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A demographic profile is a form of demographic analysis in which information is gathered about a group to better understand the group's composition or behaviors for the purpose of providing more relevant services. In business, a demographic profile is usually used to increase marketing efficiency.
Profiles must also be classified according to the kind of subject they refer to. This subject can either be an individual or a group of people. When a profile is constructed with the data of a single person, this is called individual profiling (Jaquet-Chiffelle 2008). This kind of profiling is used to discover the particular characteristics of ...
Social profiling is the process of constructing a social media user's profile using his or her social data.In general, profiling refers to the data science process of generating a person's profile with computerized algorithms and technology. [1]
A user profile can be of any format if it contains information, settings and/or characteristics specific to an individual. Most popular user profiles include those on photo and video sharing websites such as Facebook and Instagram, accounts on operating systems, such as those on Windows and MacOS and physical documents such as passports and driving licenses.
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In the information sciences, an application profile consists of a set of metadata elements, policies, and guidelines defined for a particular application. [1]The elements may come from one or more element sets, thus allowing a given application to meet its functional requirements by using metadata from several element sets - including locally defined sets.
The HEVC Main Profile (MP) has been compared in coding efficiency to H.264/MPEG-4 AVC High Profile (HP), MPEG-4 Advanced Simple Profile (ASP), H.263 High Latency Profile (HLP), and H.262/MPEG-2 Main Profile (MP). The video encoding was done for entertainment applications and twelve different bitrates were made for the nine video test sequences ...
Data profiling utilizes methods of descriptive statistics such as minimum, maximum, mean, mode, percentile, standard deviation, frequency, variation, aggregates such as count and sum, and additional metadata information obtained during data profiling such as data type, length, discrete values, uniqueness, occurrence of null values, typical string patterns, and abstract type recognition.