Doc2Vec Algorithm
(Redirected from doc2vec)
Jump to navigation
Jump to search
A Doc2Vec Algorithm is a document embedding algorithm that ...
- See: Word2Vec.
References
2016
- (Lauan & Baldwin, 2016) ⇒ Jey H. Lauan, and Timothy Baldwin. (2016). “An Empirical Evaluation of Doc2vec with Practical Insights Into Document Embedding Generation.” In: Proceedings of the 1st Workshop on Representation Learning for NLP, pp. 78-86.
- QUOTE: Recently, Le and Mikolov (2014) proposed doc2vec as an extension to word2vec (Mikolov et al., 2013a) to learn document-level embeddings. Despite promising results in the original paper, others have struggled to reproduce those results. This paper presents a rigorous empirical evaluation of doc2vec over two tasks. We compare doc2vec to two baselines and two state-of-the-art document embedding methodologies. We found that doc2vec performs robustly when using models trained on large external corpora, and can be further improved by using pre-trained word embeddings. We also provide recommendations on hyper-parameter settings for general purpose applications, and release source code to induce document embeddings using our trained doc2vec models.