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Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do.
A design is a plan or specification for the construction of an object or system or for the implementation of an activity or process, or the result of that plan or specification in the form of a prototype, product or process. The verb to design expresses the process of developing a design. In some cases, the direct construction of an object without an explicit prior plan may also be considered to be a design activity. The design usually has to satisfy certain goals and constraints; may take into account aesthetic, functional, economic, or socio-political considerations; and is expected to interact with a certain environment. Typical examples of designs include architectural blueprints, engineering drawings, business processes, circuit diagrams, and sewing patterns.
Interdisciplinarity or interdisciplinary studies involves the combination of two or more academic disciplines into one activity. It draws knowledge from several other fields like sociology, anthropology, psychology, economics etc. It is about creating something by thinking across boundaries. It is related to an interdiscipline or an interdisciplinary field, which is an organizational unit that crosses traditional boundaries between academic disciplines or schools of thought, as new needs and professions emerge. Large engineering teams are usually interdisciplinary, as a power station or mobile phone or other project requires the melding of several specialties. However, the term "interdisciplinary" is sometimes confined to academic settings.
Data mining is a process of searching, extracting and analyzing discovering various types of text graphic patterns, language and literary figures, stylistics, in large amounts of textual or mixed visual and textual data sets, that also involves methods at the intersection of machine learning, formal linguistics analyses as textual statistics, and database systems. Data mining evolved from specifically computer linguistics field to an interdisciplinary subfield of linguistics, art sciences and computer science, and linguistic and mathematical statistics with an overall goal of extracting information from a given data set, formulate results of analyses, and further may transform this resulting information into a summarized and comprehensible structure, and even to a new subset for further use. Here new emerging field is the "knowledge discovery in databases" process, or KDD, that is sometimes understood as next step after the DM searching and analysing process. Aside from the raw programming text analysis step, it also involves database engineering, database management and in some cases data management aspects; it starts with data pre-processing, constructing statistical models, data processing using strict and not strict statistical inferences either as considerations or as preanalysis stage, measurement of intelligence level results, public interest metrics, computational complexity considerations, various types of post-processing of discovered structures, data visualization, and online updating.
Knowledge management (KM) is the collection of methods relating to creating, sharing, using and managing the knowledge and information of an organization. It refers to a multidisciplinary approach to achieve organisational objectives by making the best use of knowledge.
Software development is the process of conceiving, specifying, designing, programming, documenting, testing, and bug fixing involved in creating and maintaining applications, frameworks, or other software components. Software development involves writing and maintaining the source code, but in a broader sense, it includes all processes from the conception of the desired software through to the final manifestation of the software, typically in a planned and structured process. Software development also includes research, new development, prototyping, modification, reuse, re-engineering, maintenance, or any other activities that result in software products.
Algorithmic composition is the technique of using algorithms to create music.
Computational semiotics is an interdisciplinary field that applies, conducts, and draws on research in logic, mathematics, the theory and practice of computation, formal and natural language studies, the cognitive sciences generally, and semiotics proper. The term encompasses both the application of semiotics to computer hardware and software design and, conversely, the use of computation for performing semiotic analysis. The former focuses on what semiotics can bring to computation; the latter on what computation can bring to semiotics.
A concept map or conceptual diagram is a diagram that depicts suggested relationships between concepts. Concept maps may be used by instructional designers, engineers, technical writers, and others to organize and structure knowledge.
Belief revision is the process of changing beliefs to take into account a new piece of information. The logical formalization of belief revision is researched in philosophy, in databases, and in artificial intelligence for the design of rational agents.
A blackboard system is an artificial intelligence approach based on the blackboard architectural model, where a common knowledge base, the "blackboard", is iteratively updated by a diverse group of specialist knowledge sources, starting with a problem specification and ending with a solution. Each knowledge source updates the blackboard with a partial solution when its internal constraints match the blackboard state. In this way, the specialists work together to solve the problem. The blackboard model was originally designed as a way to handle complex, ill-defined problems, where the solution is the sum of its parts.
Dedre Dariel Anne Cooke Gentner is an American cognitive and developmental psychologist. She is the Alice Gabriel Twight Professor of Psychology at Northwestern University. She is a leading researcher in the study of analogical reasoning.
Scientific modelling is a scientific activity, the aim of which is to make a particular part or feature of the world easier to understand, define, quantify, visualize, or simulate by referencing it to existing and usually commonly accepted knowledge. It requires selecting and identifying relevant aspects of a situation in the real world and then using different types of models for different aims, such as conceptual models to better understand, operational models to operationalize, mathematical models to quantify, computational models to simulate, and graphical models to visualize the subject.
Integrative learning is a learning theory describing a movement toward integrated lessons helping students make connections across curricula. This higher education concept is distinct from the elementary and high school "integrated curriculum" movement.
Grammar induction is the process in machine learning of learning a formal grammar from a set of observations, thus constructing a model which accounts for the characteristics of the observed objects. More generally, grammatical inference is that branch of machine learning where the instance space consists of discrete combinatorial objects such as strings, trees and graphs.
Process mining is a family of techniques relating the fields of data science and process management to support the analysis of operational processes based on event logs. The goal of process mining is to turn event data into insights and actions. Process mining is an integral part of data science, fueled by the availability of event data and the desire to improve processes. Process mining techniques use event data to show what people, machines, and organizations are really doing. Process mining provides novel insights that can be used to identify the executional path taken by operational processes and address their performance and compliance problems.
Enterprise engineering is the body of knowledge, principles, and practices used to design all or part of an enterprise. An enterprise is a complex socio-technical system that comprises people, information, and technology that interact with each other and their environment in support of a common mission. One definition is: "an enterprise life-cycle oriented discipline for the identification, design, and implementation of enterprises and their continuous evolution", supported by enterprise modelling. The discipline examines each aspect of the enterprise, including business processes, information flows, material flows, and organizational structure. Enterprise engineering may focus on the design of the enterprise as a whole, or on the design and integration of certain business components.
The science of team science (SciTS) field encompasses both conceptual and methodological strategies aimed at understanding and enhancing the processes and outcomes of collaborative, team-based research. It is useful to distinguish between team science (TS) initiatives and the science of team science (SciTS) field. Team science initiatives are designed to promote collaborative, and often cross-disciplinary approaches to answering research questions about particular phenomena. The SciTS field, on the other hand, is concerned with understanding and managing circumstances that facilitate or hinder the effectiveness of collaborative science, and evaluating the outcomes of collaborative science. Its principal units of analysis are the research, training, and community-based translational initiatives implemented by both public and private sector organizations.
Knowledge extraction is the creation of knowledge from structured and unstructured sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to information extraction (NLP) and ETL, the main criterion is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge or the generation of a schema based on the source data.
This glossary of artificial intelligence is a list of definitions of terms and concepts relevant to the study of artificial intelligence, its sub-disciplines, and related fields. Related glossaries include Glossary of computer science, Glossary of robotics, and Glossary of machine vision.