Experiment on Chinese postgraduates’recognizing 100 Everyday English adopting“MMOASAPMI”

The purpose of this study was to investigate the memory effects of the postgraduates’memorizing Everyday English from 30 to 100 using the Natural Numeral Imagery Memory(Method by memorizing the concrete objects associated with the shapes of Arabic numeral to produce marvelous imagination,MMOASAPMI).The results indicated as follows:Firstly,the postgraduates,who applied the MMOASAPMI to memorize and recall the Everyday English from 30 to 100,could recite them well in sequence backward,forward,and randomly.The reaction time of reciting any sentence randomly is no more than 2 seconds.Secondly,it can transform the materials of the short-term memory into long-term memory quickly,and effectively prevent them from the interference of proactive and retroactive inhibition,so it is useful for keeping memorized information with less loss and remaining for a long period.Thirdly,with the materials in strong sequence,large quantities and the difficulty to memorize,it is an extremely effective method for memorizing them.Fourthly,the keys to improving the memory efficiency are the well-storing skills of memory,storing methods,and memory clues.

Chinese Semantic Parsing Based on Feature Structure with Recursive Directed Graph

It is difficult to analyze semantic relations automatically, especially the semantic relations of Chinese special sentence patterns. In this paper, we apply a novel model feature structure to represent Chinese semantic relations, which is formalized as ＂recursive directed graph＂. We focus on Chinese special sentence patterns, including the complex noun phrase, verb-complement structure, pivotal sentences, serial verb sentence and subject-predicate predicate sentence. Feature structure facilitates a richer Chinese semantic information extraction when compared with dependency structure. The results show that using recursive directed graph is more suitable for extracting Chinese complex semantic relations.