In the present study, we examined the relation of knowledge of semantic radicals to students’ language proficiency and word reading for adult Chinese-as-a-foreign language students. Ninety-seven college students rated their proficiency in speaking, listening, reading, and writing in Chinese, and were administered measures of receptive and productive knowledge of semantic radical position and fu...

The aim of this study is to determine the effect of word clustering method on vocabulary learning of Iranian EFL learners through a case of semantic versus phonological clustering. To this effect, 80 homogeneous students from four intermediate classes at an English institute in Torbat e Heydariyeh participated in this research. They were assigned to four groups according to semantic versus phon...

This work concerns non-parametric approaches for statistical learning applied to the standard knowledge representations languages adopted in the Semantic Web context. We present methods based on epistemic inference that are able to elicit and exploit the semantic similarity of individuals in OWL knowledge bases. Specifically, a totally semantic and language independent semi-distance function is...

Analyzing land cover using remote sensing images has broad prospects, the precise segmentation of is key to application this technology. Nowadays, Convolution Neural Network (CNN) widely used in many image semantic tasks. However, existing CNN models often exhibit poor generalization ability and low accuracy when dealing with To solve problem, paper proposes Dual Function Feature Aggregation (D...

UNLABELLED Finding gene functions discussed in the literature is an important task of information extraction (IE) from biomedical documents. Automated computational methodologies can significantly reduce the need for manual curation and improve quality of other related IE systems. We propose an open-IE method for the BioCreative IV GO shared task (subtask b), focused on finding gene function te...