In this paper, we aim to organize a collection of papers into journal categories which describe research areas of a field, and then analyze the trend of each ...
In [16] an extension of ParagraphVector is proposed with the aim of modeling the hierarchical data structure and be able to capture its associated semantic as a ...
Paragraph Vector: A distributed memory model. Our approach for learning paragraph vectors is inspired by the methods for learning the word vectors. The ...
Pengfei Liu, King Keung Wu, and Helen M. Meng. 2017. A Model of Extended Paragraph Vector for Document Categorization and Trend Analysis. IJCNN. Yinhan Liu, ...
May 20, 2020 · Pengfei Liu, King Keung Wu, and Helen M. Meng. 2017. A Model of Extended Paragraph Vector for Document Categorization and Trend Analysis. IJCNN.
A model of extended paragraph vector for document categorization and trend analysis. Conference Paper. May 2017. Pengfei Liu · King Keung Wu ...
In this paper, we propose Paragraph Vector, an unsupervised algorithm that learns fixed-length feature representations from variable-length pieces of texts.
Jan 22, 2020 · In this study, we propose Paragraph Vector Topic Model (PVTM) and apply it to technology-related news articles to analyze innovation-related topics over time.
Our model progressively builds a document vector by aggregating important words into sentence vectors and then aggregating important sentences vectors to ...
A 'Document Vector' in Computer Science refers to a representation of a document where each word is considered an attribute and each row is a separate document.
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