Artificial Named Entity Classifier based on BiLSTM for an AI-Based Business Analyst

Artificial Named Entity Classifier based on BiLSTM for an AI-Based Business Analyst

Excited to share that the NLP-AI research paper, authored by Taaniya Arora, Neha Prabhugaonkar, Ganesh Subramanian, Kathy Leake was accepted for the 10th International Conference on Natural Language Processing (NLP 2021) to be held in December 23 ~ 24, 2021, Sydney, Australia. The paper is included in the proceedings published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT), Vol 11. 


Business users across enterprises today rely on reports and dashboards created by IT organizations to understand the dynamics of their business better and get insights into the data. In many cases, these users are underserved and do not possess the technical skillset to query the source of data to get the information they need. There is a need for users to access information in the most natural way possible. AI-based Business Analysts are going to change the future of business analytics and business intelligence by providing a natural language interface between the user and data. This natural language interface is capable of understanding ambiguous questions from users in a natural form, understand the intent and convert the same into a database query.

One of the important elements of an AI-based business analyst is to interpret a natural language question. It also requires identification of key business entities within the question and relationship between them to generate insights. The Artificial Named Entity Classifier helps us take a huge step forward in that direction by not only identifying, but also classifying, entities with the help of the sequence recognizing prowess of BiLSTMs.

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