Everything you need to know about Text and Data Mining

What is Text and Data Mining? 

TDM is the process of stemming high-quality information from text, making use of technology to extract new, unknown information from different written sources. And what type of sources are we talking about? They can range from books, emails, websites, articles, reviews, and so on.

According to an analysis, 80 percent of business-relevant information originates in unstructured form, primarily text (Unstructured Data and the 80 Percent Rule), so these techniques help discover and present important knowledge that would otherwise never be available for automated processing. 

TDM allows patterns and relationships to be found, semantics to be analysed and ultimately figure out how content relates to ideas. This is incredibly useful for research and studies. 

The goal of text and data mining is to filter through information, identify pieces of data, and find the relationships and patterns among them. – Mary Ellen Bates

Source: Springer Nature

Why?

Text mining empowers R&D teams to methodically and productively look at content to solution problems that eventually lead to business decisions. The other option would be to curate thousands of pieces of content manually and, given today’s huge stream of research publications and fast-paced environment, this would be unachievable.

How?

TDM tools use sophisticated software which applies natural language processing (NLP) algorithms to read and analyse text. The process can be divided into 2 phases:

1. Identifying the entities a company’s interested in. For instance, in biomedicine these might be genes, cell lines, proteins, small molecules, and so on.
2. Inspecting sentences in which those entities appear, in order to determine how they relate to each other. A relationship is a connection between at least two entities.

Format

The favoured format for text mining software is XML. It stands for “Extensible Markup Language,” a markup language that defines a set of document coding rules in a format that is both human-readable and machine-readable. It is largely used for encoding documents so that computer programs can examine or disclose the content fittingly.

TDM at Springer Nature

Springer Nature is well-known for publishing trusted research and championing open science. They recognise the importance of new research and the need to support innovation, which is why they have streamlined their TDM policy and optimised the tools for researchers. 

Scientific publications have increased in the past few years, highlighting the importance of optimising the analysis of large amounts of data. Springer Nature offers TDM for subscribers, for non-subscribers (variety of TDM tools for our Open Access resources, such as our Open Access fulltext API), TDM for Open Access content (the Open Access API provides metadata and fulltext content where available for more than 500,000 online documents from Springer Nature open access XML, including BioMed Central and SpringerOpen journals). 

Springer Nature are hiring tech professionals. Their working philosophy is agile and highly motivated – with the atmosphere and culture of a start-up, embedded in a vital and dynamic publishing group. You’ll use cutting-edge technology to create applications, and perhaps most importantly, at the end of the day you’ll be home in time for dinner! 

They’re strengthening areas like Software Development, QA, Data Business Analysis, Agile, App Security, and more. Check out all open positions here.