Collaborative filtering (CF) is a technique used by recommender systems. Collaborative filtering has two senses, a narrow one and a more general one.
A recommender system, or a recommendation system, is a subclass of information filtering system that provides suggestions for items that are most pertinent to a particular user. Recommender systems are particularly useful when an individual needs to choose an item from a potentially overwhelming number of items that a service may offer.
Personalization consists of tailoring a service or product to accommodate specific individuals. It is sometimes tied to groups or segments of individuals. Personalization involves collecting data on individuals, including web browsing history, web cookies, and location. Various organizations use personalization to improve customer satisfaction, digital sales conversion, marketing results, branding, and improved website metrics as well as for advertising. Personalization acts as a key element in social media and recommender systems. Personalization influences every sector of society — be it work, leisure, or citizenship.
A voice-user interface (VUI) enables spoken human interaction with computers, using speech recognition to understand spoken commands and answer questions, and typically text to speech to play a reply. A voice command device is a device controlled with a voice user interface.
In critical theory, power-knowledge is a term introduced by the French philosopher Michel Foucault. According to Foucault's understanding, power is based on knowledge and makes use of knowledge; on the other hand, power reproduces knowledge by shaping it in accordance with its anonymous intentions. Power creates and recreates its own fields of exercise through knowledge.
In science, randomized experiments are the experiments that allow the greatest reliability and validity of statistical estimates of treatment effects. Randomization-based inference is especially important in experimental design and in survey sampling.
Social search is a behavior of retrieving and searching on a social searching engine that mainly searches user-generated content such as news, videos and images related search queries on social media like Facebook, LinkedIn, Twitter, Instagram and Flickr. It is an enhanced version of web search that combines traditional algorithms. The idea behind social search is that instead of ranking search results purely based on semantic relevance between a query and the results, a social search system also takes into account social relationships between the results and the searcher. The social relationships could be in various forms. For example, in LinkedIn people search engine, the social relationships include social connections between searcher and each result, whether or not they are in the same industries, work for the same companies, belong the same social groups, and go the same schools, etc.
Cold start is a potential problem in computer-based information systems which involves a degree of automated data modelling. Specifically, it concerns the issue that the system cannot draw any inferences for users or items about which it has not yet gathered sufficient information.
Social information processing is "an activity through which collective human actions organize knowledge." It is the creation and processing of information by a group of people. As an academic field Social Information Processing studies the information processing power of networked social systems.
Wikipedia has been studied extensively. Between 2001 and 2010, researchers published at least 1,746 peer-reviewed articles about the online encyclopedia. Such studies are greatly facilitated by the fact that Wikipedia's database can be downloaded without help from the site owner.
Folksonomy is a classification system in which end users apply public tags to online items, typically to make those items easier for themselves or others to find later. Over time, this can give rise to a classification system based on those tags and how often they are applied or searched for, in contrast to a taxonomic classification designed by the owners of the content and specified when it is published. This practice is also known as collaborative tagging, social classification, social indexing, and social tagging. Folksonomy was originally "the result of personal free tagging of information [...] for one's own retrieval", but online sharing and interaction expanded it into collaborative forms. Social tagging is the application of tags in an open online environment where the tags of other users are available to others. Collaborative tagging is tagging performed by a group of users. This type of folksonomy is commonly used in cooperative and collaborative projects such as research, content repositories, and social bookmarking.
Personalized search is a web search tailored specifically to an individual's interests by incorporating information about the individual beyond the specific query provided. There are two general approaches to personalizing search results, involving modifying the user's query and re-ranking search results.
A filter bubble or ideological frame is a state of intellectual isolation that can result from personalized searches, recommendation systems, and algorithmic curation. The search results are based on information about the user, such as their location, past click-behavior, and search history. Consequently, users become separated from information that disagrees with their viewpoints, effectively isolating them in their own cultural or ideological bubbles, resulting in a limited and customized view of the world. The choices made by these algorithms are only sometimes transparent. Prime examples include Google Personalized Search results and Facebook's personalized news-stream.
Social advertising is advertising that relies on social information or networks in generating, targeting, and delivering marketing communications. Many current examples of social advertising use a particular Internet service to collect social information, establish and maintain relationships with consumers, and for delivering communications. For example, the advertising platforms provided by Google, Twitter, and Facebook involve targeting and presenting ads based on relationships articulated on those same services. Social advertising can be part of a broader social media marketing strategy designed to connect with consumers.
Social media mining is the process of obtaining data from user-generated content on social media in order to extract actionable patterns, form conclusions about users, and act upon the information. Mining supports targeting advertising to users or academic research. The term is an analogy to the process of mining for minerals. Mining companies sift through raw ore to find the valuable minerals; likewise, social media mining sifts through social media data in order to discern patterns and trends about matters such as social media usage, online behaviour, content sharing, connections between individuals, buying behaviour. These patterns and trends are of interest to companies, governments and not-for-profit organizations, as such organizations can use the analyses for tasks such as design strategies, introduce programs, products, processes or services.
Algorithmic bias describes systematic and repeatable errors in a computer system that create "unfair" outcomes, such as "privileging" one category over another in ways different from the intended function of the algorithm.
Matrix factorization is a class of collaborative filtering algorithms used in recommender systems. Matrix factorization algorithms work by decomposing the user-item interaction matrix into the product of two lower dimensionality rectangular matrices. This family of methods became widely known during the Netflix prize challenge due to its effectiveness as reported by Simon Funk in his 2006 blog post, where he shared his findings with the research community. The prediction results can be improved by assigning different regularization weights to the latent factors based on items' popularity and users' activeness.
Responsive computer-aided design is an approach to computer-aided design (CAD) that utilizes real-world sensors and data to modify a three-dimensional (3D) computer model. The concept is related to cyber-physical systems through blurring of the virtual and physical worlds, however, applies specifically to the initial digital design of an object prior to production.
Click tracking is when user click behavior or user navigational behavior is collected in order to derive insights and fingerprint users. Click behavior is commonly tracked using server logs which encompass click paths and clicked URLs. This log is often presented in a standard format including information like the hostname, date, and username. However, as technology develops, new software allows for in depth analysis of user click behavior using hypervideo tools. Given that the internet can be considered a risky environment, research strives to understand why users click certain links and not others. Research has also been conducted to explore the user experience of privacy with making user personal identification information individually anonymized and improving how data collection consent forms are written and structured.
In the design of experiments, a sample ratio mismatch (SRM) is a statistically significant difference between the expected and actual ratios of the sizes of treatment and control groups in an experiment. Sample ratio mismatches also known as unbalanced sampling often occur in online controlled experiments due to failures in randomization and instrumentation.
