The Creation of Custom Data Sets to Meet Customer Needs: A BSC Project
Rapidly advancing technology and the growing need for accurate and efficient data analysis have led organizations to seek customized data sets tailored to their specific needs.
Rapidly advancing technology and the growing need for accurate and efficient data analysis have led organizations to seek customized data sets tailored to their specific needs.
In this article, we will explore the creation of custom data sets containing bilingual segments classified by domain and style, using the Pangeanic BSC project as a key example.
A data set is a structured collection of information, which can be numeric, textual, visual or a combination of these data types. Data sets are used in various fields and disciplines, such as data science, artificial intelligence, statistics, scientific research and many others, to perform analyses, studies and experiments. Data sets can be divided into several categories depending on their type and structure.
There are several types of data sets, which can be classified according to various characteristics, such as format, structure and purpose. Some of the most common types of data sets according to their type are:
These are just a few examples of the types of data sets that exist. Data sets can be very diverse and vary depending on the domain and purpose of analysis.
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Data sets can also be classified according to their structure. Some of the most common data types, based on their structure, include:
Using a data set, which is a collection of organized and structured information, offers numerous advantages in a variety of contexts. Here are some important advantages of using a data set:
In short, data sets are fundamental tools for data analysis, research, machine learning development and informed decision-making. They provide a solid foundation for decision-making, gaining insights, identifying patterns and opportunities, and improving the user experience, which can lead to better outcomes and greater understanding in a wide range of applications and contexts.
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Personalized data sets enable companies to better understand their customers, allowing them to personalize product offerings and improve their customer experience.
Access to unique and customized data sets can provide organizations with a significant competitive advantage, enabling them to make informed decisions faster and more effectively.
Customized data sets can also provide valuable information on specific industries, helping organizations stay ahead of trends and developments. In addition, they can improve the performance of machine learning models by providing highly relevant and domain-specific data for training and validation.
The Pangeanic BSC project focuses on the creation of customized data sets containing bilingual segments classified by domain and style. This innovative approach responds to the growing demand for high-quality customized data in various industries.
The project emphasizes bilingual data collection, which can be used to train machine translation systems, linguistic models and other natural language processing applications. Data sets are classified by domain, ensuring that users can access data relevant to their industry and area of interest, leading to more accurate and meaningful results. In addition, stylistic classification allows for greater granularity of data, taking into account the specific nuances of different writing styles and registers.
In order to create a labeled bilingual English-Catalan data set, several steps were followed, as detailed below:
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Since representativeness in the construction of a text data set is essential to ensure the quality and reliability of the models that use them, some guidelines were followed to try to ensure this, classifying the text by domain and style. As a result, an analysis of the definition of the labels was carried out to ensure that there are no inconsistencies or overlaps in the definitions of the labels.
In addition, special care was taken when selecting data sources, so that they were varied, and to avoid bias in the data, as well as obtaining an adequate amount of data from different sources and writing styles to avoid over representation of any of them.
The representativeness of a data set is not static, but can evolve over time. It is important to perform periodic updates of the data set, add new data from different sources and writing styles, correct possible errors in the annotation and improve the quality of the data set.
In summary, an exhaustive process was undertaken that included selecting domains and text styles, identifying and obtaining data sources, data crawling, data cleaning and processing, data validation and labeling, and preparing the data set for use in natural language processing applications. This bilingual English-Catalan data set is a very valuable resource, especially considering that Catalan is a low-resource language.
By offering customized data sets that are tailored to clients' unique needs, the Pangeanic BSC project sets a new standard for data quality and relevance, paving the way for more efficient and accurate data-driven solutions in a variety of industries.
Rapidly advancing technology and the growing need for accurate and efficient data analysis have led organizations to seek customized data sets tailored to their specific needs.
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