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Cognitive Computing
Cognitive computing (CC) refers to technology platforms that, broadly speaking, are based on the scientific disciplines of artificial intelligence and signal processing. These platforms encompass machine learning, reasoning, natural language processing, speech recognition and vision (object recognition), human–computer interaction, dialog and narrative generation, among other technologies. Definition At present, there is no widely agreed upon definition for cognitive computing in either academia or industry. In general, the term cognitive computing has been used to refer to new hardware and/or software that mimics the functioning of the human brain (2004) and helps to improve human decision-making. In this sense, CC is a new type of computing with the goal of more accurate models of how the human brain/mind senses, reasons, and responds to stimulus. CC applications link data analysis and adaptive page displays ( AUI) to adjust content for a particular type of audienc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computing Platform
A computing platform or digital platform is an environment in which a piece of software is executed. It may be the hardware or the operating system (OS), even a web browser and associated application programming interfaces, or other underlying software, as long as the program code is executed with it. Computing platforms have different abstraction levels, including a computer architecture, an OS, or runtime libraries. A computing platform is the stage on which computer programs can run. A platform can be seen both as a constraint on the software development process, in that different platforms provide different functionality and restrictions; and as an assistant to the development process, in that they provide low-level functionality ready-made. For example, an OS may be a platform that abstracts the underlying differences in hardware and provides a generic command for saving files or accessing the network. Components Platforms may also include: * Hardware alone, in the case ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Analysis
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. In statistical applications, data analysis can be divided into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Face Detection
Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene. Definition and related algorithms Face detection can be regarded as a specific case of object-class detection. In object-class detection, the task is to find the locations and sizes of all objects in an image that belong to a given class. Examples include upper torsos, pedestrians, and cars. Face detection simply answers two question, 1. are there any human faces in the collected images or video? 2. where is the located? Face-detection algorithms focus on the detection of frontal human faces. It is analogous to image detection in which the image of a person is matched bit by bit. Image matches with the image stores in database. Any facial feature changes in the database will invalidate the matching process. A reliable face-detectio ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sentiment Analysis
Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine. With the rise of deep language models, such as RoBERTa, also more difficult data domains can be analyzed, e.g., news texts where authors typically express their opinion/sentiment less explicitly.Hamborg, Felix; Donnay, Karsten (2021)"NewsMTSC: A Dataset for (Multi-)Target-dependent Sentiment Classification in Political News Articles" "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume" Examples The objective a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Speech Recognition
Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers with the main benefit of searchability. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis. Some speech recognition systems require "training" (also called "enrollment") where an individual speaker reads text or isolated vocabulary into the system. The system analyzes the person's specific voice and uses it to fine-tune the recognition of that person's speech, resulting in increased accuracy. Systems that do not use training are called "speaker-independent" systems. Systems that use training are called "speaker dependent". Speech recognitio ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Carcinogen
A carcinogen is any substance, radionuclide, or radiation that promotes carcinogenesis (the formation of cancer). This may be due to the ability to damage the genome or to the disruption of cellular metabolic processes. Several radioactive substances are considered carcinogens, but their carcinogenic activity is attributed to the radiation, for example gamma rays and alpha particles, which they emit. Common examples of non-radioactive carcinogens are inhaled asbestos, certain dioxins, and tobacco smoke. Although the public generally associates carcinogenicity with synthetic chemicals, it is equally likely to arise from both natural and synthetic substances. Carcinogens are not necessarily immediately toxic; thus, their effect can be insidious. Carcinogens, as mentioned, are agents in the environment capable of contributing to cancer growth. Carcinogens can be categorized into two different types: activation-dependent and activation-independent, and each nature impacts their l ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Tutor
TUTOR, also known as PLATO Author Language, is a programming language developed for use on the PLATO system at the University of Illinois at Urbana-Champaign beginning in roughly 1965. TUTOR was initially designed by Paul Tenczar for use in computer assisted instruction (CAI) and computer managed instruction (CMI) (in computer programs called "lessons") and has many features for that purpose. For example, TUTOR has powerful answer-parsing and answer-judging commands, graphics, and features to simplify handling student records and statistics by instructors. TUTOR's flexibility, in combination with PLATO's computational power (running on what was considered a supercomputer in 1972), also made it suitable for the creation of games — including flight simulators, war games, dungeon style multiplayer role-playing games, card games, word games, and medical lesson games such as ''Bugs and Drugs'' (''BND''). TUTOR lives on today as the programming language for the Cyber1 PLATO Sys ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Anxiety
Anxiety is an emotion which is characterized by an unpleasant state of inner turmoil and includes feelings of dread over anticipated events. Anxiety is different than fear in that the former is defined as the anticipation of a future threat whereas the latter is defined as the emotional response to a real threat. It is often accompanied by nervous behavior such as pacing back and forth, somatic complaints, and rumination. Anxiety is a feeling of uneasiness and worry, usually generalized and unfocused as an overreaction to a situation that is only subjectively seen as menacing. It is often accompanied by muscular tension, restlessness, fatigue, inability to catch one's breath, tightness in the abdominal region, nausea, and problems in concentration. Anxiety is closely related to fear, which is a response to a real or perceived immediate threat (fight or flight response); anxiety involves the expectation of future threat including dread. People facing anxiety may withdraw ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Unstructured Data
Unstructured data (or unstructured information) is information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Unstructured information is typically text-heavy, but may contain data such as dates, numbers, and facts as well. This results in irregularities and ambiguities that make it difficult to understand using traditional programs as compared to data stored in fielded form in databases or annotated ( semantically tagged) in documents. In 1998, Merrill Lynch said "unstructured data comprises the vast majority of data found in an organization, some estimates run as high as 80%." It's unclear what the source of this number is, but nonetheless it is accepted by some. Other sources have reported similar or higher percentages of unstructured data. , IDC and Dell EMC project that data will grow to 40 zettabytes by 2020, resulting in a 50-fold growth from the beginning of 2010. More recently, IDC and Seagate predict that the global data ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Unstructured Information
Unstructured data (or unstructured information) is information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Unstructured information is typically text-heavy, but may contain data such as dates, numbers, and facts as well. This results in irregularities and ambiguities that make it difficult to understand using traditional programs as compared to data stored in fielded form in databases or annotated ( semantically tagged) in documents. In 1998, Merrill Lynch said "unstructured data comprises the vast majority of data found in an organization, some estimates run as high as 80%." It's unclear what the source of this number is, but nonetheless it is accepted by some. Other sources have reported similar or higher percentages of unstructured data. , IDC and Dell EMC project that data will grow to 40 zettabytes by 2020, resulting in a 50-fold growth from the beginning of 2010. More recently, IDC and Seagate predict that the global data ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neural Network
A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning resulting fro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
DIKW Pyramid
The DIKW pyramid, also known variously as the DIKW hierarchy, wisdom hierarchy, knowledge hierarchy, information hierarchy, information pyramid, and the data pyramid, refers loosely to a class of models for representing purported structural and/or functional relationships between data, information, knowledge, and wisdom. "Typically information is defined in terms of data, knowledge in terms of information, and wisdom in terms of knowledge".The DIKW acronym has worked into the rotation from knowledge management. It demonstrates how the deep understanding of the subject emerges, passing through four qualitative stages: "D" – data, "I" – information, "K" – knowledge and "W" – wisdom Not all versions of the DIKW model reference all four components (earlier versions not including data, later versions omitting or downplaying wisdom), and some include additional components. In addition to a hierarchy and a pyramid, the DIKW model has also been characterized as a chain, as a fra ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
