A representation learning method is considered stable if it consistently generates similar
representation of the given data across multiple runs. Word Embedding Methods (WEMs) …

Pre-trained word embedding models are easily distributed and applied, as they alleviate
users from the effort to train models themselves. With widely distributed models, it is …

Early detection of emerging research trends could potentially revolutionise the way research
is done. For this reason, trend analysis has become an area of paramount importance in …

In the recent years, the interest to knowledge extraction in the architecture, engineering and
construction (AEC) domain has grown dramatically. Along with the advances in the AEC …

摘要在科技文献情报分析领域, 词汇语义分析至关重要. 分布式词嵌入技术可以有效学习词汇的
语义表示, 近年来逐渐成为科技词汇语义分析的共性基础技术. 然而, 主流词嵌入模型的随机 …

Objective The goal of this work is to reduce the amount of manual work required to go from
data capture to regulatory submission. It will be shown that the use of Siamese networks will …

The study of the dynamics or the progress of science has been widely explored with
descriptive and statistical analyses. Also this study has attracted several computational …

This article proposes a comprehensive strategy for training, evaluating, and optimizing
domain-specific word2vec-based word embeddings, using social science literature as an …

因為能夠反應社會上的價值觀, 再加上其性別化的訊息, 還有新聞性的本質, 流行雜誌時常是性別
研究的研究對象. 先前的研究表明, 詞嵌入模型能夠揭示媒體中性別之間的微妙偏見 …

Research in analysis of big scholarly data has increased in the recent past and it aims to
understand research dynamics and forecast research trends. The ultimate objective in this …