Organisations are looking for specialised data sets that are catered to their particular requirements as a result of the quickly developing technology and the expanding need for precise and effective data analysis.
Using the Pangeanic BSC project as a focal point, this article will examine the development of unique data sets that contain bilingual segments categorised by domain and style.
What is a data set, and what kinds are there?
A data set is a structured collection of information that may include text, numbers, images, or a combination of these. To conduct analyses, studies, and experiments, data sets are utilised in a variety of sectors and disciplines, including data science, artificial intelligence, statistics, scientific research, and many more. Depending on several factors, data sets can be categorised into their structure and type.
Depending on the data type
There are many different kinds of data sets that can be categorised based on attributes including format, organisation, and purpose. According to their kind, some of the most typical types of Customs data sets include:
Data sets that track a variable's development through time are called time series data. These data sets frequently include timestamps, which makes it possible to analyse patterns and trends across time. Weather, stock price, and traffic statistics are a few examples of time series data sets.
Data sets comprising images, such as photographs, medical images, satellite images, or other kinds of images, are referred to as image data. Typically, these data sets are utilised in computer vision for picture and object recognition.
Data sets comprising text, such as papers, text messages, tweets, or news, are referred to as text data. Natural language processing applications, including sentiment analysis, text categorization, and other tasks involving text processing, utilise these data sets.
Data sets including information created by people on social networks like Facebook, Twitter, or Instagram are referred to as social network data. Online behavioural research, opinion mining, and social network analysis all make use of these data sets.
Data sets including geographic information, such as GPS coordinates, maps, or geospatial sensor data, are referred to as geospatial data. Applications for mapping, location analysis, and geolocation use these data sets.