… [Limitations] We examined more mainstream methods for keyword extraction. [Conclusions]
This paper summarizes the developing trends of keyword extraction methods, as well as the …

… a digital format, text written on a document or manuscript, and text typed on a document or text
image. This attention … [13] have suggested a hybrid SMS classification system for detecting …

… item embeddings is to express the item document as a fixed-length … Embedding Creator
module which uses item descriptions (concatenated with title) to create item embeddings based …

… 1: Embedding层通过使用Word2vec模型获得doc的词向量矩阵V … Text classification
using label names only: A language model self-training ap⁃ proach[J]. arXiv preprint arXiv, …

… a new method to explore consumer psychology and their preferences based on online
comments, aiming to address the difficulties of drawing personality-based consumer portraits. […

… information of the document, and the important statistical features of words are not fully
utilized in deep learning methods, a keyphrase extraction algorithm based on global and local …

… After manually screening and extending citation search based on seed documents, a
total of 58 articles were retrieved, which included 30 papers directly discussing incremental …

… Whereas previous pure linguistic and pure geographic approaches were not successful,
our data-mining method integrates methods of GIS and Computational Linguistics and shows …

… do appear in sentiment texts on the Internet, we may often encounter incorrect correlations
between words if we apply the single-view transfer learning methods. This problem would …

… Semantic expansion using word embedding clustering and convolutional neural network
for improving short text classification. Neurocomputing, 2016, 174: 806-814. [17] Zhao M, Li H, …