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Preference Elicitation
Preference elicitation refers to the problem of developing a decision support system capable of generating recommendations to a user, thus assisting in decision making. It is important for such a system to model user's preferences accurately, find hidden preferences and avoid redundancy. This problem is sometimes studied as a computational learning theory problem. Another approach for formulating this problem is a partially observable Markov decision process. The formulation of this problem is also dependent upon the context of the area in which it is studied. Overview With the explosion of on-line information new opportunities for finding and using electronic data have been generated, these changes have also brought the task of eliciting useful information to the forefront. Researchers as well as major online catalog companies have come up with algorithms and prototypes of systems that can aid a user to be able to navigate through a complex and huge information space using some inf ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision Support System
A decision support system (DSS) is an information system that supports business or organizational decision-making activities. DSSs serve the management, operations and planning levels of an organization (usually mid and higher management) and help people make decisions about problems that may be rapidly changing and not easily specified in advance—i.e. unstructured and semi-structured decision problems. Decision support systems can be either fully computerized or human-powered, or a combination of both. While academics have perceived DSS as a tool to support decision making processes, DSS users see DSS as a tool to facilitate organizational processes. Some authors have extended the definition of DSS to include any system that might support decision making and some DSS include a decision-making software component; Sprague (1980)Sprague, R;(1980).A Framework for the Development of Decision Support Systems" MIS Quarterly. Vol. 4, No. 4, pp.1-25. defines a properly termed DSS as f ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recommender System
A recommender system, or a recommendation system (sometimes replacing 'system' with a synonym such as platform or engine), is a subclass of information filtering system that provide suggestions for items that are most pertinent to a particular user. Typically, the suggestions refer to various decision-making processes, such as what product to purchase, what music to listen to, or what online news to read. 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. Recommender systems are used in a variety of areas, with commonly recognised examples taking the form of playlist generators for video and music services, product recommenders for online stores, or content recommenders for social media platforms and open web content recommenders.Pankaj Gupta, Ashish Goel, Jimmy Lin, Aneesh Sharma, Dong Wang, and Reza Bosagh ZadeWTF:The who-to-follow system at Twitter Proceedings of the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Partially Observable Markov Decision Process
A partially observable Markov decision process (POMDP) is a generalization of a Markov decision process (MDP). A POMDP models an agent decision process in which it is assumed that the system dynamics are determined by an MDP, but the agent cannot directly observe the underlying state. Instead, it must maintain a sensor model (the probability distribution of different observations given the underlying state) and the underlying MDP. Unlike the policy function in MDP which maps the underlying states to the actions, POMDP's policy is a mapping from the history of observations (or belief states) to the actions. The POMDP framework is general enough to model a variety of real-world sequential decision processes. Applications include robot navigation problems, machine maintenance, and planning under uncertainty in general. The general framework of Markov decision processes with imperfect information was described by Karl Johan Åström in 1965 in the case of a discrete state space, and it ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Prototype
A prototype is an early sample, model, or release of a product built to test a concept or process. It is a term used in a variety of contexts, including semantics, design, electronics, and Software prototyping, software programming. A prototype is generally used to evaluate a new design to enhance precision by system analysts and users. Prototyping serves to provide specifications for a real, working system rather than a theoretical one. In some design workflow models, creating a prototype (a process sometimes called materialization) is the step between the Formal specification, formalization and the evaluation of an idea. A prototype can also mean a typical example of something such as in the use of the derivation 'prototypical'. This is a useful term in identifying objects, behaviours and concepts which are considered the accepted norm and is analogous with terms such as stereotypes and archetypes. The word ''wikt:prototype, prototype'' derives from the Greek language, Greek ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cold Start (computing)
Cold start in computing refers to a problem where a system or its part was created or restarted and is not working at its normal operation. The problem can be related to initialising internal objects or populating cache or starting up subsystems. In a typical web service system the problem occurs after restarting the server, and also when clearing the cache (e.g., after releasing new version). The first requests to the web service will cause significantly more load due to the server cache being populated, the browser cache being cleared, and new resources being requested. Other services like a caching proxy or web accelerator will also need time to gather new resources and operate normally. Similar problem occurs when creating instances in a hosted environment and instances in cloud computing services. Cold start (or cold boot) may also refer to a booting process of a single computer (or virtual machine). In this case services and other startup applications are executed after reb ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Collaborative Filtering
Collaborative filtering (CF) is a technique used by recommender systems.Francesco Ricci and Lior Rokach and Bracha ShapiraIntroduction to Recommender Systems Handbook Recommender Systems Handbook, Springer, 2011, pp. 1-35 Collaborative filtering has two senses, a narrow one and a more general one. In the newer, narrower sense, collaborative filtering is a method of making automatic predictions (filtering) about the interests of a user by collecting preferences or taste information from many users (collaborating). The underlying assumption of the collaborative filtering approach is that if a person ''A'' has the same opinion as a person ''B'' on an issue, A is more likely to have B's opinion on a different issue than that of a randomly chosen person. For example, a collaborative filtering recommendation system for preferences in television programming could make predictions about which television show a user should like given a partial list of that user's tastes (likes or dislikes ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Collective Intelligence
Collective intelligence (CI) is shared or group intelligence (GI) that emerges from the collaboration, collective efforts, and competition of many individuals and appears in consensus decision making. The term appears in sociobiology, political science and in context of mass peer review and crowdsourcing applications. It may involve consensus, social capital and formalisms such as voting systems, social media and other means of quantifying mass activity. Collective IQ is a measure of collective intelligence, although it is often used interchangeably with the term collective intelligence. Collective intelligence has also been attributed to bacteria and animals. It can be understood as an emergent property from the synergies among: #data-information-knowledge #software-hardware #individuals (those with new insights as well as recognized authorities) that continually learns from feedback to produce just-in-time knowledge for better decisions than these three elements acting alo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Long Tail
In statistics and business, a long tail of some probability distribution, distributions of numbers is the portion of the distribution having many occurrences far from the "head" or central part of the distribution. The distribution could involve popularities, random numbers of occurrences of events with various probabilities, etc. The term is often used loosely, with no definition or an arbitrary definition, but precise definitions are possible. In statistics, the term ''long-tailed distribution'' has a narrow technical meaning, and is a subtype of heavy-tailed distribution. Intuitively, a distribution is (right) long-tailed if, for any fixed amount, when a quantity exceeds a high level, it almost certainly exceeds it by at least that amount: large quantities are probably even larger. Note that there is no sense of ''the'' "long tail" of a distribution, but only the ''property'' of a distribution being long-tailed. In business, the term ''long tail'' is applied to rank-size dis ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Personalized Marketing
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. Beginning in the early 1990s, web developers began tracking HTML calls that their websites were receiving from online visitors. In 2012, the Web Analytics Association (WAA) officially changed its name to the Digital Analytics Association (DAA) in order to accommodate new and developing data streams that exist in addition to the web. Technology Personalized marketing is dependent on many different types of technology for data collection, data classification, data analysis, data transfer, and data scalabil ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Product Finder
Product finders are information systems that help consumers to identify products within a large palette of similar alternative products. Product finders differ in complexity, the more complex among them being a special case of decision support systems. Conventional decision support systems, however, aim at specialized user groups, e.g. marketing managers, whereas product finders focus on consumers. Area of application Usually, product finders are part of an e-shop or an online presentation of a product-line. Being part of an e-shop, a product finder ideally leads to an online buy, while conventional distribution channels are involved in product finders that are part of an online presentation (e.g. shops, order by phone). Product finders are best suited for product groups whose individual products are comparable by specific criteria. This is true, in most cases, with technical products such as notebooks: their features (e.g. clock rate, size of harddisk, price, screen size) may ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Revealed Preference
Revealed preference theory, pioneered by economist Paul Anthony Samuelson in 1938, is a method of analyzing choices made by individuals, mostly used for comparing the influence of policies on consumer behavior. Revealed preference models assume that the preferences of consumers can be revealed by their purchasing habits. Revealed preference theory arose because existing theories of consumer demand were based on a diminishing marginal rate of substitution (MRS). This diminishing MRS relied on the assumption that consumers make consumption decisions to maximise their utility As a topic of economics, utility is used to model worth or value. Its usage has evolved significantly over time. The term was introduced initially as a measure of pleasure or happiness as part of the theory of utilitarianism by moral philosopher .... While utility maximisation was not a controversial assumption, the underlying utility functions could not be measured with great certainty. Revealed preference ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision Support Systems
A decision support system (DSS) is an information system that supports business or organizational decision-making activities. DSSs serve the management, operations and planning levels of an organization (usually mid and higher management) and help people make decisions about problems that may be rapidly changing and not easily specified in advance—i.e. unstructured and semi-structured decision problems. Decision support systems can be either fully computerized or human-powered, or a combination of both. While academics have perceived DSS as a tool to support decision making processes, DSS users see DSS as a tool to facilitate organizational processes. Some authors have extended the definition of DSS to include any system that might support decision making and some DSS include a decision-making software component; Sprague (1980)Sprague, R;(1980).A Framework for the Development of Decision Support Systems" MIS Quarterly. Vol. 4, No. 4, pp.1-25. defines a properly termed DSS as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
