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Reinforcement learning, Active learning, Contextual Bandit, NLP, NER, Sentiment Analysis, Counter factual Evaluation, Travel Industry, Unit tests, Serverless Functions, Language Understanding, Azure Cosmos DB, Serverless Functions, Azure Personalizer,
Remove constraint Keyword: Reinforcement learning, Active learning, Contextual Bandit, NLP, NER, Sentiment Analysis, Counter factual Evaluation, Travel Industry, Unit tests, Serverless Functions, Language Understanding, Azure Cosmos DB, Serverless Functions, Azure Personalizer,
Publisher
Data Science Masters Theses
Remove constraint Publisher: Data Science Masters Theses
Resource type
Dissertation
Remove constraint Resource type: Dissertation
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Description:
The challenges of using inadequate online recruitment systems can be addressed with
machine learning and software engineering techniques. Bi-directional personalization
reinforcement learning-based architecture with active learning can get recruiters to recommend
qualified applicants and also enable applicants to receive personalized job recommendations.
This paper focuses on how machine learning...
Keyword:
Reinforcement learning, Active learning, Contextual Bandit, NLP, NER, Sentiment Analysis, Counter factual Evaluation, Travel Industry, Unit tests, Serverless Functions, Language Understanding, Azure Cosmos DB, Serverless Functions, Azure Personalizer,
Subject:
Natural language processing (Computer science) , Artificial intelligence , Sentiment analysis , Reinforcement learning , and Machine learning
Creator:
Ezana N. Beyenne
Owner:
Ezana Negga Beyenne
Publisher:
Data Science Masters Theses
Date Uploaded:
03/15/2023
Date Modified:
03/15/2023
Resource Type:
Dissertation and Masters Thesis