Influencing Trends for Neural Information Processing Systems

EasyChair Preprint 2050

Abstract

Neural Information Processing Systems (NIPS) is leading Machine Learning and Computational Neuroscience conference in the world where innovative work is published. The NIPS include over million research papers describing various projects in the latest technologies. However, there are various problems to find out the trending topics in recent technologies for studying and research purpose due to its large amount of data. Consequently, Data Analytics may pinpoint the evolving trends within technologies like Machine Learning, Artificial Intelligence, etc. Natural Language Processing techniques allow us for relatively rapid and largely automated analysis of large collections of text data. The objectives of our project are to carry out a review of the papers accepted at NIPS in the 1990-2015 decade, analyze and characterize the topics and trends in technology and identify challenges for the evolution of the area in the near future. In our project, we will review the title, the abstract, and the keywords of the papers that are published in NIPS and identify the technological topics involved in these research works and will try to provide a classification of these papers in trending technological perspectives and obtain the timeline of these topics in order to determine interest growths and declines. The techniques used here to handle large amount of data, can also be applied to other text datasets as well.

Keyphrases: Bag of Words, LDA, NIPS, Natural Language Processing

@booklet{EasyChair:2050,
  author    = {Akshay Lunawat and Shreyas Sawai and Sairaj Nanaware and Jhanvi Bhatia and Swapnil Jawahire},
  title     = {Influencing Trends for Neural Information Processing Systems},
  howpublished = {EasyChair Preprint 2050},
  year      = {EasyChair, 2019}}