[EDITOR’S NOTE: This is a guest post by Xinyi Duan, Director of Technology and Data Research at Liberty Shared.]
Liberty Shared is committed to ensuring that the experiences of vulnerable and exploited workers around the world is represented in our markets, legal systems, and information infrastructures. To do this, we have to take on the daunting task of wrangling some of the messiest data that have been previously un-mined and unstructured.
MeaningCloud has enabled us to quickly and effectively deploy NLP techniques to tackle these problems, and it works easily for team members who are using NLP statistical models already to those without that technical background. It is also powerful enough to grow with our programs. As we learn more about the problem, it is easy to update the models to reflect our learnings.
We have so far found topic extraction and text classification models incredibly useful for easy and customizable text mining for low hanging fruits and we anticipate making use of the more advanced semantic models as our text corpora become more robust. It is by far the most flexible, user-friendly, and robust NLP platform that we tested. Integrating MeaningCloud has accelerated our learning process enormously. We have already seen it paid dividends for various data analysis projects without much additional manual effort. The MeaningCloud support team is also phenomenal. It is now one of our top tools to recommend for our partners in the public sector and civil society who also work on difficult data problems with limited resources.
[Liberty Shared is a Hong Kong registered charitable organization under Share (Asia Pacific) Limited, founded in 2011. You can contact them at firstname.lastname@example.org.]