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Text-Mined Knowledge Graphs — Beyond Text Mining

Text is the medium used to store the tremendous wealth of scientific knowledge regarding the world we live in. However, with its ever-increasing magnitude and throughput, analyzing this unstructured data has become an impossibly tedious task. This has led to the rise of Text Mining and Natural Language Processing (NLP) techniques and tools as the go-to for examining and processing large amounts of natural text data.

Text-Mining is the automatic extraction of structured semantic information from unstructured machine-readable text. The identification and further analysis of these explicit concepts and relationships help in discovering multiple insights contained in text in a scalable and efficient way.

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Text Mining 101: What it Is and How it Works

The modern world generates enormous amounts of data, and it is growing year by year. Data has become the most valuable managerial resource to provide a competitive edge and create knowledge management initiatives. Now manual data processing and classification has become costly and ineffective — and it has to be either automated entirely or used only when the important data is already selected automatically from the total quantity.

Text mining is essentially the automated process of deriving high-quality information from text. Its main difference from other types of data analysis is that the input data is not formalized in any way, which means it cannot be described with a simple mathematical function.