基於已知名稱搜尋結果的網路實體辨識模型建立工具(A Tool for Web NER Model Generation Using Search Snippets of Known Entities) [In Chinese]
黃雅筠 Ya-Yun Huang 國立中央大學資訊工程學系 Department of Computer Science and Information Engineering National Central University a2425320032002@gmail.com 張嘉惠 Chia-Hui Chang 國立中央大學資訊工程學系 Department of Computer Science and Information Engineering National Central University chia@csie.ncu.edu.tw 周建龍 Chia-Hui Chang 國立中央大學資訊工程學系 Department of Computer Science and Information Engineering National Central University formatc.chou@gmail.com
Chinese Organization Name Recognition Based on Multiple Features
Recognition of Chinese organization names is the key of the recognition of Chinese named entities. However, the lack of a single unified naming system to capture all types of organizations and the uncertainty in word segmentation, make the recognition of Chinese organization names especially difficult. In this paper, we focus on the recognition of Chinese organization names and propose an approach that takes advantage of various types of features of Chinese organization names to address it. First of all, we pre-process inputs to make the recognition more convenient. Secondly, we use the features of the left and right boundary to determine the candidate Chinese organization names automatically. Thirdly, we evaluate and refine the initial recognition results with the features of behaviors and debugging structure patterns to improve the performance of the recognition. From the experimental results on People's Daily testing data set, the approach proposed in this paper outperforms the method based on role tagging more than 7%. And through designing a series of other experiments, we have proved that the proposed approach can perfectly complete the task of recognizing Chinese organization names and is particularly effective in nested cases.
Sustainable production of toxin free marine microalgae biomass as fish feed in large scale open system in the Qatari desert.
Mass cultivation of microalgae biomass for feed should be cost effective and toxin free. Evaporation loss in Qatar can be as high as 2 cm/d. Hence, production of marine microalgae biomass in Qatar would also require mitigating water loss as there was only very limited groundwater reserve. To address these issues, a combination of four growth conditions were applied to a 25,000 L raceway pond: locally isolated microalgae strain was selected which could grow in elevated salinity; strain that did not require silica and vitamins; volume of the culture would increase over time keeping denser inoculum in the beginning, and evaporation water loss would be balanced by adding seawater only. A local saline tolerant Nannochloropsis sp. was selected which did not require silica and vitamins. When the above conditions were combined in the pond, average areal biomass productivities reached 20.37 g/m(2)/d, and the culture was not contaminated by any toxic microalgae.