Evaluating Deep Learning Algorithms for Natural Language Processing SpringerLink

This application is also useful for the health industry, particularly in areas such as pharmacovigilance. For the financial sector NLPs ability to reduce risk and improve risk models may prove invaluable. Their Kore platform is designed to help financial institutions develop AI systems to forecast risk. Increasingly major organisations, such as General Motors, are using social media to improve their reputation and product.

This technology works on the speech provided by the user breaks it down for proper understanding and processes it accordingly. This is a very recent and effective approach due to which it has a really high demand in today’s market. Natural Language Processing is an upcoming field where already many transitions such as compatibility with smart devices, and interactive talks with a human have been made possible. Knowledge representation, logical reasoning, and constraint satisfaction were the emphasis of AI applications in NLP. In the last decade, a significant change in NLP research has resulted in the widespread use of statistical approaches such as machine learning and data mining on a massive scale.

Methods

As the amount of data, particularly unstructured data, that we produce continues to grow, NLP will be key to classifying, understanding and using it. This application can be used to process written notes such as clinical documents or patient referrals. This virtual assistant can search a claim, extracting the relevant information and providing insurance agents with the right information. It can also be used by customer service personnel when searching for the right information. Natural language processing allows for the automation of customer communication.

Symbolic algorithms can support machine learning by helping it to train the model in such a way that it has to make less effort to learn the language on its own. Although machine learning supports symbolic ways, the ML model can create an initial rule set for the symbolic and spare the data scientist from building it manually. NLP is a dynamic technology that uses different methodologies to translate complex human language for machines. It mainly utilizes artificial intelligence to process and translate written or spoken words so they can be understood by computers.

#5. Knowledge Graphs

Event discovery in social media feeds (Benson et al.,2011) [13], using a graphical model to analyze any social media feeds to determine whether it contains the name of a person or name of a venue, place, time etc. This study was a systematic review that aimed to review articles that extracted cancer concepts using NLP. Subsequently, the titles and abstracts of the remaining articles were screened, and inclusion and exclusion criteria were applied. After applying exclusion criteria, a total of 2436 articles were excluded, and 67 studies were deemed relevant. The full texts of these articles were reviewed, and finally, 17 articles were selected, and their information was extracted (Fig. 1).

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