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
Semantic Role Labeling for Opinion Target Extraction from Chinese Social Network
Social network is a good resource to collect public opinions considering the diversity and variety in fashion, especially user generated content (UGC). Extracting the opinions from UGC can be the base of commercial policy, so how to extract the opinions correctly is an important problem. However, there are two problems: Are the opinions really talking about the target entities? Or the amount of opinions is enough for network volume analysis? In this study, we combine rule-based method and Semantic Role Labeling (SRL) to detect the opinion target (OTD) from UGC. In SRL task, we design a neural network model to extract the opinion words. Considering gradient vanish problem, we use highway connection to control the percentage of data. To improve the performance of SRL, we use additional features to help model learn the features between verb and other phrases. Finally, we design a rule to filter the result of SRL for OTD task. The experimental results show that our SRL model obtains 71% F1, and our method on OTD task obtains 73% precision which outperforms LTP. This research can be the basis of hot topic prediction for sponsors and helps them to decide marketing strategies
Experimental investigation of the geotechnical properties and microstructure of lime-stabilized saline soils under freeze-thaw cycling
Abstract The Song-Nen Plain in northeastern China holds one of the three largest expanses of soda saline-alkali soil in the world. Due to its disadvantageous geotechnical properties, the saline soil in this area is unable to meet the needs of construction projects. This study evaluates the stabilizing effect of adding lime to such soils. Specifically, it investigates how the physicochemical and mechanical properties and microstructure of soda saline-alkali soil are altered by lime and how these changes are affected by both freeze-thaw cycling and the duration of curing. The results reveal that adding lime to saline soil transforms clay particles into sand and silt particles and causes the pore size distribution (PSD) to become bimodal, with small-pore and macropore populations. An increase in lime content leads to an increase in the unconfined compressive strength (UCS) but a gradual decrease in both the cation exchange capacity (CEC) and plastic index. Freeze-thaw cycles break up coarse particles and aggregate finer particles, increasing the diameter of macropores and decreasing the USC; however, the effect on specimens with >9% lime is negligible. It is further shown that the geotechnical properties of the soil change immediately after the addition of lime, indicating that the cation exchange reaction takes place very quickly. Furthermore, the pozzolanic reaction leads to an increase in the percentage of sand-sized particles and a decrease in porosity after 28 days of curing. Overall, these results indicate that it is feasible to use lime to improve the engineering properties of soda saline-alkali soil in this area.