Can I read Technological forecasting based on estimation of word embedding matrix using LSTM networks on EtoBox?

Technological forecasting based on estimation of word embedding matrix using LSTM networks by Necip Gozuacik; C. Okan Sakar; Sercan Ozcan is a Business, Management and Accounting article available to read on EtoBox.

What is Technological forecasting based on estimation of word embedding matrix using LSTM networks about?

There are a vast number of quantitative and qualitative technological forecasting methods. In the last decade, advanced quantitative technological forecasting methods based on the various applications of data science approaches have been proposed. Text mining is one of the key approaches used to examine large datasets consisting of scientific publications and patent documents with the aim of offering foresight for a selected area. However, the existing related studies either perform a qualitative approach by analysing the recent data to identify the emerging topics or use extrapolation techniques to predict the future values of some statistical terms or the future frequency of some important keywords. In this study, different from such related studies, we propose a deep learning-based framework to predict future co-similarity matrix representing the possible new and disappearing interactions between the words in the future. For this purpose, word vectors are generated using a word embedding technique and the temporal changes of the associations between the words are modelled using Long Short-Term Memory networks for the future estimation of the word embedding matrix. The text minin

Who reads Technological forecasting based on estimation of word embedding matrix using LSTM networks?

Author

Necip Gozuacik; C. Okan Sakar; Sercan Ozcan

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Business, Management and Accounting (Social Sciences)