internat_moskva_1954
New Member
| Luận văn: | A hybrid approach to finding phenotype candidates in genetic text = một hướng tiếp cận lai để nhận dạng các ứng viên kiểu hình trong văn bản sinh học. Luận văn ThS. Công nghệ thông tin: 60 48 01 |
| Nhà xuất bản: | ĐHCN |
| Ngày: | 2012 |
| Chủ đề: | Công nghệ thông tin Khoa học máy tính Dữ liệu sinh học |
| Miêu tả: | 48 tr. + CD-ROM Luận văn ThS. Khoa học máy tính -- Trường Đại học Công nghệ. Đại học Quốc gia Hà Nội, 2012 Named entity recognition (NER) has been extensively studied for the names of genes and gene products but there are few proposed solutions for phenotypes. Phe-notype terms are expected to play a key role in inferring gene function in complex heritable diseases but are intrinsically difficult to analyse due to their complex se-mantics and scale. In contrast to previous approaches we evaluate state-of-the-art techniques involving the fusion of machine learning on a rich feature set with evi-dence from extant domain knowledge-sources. The techniques are validated on two gold standard collections including a novel annotated collection of 112 abstracts de-rived from a systematic search of the Online Mendelian Inheritance of Man database for auto-immune diseases. Encouragingly the hybrid model outperforms a HMM, a CRF and a pure knowledge-based method to achieve an F1 of 75.37 for BF and micro average F1 of 84.01 for the whole system Electronic Resources |
| Kiểu: | text |
| Định dạng: | text/pdf |
You must be registered for see links
You must be registered for see links