1 Introduction This article mainly introduces a very classic algorithm in word embedding, Word2Vec. Initially, Word2Vec was primarily used in text-related problems, but now friends participating in competitions should have noticed that almost half of the traditional data competitions involve Word2Vec. Therefore, we must take a good look at what Word2Vec is actually learning, so … Read more
Follow the public account “ML_NLP“ Set as “Starred“, heavy content delivered to you first! Source | Zhihu Address | https://www.zhihu.com/question/44832436/answer/266068967 Author | crystalajj Editor | Machine Learning Algorithms and Natural Language Processing Public Account This article is for academic sharing only. If there is an infringement, please contact the background for deletion. Introduction How does … Read more
Machine Heart Column Author: Principal Engineer Dong Bingfeng, Chubao AI Lab The input vector X in traditional CRF is generally in the one-hot format of words, which loses a lot of semantic information about words. With the advent of word embedding methods, the word representation in vector form generally performs better than the one-hot representation. … Read more
Summary of Word2vec Reference Materials Let me briefly describe my deep dive into Word2vec: I first looked at Mikolov’s two original papers on Word2vec, but found myself still confused after reading them. The main reason is that these papers omit too much theoretical background and derivation details. I then revisited Bengio’s 2003 JMLR paper and … Read more
Baidu NLP Column Author: Baidu NLP 1. Introduction Text matching is an important foundational problem in natural language processing. Many tasks in natural language processing can be abstracted as text matching tasks. For example, web search can be abstracted as a relevance matching problem between web pages and user search queries, automatic question answering can … Read more