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Strategies to Choose the Right Natural Language Processing (NLP) Solution

By Nikhil Sonawane - October 20, 2022 3 Mins Read

Business leaders are leveraging Natural Language Processing (NLP) and Machine Learning to get valuable insights from all the gathered data.

Enterprises today gather, store, and process huge amounts of documents, data, and information in various formats and types. There is a tremendous amount of data available in investor reports, sales orders, client manuals, official documents, text, emails, and other document formats. The best NLP software is capable of gathering and interpreting text enabling systems to learn, evaluate and understand human interactions. There are multiple vendors that offer various natural language processing tools that enterprises can leverage to enhance internal efficiency and get more visibility into customer behavior. However, not all the NLP tools will help the organization to bridge the gaps in their workflows or get valuable insights from their customer interactions.

Before enterprises embark on a journey to integrate natural language processing tools in their IT infrastructure; they can consider the following points to explore, evaluate and select the right NLP solutions:

Contextual analytics and advanced linguistic capabilities

The best natural language processing tool should be capable of identifying linguistic entities and determining relationships and context, irrespective of how it is written. Moreover, it should have all the relevant references to ensure accuracy in the understanding of the context. Enterprises should be able to scan all the documents on the business network; gather all the crucial information usually stored in complex tables. Furthermore, business leaders need to have structured data as an outcome to seamlessly group and visualize data sets and ingest the results into the data lakehouse or leverage them to develop machine learning models. IT decision-makers need to evaluate the NLP vendors based on their contextual analytics and advanced linguistic capabilities to interpret the text or interactions.

Scalability and regular updates

Business leaders should select an NLP tool that adapts to the business needs and scale with them.

Evaluating the natural language processing vendor based on its scalability, reliability, costs, and after-sales service is crucial.

As the technology is developing tremendously, the NLP vendor should have a talented DevOps team that constantly works on updating the solution to remove bugs and scale with the demands of the market. The are many natural language processing solutions that customize the tool according to the organization’s needs.

Domain knowledge

In industry 4.0, every sector that has embraced a digital-first approach is flourishing at an exponential rate. Enterprises need a natural language processing solution that has the domain expertise to adapt to business needs and scale with them. Implementing an NLP tool that has deep domain expertise will enable organizations to maximize efficiency and productivity.

Seamless integration with the other tools in the IT infrastructure

It is crucial that the natural language processing which the enterprise selects needs to have an open architecture. Because enterprises might require to add or update the tools as per the business requirements, additionally, it is crucial to select an NLP solution that seamlessly integrates with the other tools and applications in the IT infrastructure to streamline the workflows. The natural language processing solution should be able to seamlessly integrate unstructured data with managing Master Data, data warehouses, and other data analytics tools.

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AUTHOR

Nikhil Sonawane

Nikhil S is a Tech Journalist with OnDot Media. He is a media professional with eclectic experience in communications for various technology media brands. He brings his eye for editorial detail and keen sense of language skills to every article he writes.

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