Tag: Topic Modeling (TM)
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Identification of topic evolution: network analytics with piecewise linear representation and word embedding
Understanding the evolutionary relationships among scientific topics and learning the evolutionary process of innovations is a crucial issue for strategic decision makers in governments, firms and funding agencies when they carry out forward-looking research activities. However, traditional co-word network analysis on topic identification cannot effectively excavate semantic relationship from the context, and fixed time window…
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Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research
Highlights Data-driven clustering approach to group topics with high accuracy Similarity measure approach to trace the interaction between topics in time series Analyzing changes of TFIDF values of related topics to predict future trends Technology Roadmapping to blend historical analysis and expert-based forecasting The number and extent of current Science, Technology & Innovation topics are…
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Map of science with topic modeling: Comparison of unsupervised learning and human-assigned subject classification
The delineation of coordinates is fundamental for the cartography of science, and accurate and credible classification of scientific knowledge presents a persistent challenge in this regard. We present a map of Finnish science based on unsupervised-learning classification, and discuss the advantages and disadvantages of this approach vis-à-vis those generated by human reasoning. We conclude that…