Wednesday, May 6, 2020

Natural Language Processing And Machine Learning Techniques

The manuscript at hand presents a framework that implements Natural language processing (NLP) and machine learning techniques to extract synthesis parameters of metal oxides from a large set of published articles. The manuscript also presents insights into the key synthesis parameters using machine learning algorithms. NLP technique is of broad and current interest in many research areas and it is being extensively used to extract information on a large scale, which is otherwise not feasible via manual exploration. In the field of chemistry/materials, NLP holds immense promise to extract useful information the literature, such as extraction of materials properties, processes, and various synthesis details. However, NLP has not been†¦show more content†¦I believe the current manuscript holds the merit to be published in a high-quality journal, and my recommendation is to accept the manuscript to be published in Chemistry of Materials. The authors may want to address the following list of minor issues to further improve the manuscript: 1. Logistic regression classifier is applied to distinguish paragraphs that are related to synthesis from other non-synthesis related paragraphs. Applying logistic regression to classify the paragraphs is an elegant way to determine the synthesis details, however, it might have errors in the classification (95% accuracy in the current manuscript). A simpler way to classify would be to search for section titles like ‘Methods’, ‘Materials’, ‘Methods and materials’, etc., and then classify the text in this section as synthesis paragraphs. It will be worth considering this approach and comparing it with the logistic regression approach. However, the former technique might not work if the search paper is a review article. 2. From the description presented in the manuscript, it appears that the data is extracted from the paragraphs. However, there are articles where the information is presented in the form of tables/figures. A discussion on the scope of data extraction from tables/figures would be of significant interest to the chemistry community as large amount of chemical/materials data is published in this format. 3. It would be helpful to have an explanation of theShow MoreRelated Artificial Intelligence and Investing Essay1648 Words   |  7 Pagesintelligence. The techniques of this intelligence include knowledge-based, machine learning, and natural language processing techniques. Investing can be defined as the act of committing money to an endeavour with the exception of obtaining profit. Investing activities require data identification, asset valuation (the process of determining the worth of something), and risk management (the process of managing the uncertainty in investment decision-making). 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