Book
Opportunities and challenges of text mining in aterials research
| Identifier | --olgakonono-511 |
|---|---|
| Penulis / Pengarang | Olga Kononova, Tanjin He, Haoyan Huo, Amalie Trewartha, Elsa A. Olivetti and Gerbrand Ceder |
| Kata Kunci | aterials research |
| Tanggal Publikasi | 09 Aug 2018 |
| Bahasa | Bahasa Indonesia |
| Abstrak / Deskripsi | Research publications are the major repository of scientiï¬Âc knowledge. However, their unstructured and highly heterogenous format creates a signiï¬Âcant obstacle to large-scale analysis of the information contained within. Recent progress in natural language processing (NLP) has provided a variety of tools for high-quality information extraction from unstructured text. These tools are primarily trained on non-technical text and struggle to produce accurate results when applied to scientiï¬Âc text, involving speciï¬Âc technical terminology. During the last years, signiï¬Âcant efforts in information retrieval have been made for biomedical and biochemical publications. For materials science, text mining (TM) methodology is still at the dawn of its development. In this review, we survey the recent progress in creating and applying TM and NLP approaches to materials science ï¬Âeld. This review is directed at the broad class of researchers aiming to learn the fundamentals of TM as applied to the materials science publications. |
Attached Files / Download (1)
| No | Nama Berkas | Format | Ukuran | Aksi |
|---|---|---|---|---|
| 1 | 1-s2.0-S2589004221001231-main.pdf | application/pdf | 3,1 MB | ⬇️ Buka / Download |
Comments & Discussion (0)
Belum ada komentar untuk koleksi ini. Jadilah yang pertama berdiskusi!