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Population Profiling
In information science, profiling refers to the process of construction and application of user profiles generated by computerized data analysis. This is the use of Algorithm, algorithms or other mathematical techniques that allow the pattern recognition, discovery of patterns or correlations in large quantities of data, aggregated in databases. When these patterns or correlations are used to identify or represent people, they can be called ''profiles''. Other than a discussion of profiling ''technologies'' or ''population profiling'', the notion of profiling in this sense is not just about the construction of profiles, but also concerns the ''application'' of group profiles to individuals, e. g., in the cases of credit scoring, price discrimination, or identification of security risks . Profiling is being used in Data analysis techniques for fraud detection, fraud prevention, ambient intelligence, consumer analytics, and surveillance. Statistical methods of profiling includ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Preparation
Data preparation is the act of manipulating (or pre-processing) raw data (which may come from disparate data sources) into a form that can be readily and accurately analysed, e.g. for business purposes. Data preparation is the first step in data analytics projects and can include many discrete tasks such as loading data or data ingestion, data fusion, data cleaning, data augmentation, and data delivery. The issues to be dealt with fall into two main categories: * systematic errors involving large numbers of data records, probably because they have come from different sources; * individual errors affecting small numbers of data records, probably due to errors in the original data entry. Data specification The first step is to set out a full and detailed specification of the format of each data field and what the entries mean. This should take careful account of: * most importantly, consultation with the users of the data * any available specification of the system which wil ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Customer Analytics
Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing, site selection, and customer relationship management. Marketing provides services to satisfy customers. With that in mind, the productive system is considered from its beginning at the production level, to the end of the cycle at the consumer. Customer analytics plays an important role in the prediction of customer behavior. Uses ;Retail:Although until recently over 90% of retailers had limited visibility on their customers, with increasing investments in loyalty programs, customer tracking solutions and market research, this industry started increasing use of customer analytics in decisions ranging from product, promotion, price and distribution management. The most obvious use of customer analytics in retail today is the development of personalized communic ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Forensic Science
Forensic science combines principles of law and science to investigate criminal activity. Through crime scene investigations and laboratory analysis, forensic scientists are able to link suspects to evidence. An example is determining the time and cause of death through autopsies. This evidence can then be used for proof towards a crime. Forensic science, often confused with criminalistics, is the application of science principles and methods to support legal decision-making in matters of Criminal law, criminal and Civil law (legal system), civil law. During criminal investigation in particular, it is governed by the legal standards of admissible evidence and criminal procedure. It is a broad field utilizing numerous practices such as the analysis of Genetic analysis, DNA, fingerprints, Bloodstain pattern analysis, bloodstain patterns, firearms, ballistics, toxicology, microscopy, and fire debris analysis. Forensic scientists collect, preserve, and analyze evidence during the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Attention Management
Attention management refers to models and tools for supporting the management of attention at the individual or at the collective level (cf. attention economy), and at the short-term (quasi real time) or at a longer term (over periods of weeks or months). The ability to control distractions and stay focused is essential to produce higher quality results. A research conducted by Stanford shows that single-tasking is more effective and productive than multi-tasking. Different studies have been conducted in using Information and Communications Technology (ICT) for supporting attention, and in particular, models have been elaborated for supporting attention. Background The scarcity of attention is the underlying assumption for attention management; the researcher Herbert A. Simon pointed out that when there is a vast availability of information, attention becomes the more scarce resource as human beings cannot digest all the information. Fundamentally, attention is limited by the pr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Adaptive Hypermedia
Adaptive hypermedia (AH) uses hypermedia which is adaptive according to a '' user model''. In contrast to regular hypermedia, where all users are offered the same set of hyperlinks, adaptive hypermedia (AH) tailors what the user is offered based on a model of the user's goals, preferences and knowledge, thus providing links or content most appropriate to the current user. Background Adaptive hypermedia is used in educational hypermedia, on-line information and help systems, as well as institutional information systems. Adaptive educational hypermedia tailors what the learner sees to that learner's goals, abilities, needs, interests, and knowledge of the subject, by providing hyperlinks that are most relevant to the user in an effort to shape the user's cognitive load. The teaching tools "adapt" to the learner. On-line information systems provide reference access to information for users with a different knowledge level of the subject. An adaptive hypermedia system should satisfy th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Employee Monitoring
Employee monitoring is the (often automated) surveillance of workers' activity. Organizations engage in employee monitoring for different reasons, such as to track performance, avoid legal liability, protect trade secrets, or address other security concerns. This practice may impact employee satisfaction due to its impact on the employee's privacy. Among organizations, the extent and methods of employee monitoring differ. Surveillance methods A company can use its everyday electronic devices to monitor its employees almost continuously. Common methods include software monitoring, telephone tapping, video surveillance, email monitoring, and location monitoring. Software monitoring. Companies often use employee monitoring software to track what their employees are doing on their computers. Tracking data may include typing speed, mistakes, applications used, and what specific keys are pressed. Telephone tapping can be used to monitor and record employees' phone call details a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Money-laundering
Money laundering is the process of illegally concealing the origin of money obtained from illicit activities (often known as dirty money) such as drug trafficking, sex work, terrorism, corruption, and embezzlement, and converting the funds into a seemingly legitimate source, usually through a front organization. Money laundering is illegal; the acts generating the money almost always are themselves crime, criminal in some way (for if not, the money would not need to be laundered). As financial crime has become more complex and financial intelligence is more important in combating transnational crime, international crime and terrorism, money laundering has become a prominent political debate, political, economics, economic, and legal debate. Most countries implement some anti-money laundering, anti-money-laundering measures. In the past, the term "money laundering" was applied only to financial transactions related to organized crime. Today its definition is often expanded by go ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fraud Prevention
In law, fraud is intentional deception to deprive a victim of a legal right or to gain from a victim unlawfully or unfairly. Fraud can violate civil law (e.g., a fraud victim may sue the fraud perpetrator to avoid the fraud or recover monetary compensation) or criminal law (e.g., a fraud perpetrator may be prosecuted and imprisoned by governmental authorities), or it may cause no loss of money, property, or legal right but still be an element of another civil or criminal wrong. The purpose of fraud may be monetary gain or other benefits, such as obtaining a passport, travel document, or driver's licence. In cases of mortgage fraud, the perpetrator may attempt to qualify for a mortgage by way of false statements. Terminology Fraud can be defined as either a civil wrong or a criminal act. For civil fraud, a government agency or person or entity harmed by fraud may bring litigation to stop the fraud, seek monetary damages, or both. For criminal fraud, a person may be prose ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine-readable Data
In communications and computing, a machine-readable medium (or computer-readable medium) is a medium capable of storing data in a format easily readable by a digital computer or a sensor. It contrasts with ''human-readable'' medium and data. The result is called machine-readable data or computer-readable data, and the data itself can be described as having machine-readability. Data Machine-readable data must be structured data. Attempts to create machine-readable data occurred as early as the 1960s. At the same time that seminal developments in machine-reading and natural-language processing were releasing (like Weizenbaum's ELIZA), people were anticipating the success of machine-readable functionality and attempting to create machine-readable documents. One such example was musicologist Nancy B. Reich's creation of a machine-readable catalog of composer William Jay Sydeman's works in 1966. In the United States, the OPEN Government Data Act of 14 January 2019 defines ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Unsupervised Learning
Unsupervised learning is a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled data. Other frameworks in the spectrum of supervisions include weak- or semi-supervision, where a small portion of the data is tagged, and self-supervision. Some researchers consider self-supervised learning a form of unsupervised learning. Conceptually, unsupervised learning divides into the aspects of data, training, algorithm, and downstream applications. Typically, the dataset is harvested cheaply "in the wild", such as massive text corpus obtained by web crawling, with only minor filtering (such as Common Crawl). This compares favorably to supervised learning, where the dataset (such as the ImageNet1000) is typically constructed manually, which is much more expensive. There were algorithms designed specifically for unsupervised learning, such as clustering algorithms like k-means, dimensionality reduction techniques l ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Mining
Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use. Data mining is the analysis step of the " knowledge discovery in databases" process, or KDD. Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. The term "data mining" is a misnomer because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction (''mining'') of data itself. It also is a buzzwo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
