Data in all aspects drive today’s world. Data is collected from almost all actions, from various sources, and utilized in many other ways. Text data lacks structure in this aspect; however natural language can provide structure to data.
When you’re wondering what “natural language is structured data” means, there are many possible answers. To know more about it, you need to know what natural language is, how it relates to structured data, and more.
What is Natural Language?
Natural language for data processing is known to be a language that has developed naturally. It means that artificial language or computer code isn’t utilized when developed.
Natural language is used by humans and developed through continuous use over the years. It is not constructed by computers and signified by ambiguity. Ambiguity is a feature that isn’t present in AI, and therefore it can’t be processed by technology optimally.
How Does It Relate to Structured Data?
Structured data is used by applications, software, and technology to find specific sets of information or data. It is also categorized as quantitative data. Machine learning algorithms easily organize it.
Natural language relates to language that computers haven’t developed. Traditionally, structured data is not associated with natural language. Structured data can be easily organized and deciphered, which is not the case with natural language.
Structured data comes in many forms, from unstructured to semi-structured. However, natural language has its structure, which means it’s structured, albeit differently.
Natural Language in Graph Form
Natural language can also be displayed in various forms, including graphs. Natural Language Processing techniques are most frequently used when handling anything with even a bit of natural language.
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Leveraging patterns found in natural language to be presented in graphs is one of the best ways to utilize natural language. Word embedding techniques such as Word2vec can construct graphs relating to keywords. Cosine similarity can also be derived from these techniques and graphs.
Graphs can also be further utilized by applying algorithms such as PageRank to learn which words can have the most influence over any given set of documents. Using these techniques and software is essential to ensure that your vast natural language database isn’t wasted.
How to Extract Data
The graph database is the only one-way natural language used in data forms. There are many ways to capture the intrinsic structure within natural language when you have an expert and capable software handling it for you.
It can be extracted in several ways depending on the natural language data. Utilizing graph databases is one of the simplest ways and requires little expert management.
Natural Language as Structured Data: Overview
While many people believe that natural language is not structured data, it isn’t entirely correct. Natural language is structured data, and there are many ways that natural language can be used as a valuable source of information when you know what to look for. Natural language has its structure, and when you know how to utilize it, it can be a resourceful asset.
When moving forward with your database management, consider getting software that enables you to optimize natural language according to your needs.
