منابع مشابه
Word2vec: What and Why
Words have been studied for decades as the basic unit in natural language. Although words are traditionally modeled as atomic units, a real-valued representation can wield power in many application domains. The state-of-the-art in such real-valued representations is word2vec, known for its efficiency in handling large datasets and its ability to capture multiple degrees of similarities. In this...
متن کاملword2vec Parameter Learning Explained
The word2vec model and application by Mikolov et al. have attracted a great amount of attention in recent two years. The vector representations of words learned by word2vec models have been shown to carry semantic meanings and are useful in various NLP tasks. As an increasing number of researchers would like to experiment with word2vec or similar techniques, I notice that there lacks a material...
متن کاملI-31: The Scientific Underpinning of ART in Unexplained Infertility
Although intra uterine insemination (IUI) and in vitro fertilization (IVF) are widely accepted treatments among doctors and patients and practiced on large scale, it is good to realize that they have rarely been evaluated properly in randomized clinical trials or even in comparative cohort studies. Although the first pregnancy after IUI was established in 1884, it was not until 2008 that the fi...
متن کاملLinking GloVe with word2vec
The Global Vectors for word representation (GloVe), introduced by Jeffrey Pennington et al. [3] is reported to be an efficient and effective method for learning vector representations of words. State-of-the-art performance is also provided by skip-gram with negative-sampling (SGNS) [2] implemented in the word2vec tool. In this note, we explain the similarities between the training objectives of...
متن کاملEfficient Parallel Learning of Word2Vec
Since its introduction, Word2Vec and its variants are widely used to learn semantics-preserving representations of words or entities in an embedding space, which can be used to produce state-of-art results for various Natural Language Processing tasks. Existing implementations aim to learn efficiently by running multiple threads in parallel while operating on a single model in shared memory, ig...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Frontiers in Applied Mathematics and Statistics
سال: 2020
ISSN: 2297-4687
DOI: 10.3389/fams.2020.593406