Does NLP mean business in the digital content development domain?
Publishing has witnessed some very interesting and disruptive transformations over the years. In today’s digital landscape, the publishing industry is quickly moving from a book-based product model to a services-based business model. Moreover, technological advancements have brought with them multitudes of opportunities and possibilities in learning and publishing.
Technological advancement isn’t complete without bringing in the term Artificial Intelligence (AI). Before we continue, let us quickly break AI down for you:
AI helps in building systems that can carry out intelligent tasks. Machine Learning (ML) and Natural Language Processing (NLP) are the two subsets of AI. While ML helps in building systems that can learn from experience, NLP helps in building systems that can understand language. Used together, ML and NLP help in building systems that can swiftly pick up languages.
AI capabilities have advanced to a large extent. In the context of the Publishing space, AI can automate significant portions of workflows, implying a direct positive effect on businesses and authors as well as the research community.
It is a long road ahead for NLP and AI to emulate human intelligence in content creation, and it is to be seen how both the industry and consumers together respond to a prospect like this. However, it cannot be ignored that NLP has made its indelible impact in the Publishing industry by incorporating grammar analysis into computer programs to recognize parts of a sentence and understand the structure of words to discern their meaning. NLP finds itself useful in the Digital Publishing space in various capacities:
The past witnessed NLP being employed only in analysing articles to determine the subject and define the metadata keywords for the article. Today, NLP finds its applications in Publishing and Editorial Management in many ways, going beyond mere copyediting.
With more innovative ideas to use these technologies, AI and NLP will slowly improve every stage of production, resulting in near instantaneous publishing. These technologies could help analyse a database of scholars with varied expertise and match the best individual for an appropriate peer review. AI and NLP can also identify when sections of articles have been taken directly from another source or where citations are missing or incorrect, thereby resolving issues of plagiarism. AI and NLP will not replace editors, but they will empower editors to provide more value to their authors.
With over a decade’s experience in the publishing domain, Integra today is one of the few end-to-end solutions providers for publishers. Find out how we use NLP to help our Publishers fast-track their processes. Speak to one of our experts today here.
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