A research on the shift from primacy effect to recency effect 首因效应向近因效应转换的实验研究
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Primary recency effect 初始与时近效应
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The influence of word frequency , accessibility and list composition on recency effects 易接近性和词表序列成分对近因效应影响的实验研究
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This phenomenon is known as “ recency bias ” , the tendency to be excessively affected by the pattern of recent data 这一现象被认为是“近因效应” （或近期偏差） ，即一种受近期数据模式过度影响的趋势。
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The mistake districts of interpersonal perception that people often meet include vignetteing effect , angular impression , recency effect , projection inclination and logic inference by experience effect , etc 摘要常见的人际知觉的误区主要有晕轮效应、刻板印象、近因效应、投射倾向和经验的逻辑推理效应等。
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Second , proposing a hybrid recommendation strategy which used multi - agent system , collaborative filtering , and top - n together to generate right recommendations for customers in different profitability tiers . in the first part , we have defined customer value from two categories : intrinsic value and network value . based on customer ' s historical behavior , segment them with considering their recency , frequency , and monetary 明确指出高价值客户可体现在两个方面：一是具有高自身价值的客户，二是具有高网络价值（客户的网络影响力）的客户；其次，由顾客的历史和当前行为，特别是从recency （最近访问时间） 、 frequency （访问频度） 、 mon6t8ry （购买投人）因素出发，进行顾客内部价值挖掘：并通过形式化顾客的网络价值，给出完整的分层算法和相应实验。
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The robust serial position effects were founded in the free recall experiment and in the continuous distractor paradigm with chinese character . but in the 30s distractor experiment paradigm , the primacy effect still exited , the recency effect disappeared . and the contextual - retrieval hypothesis failed to explain this phenomenon . according to the contextual cue and memory trace , it is applied successfully that the associative memory and absolute memory to the primacy effect and the recency effect respectively 以汉字为材料，在即时回忆实验中表现出明显的系列位置效应;在30s延迟实验中,表现出明显的首因效应，但近因效应消失在连续分心实验范式中证明长时记忆中存在明显的系列位置效应。说明现有理论存在的问题，并提出联想记忆和绝对记忆的概念，成功地解释首因效应和近因效应性质之差异。
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Elaborate process descriptions of evaluating offers , belief revision and proposing counteroffers are presented , in particular , we analyze the use of bayesian learning and reinforcement learning in negotiation process , restructuring the traditional q - learning into a dynamic q - leaming algorithm by introducing current beliefs and recency exploration bonus 在该谈判模型的基础上引入学习机制，并分别对评估提议、更新信念、生成提议等谈判过具有学习机制的电子商务自动谈判研究摘要程作了详细阐述，重点分析了贝叶斯学习和强化学习技术在自动谈判中的应用。
