Multilingual resume ranking API based on NLP and contextual word embeddings
Manas Ranjan Kar (~manasRK) |
How can we create a resume ranking engine based purely on job descriptions on job boards? Can I create recommendations purely based on the skillset & job role? How do I use natural language processing techniques to create valid recommendations of related skillsets? For example, how can I recommend “AngularJS” to an HTML developer who wants to prop up his CV? The other challenge lies in dealing with multilingualism - from English & Dutch job boards?
How do we account for the proper skillsets and build it in our ranking systems? The talk will answer these questions and showcase effectiveness of such a resume ranking engine.
The participants must be well versed with Python and have a basic understanding of natural language processing.
Slides to be posted soon.
Since this was a commercial project for a Dutch client I worked for earlier, no codes would be shared.
Manas likes helping clients making sense of their data and build a powerful case for business change using analytics in their respective companies. He is currently heading the NLP team at Episource, a US healthcare company.
He has architected multiple commercial NLP solutions in the area of healthcare, foods & beverages, finance and retail. He is deeply involved in functionally architecting large scale business process automation & deep insights from structured & unstructured data using Natural Language Processing & Machine Learning. He has contributed to Gensim & ConceptNet as well.
To sum up his experience, he has worked on;
- Application of machine learning to build text analytics solutions
- Automate business processes for efficiency & productivity
- Build algorithms for extracting multiple facets from text - gender of author, keywords, sentiment, taxonomies, concepts, entities
- Combine and augment unstructured insights with structured data
- Build recommendation engine for automated medical coding services
- Build models to predict taxonomies for textual content
- Create machine learning algorithms for topic detection & sentiments
- Competitive intelligence algorithms to monitor events & trends for startups & SMEs
- Pycon 2016 Selected Talk: https://in.pycon.org/cfp/2016/proposals/creating-a-recommendation-engine-based-on-nlp-and-contextual-word-embeddings~aOZGe/ LinkedIn : https://in.linkedin.com/in/manasranjankar
- Contribution to Gensim (PR #625): https://github.com/RaRe-Technologies/gensim/blob/develop/gensim/scripts/glove2word2vec.py
- Blog: http://unlocktext.com/
- Related Blog Article: http://unlocktext.com/index.php/2015/12/14/using-glove-vectors-in-gensim/
- Context oriented NLP: https://www.linkedin.com/pulse/context-extraction-better-sentiment-analysis-manas-ranjan-kar?trk=prof-post
- Analysing product reviews for context cues: http://www.datasciencecentral.com/profiles/blogs/impactful-text-analytics-for-smarter-businesses