Doc2Vec with Gensim

Doc2Vec is a technique for document embedding and text analysis. Doc2Vec can be used to build document retrieval systems, helping users find relevant documents. It can be used in recommendation systems to suggest articles, news, or products to users based on their historical preferences or behavior. It has enabled many real-world applications in a variety of domains. In healthcare, it is used with electronic health records (EHRs) to classify medical documents. In the legal field, it helps to organize and classify legal documents, particularly in e-discovery and case law research. In social media texts, it is used to identify sentiment and user behavior to help companies understand public opinion or identify emerging topics. In academic research, it helps to identify related research papers and explore connections between different studies. Similar applications exist for e-commerce, travel websites, and job-recruiting websites.

With the rise of LLMs that are capable...