Although a large number of studies have focused on various aspects of politeness,very little is known about how politeness intention is activated cognitively during verbal communication.The present study aims to explo...Although a large number of studies have focused on various aspects of politeness,very little is known about how politeness intention is activated cognitively during verbal communication.The present study aims to explore the cognitive mechanism of politeness intention processing,and how it is related to pragmatic failure during cross-cultural communication.Using 30 Chinese EFL university students who were instructed to finish a probe word judgment task with 96 virtual scenarios,the results indicate that within both mono-and cross-cultural contexts,the response time in the experimental scenarios was significantly slower than that of the filler scenarios.This suggests that politeness intention was activated while understanding the surface meaning of the conversation;however,the EFL learners could not completely avoid the negative transfer of their native politeness conventions when they were comprehending the conversational intention of the target language.Furthermore,no significant differences in response time were found between the groups with high and low English pragmatic competence,illustrating that transferring the pragmatic rules and principles into cross-cultural communication skills was more cognitively demanding.Overall,this study adds to the literature on politeness research and provides some implications for foreign language pragmatic instructions.展开更多
A two-phase monadic approach is presented for monadically slicing programs with procedures. In the monadic slice algorithm for interprocedural programs, phase 1 initializes the slice table of formal parameters in a pr...A two-phase monadic approach is presented for monadically slicing programs with procedures. In the monadic slice algorithm for interprocedural programs, phase 1 initializes the slice table of formal parameters in a procedure with the given labels, and then captures the callees＇ influence on callers when analyzing call statements. Phase 2 captures the callees＇ dependence on callers by replacing all given labels appearing in the corresponding sets of formal parameters. By the introduction of given labels, this slice method can obtain similar summary information in system-dependence-graph（SDG）-based algorithms for addressing the calling-context problem. With the use of the slice monad transformer, this monadic slicing approach achieves a high level of modularity and flexibility. It shows that the monadic interprocedural algorithm has less complexity and it is not less precise than SDG algorithms.展开更多
Recently clustering techniques have been used to automatically discover typical user profiles. In general, it is a challenging problem to design effective similarity measure between the session vectors which are usual...Recently clustering techniques have been used to automatically discover typical user profiles. In general, it is a challenging problem to design effective similarity measure between the session vectors which are usually high-dimensional and sparse. Two approaches for mining typical user profiles, based on matrix dimensionality reduction, are presented. In these approaches, non-negative matrix factorization is applied to reduce dimensionality of the session-URL matrix, and the projecting vectors of the user-session vectors are clustered into typical user-session profiles using the spherical k -means algorithm. The results show that two algorithms are successful in mining many typical user profiles in the user sessions.展开更多
文摘Although a large number of studies have focused on various aspects of politeness,very little is known about how politeness intention is activated cognitively during verbal communication.The present study aims to explore the cognitive mechanism of politeness intention processing,and how it is related to pragmatic failure during cross-cultural communication.Using 30 Chinese EFL university students who were instructed to finish a probe word judgment task with 96 virtual scenarios,the results indicate that within both mono-and cross-cultural contexts,the response time in the experimental scenarios was significantly slower than that of the filler scenarios.This suggests that politeness intention was activated while understanding the surface meaning of the conversation;however,the EFL learners could not completely avoid the negative transfer of their native politeness conventions when they were comprehending the conversational intention of the target language.Furthermore,no significant differences in response time were found between the groups with high and low English pragmatic competence,illustrating that transferring the pragmatic rules and principles into cross-cultural communication skills was more cognitively demanding.Overall,this study adds to the literature on politeness research and provides some implications for foreign language pragmatic instructions.
基金The National Outstanding Young Scientist Foundation by NSFC(No.60703086,60503020)
文摘A two-phase monadic approach is presented for monadically slicing programs with procedures. In the monadic slice algorithm for interprocedural programs, phase 1 initializes the slice table of formal parameters in a procedure with the given labels, and then captures the callees＇ influence on callers when analyzing call statements. Phase 2 captures the callees＇ dependence on callers by replacing all given labels appearing in the corresponding sets of formal parameters. By the introduction of given labels, this slice method can obtain similar summary information in system-dependence-graph（SDG）-based algorithms for addressing the calling-context problem. With the use of the slice monad transformer, this monadic slicing approach achieves a high level of modularity and flexibility. It shows that the monadic interprocedural algorithm has less complexity and it is not less precise than SDG algorithms.
文摘Recently clustering techniques have been used to automatically discover typical user profiles. In general, it is a challenging problem to design effective similarity measure between the session vectors which are usually high-dimensional and sparse. Two approaches for mining typical user profiles, based on matrix dimensionality reduction, are presented. In these approaches, non-negative matrix factorization is applied to reduce dimensionality of the session-URL matrix, and the projecting vectors of the user-session vectors are clustered into typical user-session profiles using the spherical k -means algorithm. The results show that two algorithms are successful in mining many typical user profiles in the user sessions.
