Lexis Nexis Ohio Eminent Scholar for Advanced Data Management and Analysis. Up to October 2018, Sheth's work had been cited by over 41,000 publications. He has an h-index of 100, which puts him among the top 100 computer scientists with the highest h-index. Prior to founding the Kno.e.sis Center, he served as the director of the Large Scale Distributed Information Systems Lab at the University of Georgia in Athens, Georgia.
Expertise finding is the use of tools for finding and assessing individual expertise. In the recruitment industry, expertise finding is the problem of searching for employable candidates with certain required skills set. In other words, it is the challenge of linking humans to expertise areas, and as such is a sub-problem of expertise retrieval.
An intelligent medical search engine is a vertical search engine that uses expert system technology to provide personalized medical information.
Collaborative search engines (CSE) are Web search engines and enterprise searches within company intranets that let users combine their efforts in information retrieval (IR) activities, share information resources collaboratively using knowledge tags, and allow experts to guide less experienced people through their searches. Collaboration partners do so by providing query terms, collective tagging, adding comments or opinions, rating search results, and links clicked of former (successful) IR activities to users having the same or a related information need.
A smart TV, also known as a connected TV (CTV), is a traditional television set with integrated Internet and interactive Web 2.0 features, which allows users to stream music and videos, browse the internet, and view photos. Smart TV is a technological convergence of computers, television sets, and set-top boxes. Besides the traditional functions of television sets and set-top boxes provided through traditional broadcasting media, these devices can provide Internet TV, online interactive media, over-the-top content (OTT) as well as on-demand streaming media, and home networking access.
The following outline is provided as an overview of and topical guide to search engines.
Contextual search is a form of optimizing web-based search results based on context provided by the user and the computer being used to enter the query. Contextual search services differ from current search engines based on traditional information retrieval that return lists of documents based on their relevance to the query. Rather, contextual search attempts to increase the precision of results based on how valuable they are to individual users.
Video browsing, also known as exploratory video search, is the interactive process of skimming through video content in order to satisfy some information need or to interactively check if the video content is relevant. While originally proposed to help users inspecting a single video through visual thumbnails, modern video browsing tools enable users to quickly find desired information in a video archive by iterative human–computer interaction through an exploratory search approach. Many of these tools presume a smart user that wants features to interactively inspect video content as well as automatic content filtering features. For that purpose, several video interaction features are usually provided, such as sophisticated navigation in video or search by a content-based query. Video browsing tools often build on lower-level video content analysis, such as shot transition detection, keyframe extraction, semantic concept detection, and create a structured content overview of the video file or video archive. Furthermore, they usually provide sophisticated navigation features, such as advanced timelines, visual seeker bars or a list of selected thumbnails, as well as means for content querying. Examples of content queries are shot filtering through visual concepts, through some specific characteristics, through user-provided sketches, or through content-based similarity search.
References
- ↑ Kim, H. G.; Kim, J. Y.; Baek, J. G. (2011). "An integrated music video browsing system for personalized television". Expert Systems with Applications. 38: 776. doi:10.1016/j.eswa.2010.07.032. "Personalized digital television (PDTV) aims to satisfy TV viewers who have different and various interests and face overwhelming amounts of digital videos."
- ↑ Intelligent Multimedia Interfaces(AAAI/MIT Press 1993)
- ↑ Intelligent Multimedia Information Retrieval Archived 2010-03-12 at the Wayback Machine (AAAI/ MIT Press 1997)
- ↑ Maybury, M. T., Personalcasting: Tailored Broadcast News. 2001, Workshop on Personalized Television. International Conference on User Modeling. Sondhofen, Germany
- ↑ Personalized broadcast news navigator. US Patent # 7,386,542, Maybury, M. et al. June 10, 2008