Introduction Text similarity is a fundamental task in the industrialization of NLP. Many applications require calculating the degree of similarity between two texts, including deduplication of similar texts in text retrieval, matching queries with standard template questions in question-answering systems, and semantic judgment of sentence pairs. This task can be categorized based on different criteria: … Read more
Source: Deephub Imba This article is approximately 800 words long and is recommended to be read in 5 minutes. This article mainly introduces <strong>Word2Vec</strong> and <strong>Doc2Vec</strong>. Doc2Vec is an unsupervised algorithm that learns embeddings from variable-length text segments (such as sentences, paragraphs, and documents). It first appeared in the paper Distributed Representations of Sentences and … Read more
Source: Poll’s Notes Original URL:http://www.cnblogs.com/maybe2030/ Reading Directory 1. Word Vectors 2. Distributed Representation of Word Vectors 3. Word Vector Models 4. Word2Vec Algorithm Concepts 5. Doc2Vec Algorithm Concepts 6. References Deep learning has opened a new chapter in machine learning, and significant breakthroughs have been made in applying deep learning to images and speech. Deep … Read more