This is a post that lists pointers to different posts that would help you to develop a thorough understanding of the problem of automatically identifying keyphrases from text documents. My main aim would be to give you a comprehensive overview of this field and take the readers in a tour of what this problem is all about, how researchers have tried to solve this problem using different machine learning approaches over time, the challenges in this area, ideas of future work and how the readers can contribute. Throughout the series I would like to share different resources that are publicly available in order to get started with this area and would also like to share implementations of different machine learning models and use of existing libraries. Parts 1–13 are mostly aimed towards understanding the fundamentals and then the following posts will mostly cover specific topics that needs deeper understanding. Here is a rough outline of what is coming up in the series.
- Part 1 — What is the problem of identifying keyphrases from text documents?
- Part 2 — What are applications of keyphrases that has interested researchers to solve this problem using different machine learning approaches?
- Part 3 — Different approaches taken by the machine learning community to solve the problem of automatically identifying keyphrases from text documents.
- Part 4 — Available datasets in different domains for training the machine learning models for keyphrase identification, existing…
