Data Science Seminar
Identifying Keyphrases from Text Documents - From Heuristics to Language Models
Debanjan Mahata
Identifying Keyphrases from Text Documents - From Heuristics to Language Models
| When | Friday, April 1, 2022, 3:00 PM – 4:00 PM (MT) |
|---|---|
| Where | " |
Abstract
Automatic identification of keyphrases from text documents is an extreme summarization problem that lies at the intersection of the areas of natural language processing (NLP) and information retrieval (IR). Keyphrases aid in capturing the most salient topics from the input text and are useful in multiple downstream tasks such as classification, clustering, summarization, document recommendation, query expansion, interactive document retrieval, semantic and faceted search. Despite the ground-breaking advancements triggered by deep neural networks, automatically identifying keyphrases from text using machine learning techniques is still a challenging problem that hasn’t been explored as much as other related and popular tasks such as named entity extraction, question answering, summarization. This talk will provide an overview of the advances made in keyphrase extraction and generation from text documents and present the approaches, datasets, evaluation strategies, and the associated challenges. It will also dive into the topic of how language models have been effective in pushing state-of-the-art performances in this domain. Lastly, the speaker will present the current trends and future directions for research in this domain.
Speaker
Debanjan Mahata
Moody Analytics
Debanjan Mahata is a Director of AI at Moody’s Analytics, New York, and leads the KYC machine learning team. He is also an Adjunct Faculty at the Department of Computer Science and Engineering, Indraprastha Institute of Information Technology (IIIT-Delhi). He closely collaborates with the Multimodal Digital Media Analysis lab (MIDAS@IIITD). His work lies at the intersection of natural language processing and information retrieval. He is currently interested in keyphrase extraction and generation, understanding code-switched text from social media, and computational social science problems solved using NLP. Before joining Moody’s in August 2021, he was a Senior Research Scientist at Bloomberg AI (Nov 2017 - Jul 2021) and Senior Research Associate at Infosys Limited, Palo Alto, California (Aug 2015 - Oct 2017). He holds a Ph.D. in Integrated Computing from Donaghey College of Engineering and Information Technology, University of Arkansas at Little Rock.
Tags: deep learning machine learning natural language processing society & policy
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