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61.
张文娟 《四川教育学院学报》2008,24(9):48-49
尼采的“上帝之死”是指只有否定了上帝的价值和意义,才能独立于世界,意味着一种伦理主体的死亡,是一种道德形象的人之死;福柯的“人之死”是指“人”这一概念将失去意义,意味着一种知识主体的死亡,是一种概念的人之死;罗兰·巴尔特的“作者之死”是指作者的主宰地位被读者所取代,读者获得了自由,文本获得了独立,进而人们可以对文本世界进行可写性阅读。顺乎这一逻辑,现代人又提出了“读者之死”,主要是指具体读者的消失和视觉文化时代的“读者死了”。 相似文献
62.
周国清 《湖南城市学院学报》2011,32(5)
出版产业化环境下编辑决策要牢固树立作者意识,这是由作者及其文稿在编辑活动中的重要位置与独特作用决定的。它要求编辑主体树立与作者平等相处的理念;深入研究和准确把握作者心理;善于、敢于、巧于接受来自作者的挑战;具有善待作者的慧眼与能耐。 相似文献
63.
新世纪以来,随着客家研究理论和方法的创新,客家研究取得了巨大的发展。期刊论文是科研成果的主要呈现方式之一,通过论文年度发表数量、论文的期刊分布、作者分布、作者单位分布、高频关键词、文献被引次数6个方面对2000-2010年客家研究论文进行分析,可以了解目前客家研究的状况:总体发展势头良好、建立了较好的科研成果发表平台、拥有了一批高素质学者队伍、形成了一些较好的学术团队、研究内容丰富、科研成果学术价值还需进一步提升。 相似文献
64.
黄滔 《四川教育学院学报》2011,(10):92-95
对学生演讲稿的写作过程及成稿文本研究和分析表明,学生演讲中存在清晰的隐含作者。由于演讲是一种公共传播行为,学生演讲中的隐含作者与媒体叙事中的隐含作者较为相似,表现为更优秀、更强大的“第二自我”和文本所体现的、同时也是环境和社会意识形态所要求的价值观和道德观这两个层次。真实作者(学生)与隐含作者的互动、互融过程,就是学生进步、提高的过程。在演讲教学中正确运用隐含作者的作用,将对学生成长产生深远的积极作用。 相似文献
65.
The aim of this study was to investigate videos as potential triggers of behavior. Therefore, we applied the theories of triggers and media richness to learn about the triggering efficiency of mobile marketing videos on participants’ behavioral intentions. The experiment involved three distinct test groups, each comprising 41 student participants. From the perspective of media richness theory, we observed that the different kinds of videos had quite similar effects in terms of triggering behavioral changes. However, the mechanisms explaining why triggers were present differed for each video. Further, the results reveal that the consumer's position in the information search process was the most significant reason for the triggering of any kind of effect. In addition, the instructionally designed videos were able to exert an affective triggering effect: the more participants liked the video, the more it affected their participation intention and recall scores. This study extends the media richness research by demonstrating that the effects of media richness can vary within technically similar videos, as they form different logical connections among non-verbal visual cues related to a video's storyline. 相似文献
66.
Kai Hu Qing Luo Kunlun Qi Siluo Yang Jin Mao Xiaokang Fu Jie Zheng Huayi Wu Ya Guo Qibing Zhu 《Information processing & management》2019,56(4):1185-1203
Topic evolution has been described by many approaches from a macro level to a detail level, by extracting topic dynamics from text in literature and other media types. However, why the evolution happens is less studied. In this paper, we focus on whether and how the keyword semantics can invoke or affect the topic evolution. We assume that the semantic relatedness among the keywords can affect topic popularity during literature surveying and citing process, thus invoking evolution. However, the assumption is needed to be confirmed in an approach that fully considers the semantic interactions among topics. Traditional topic evolution analyses in scientometric domains cannot provide such support because of using limited semantic meanings. To address this problem, we apply the Google Word2Vec, a deep learning language model, to enhance the keywords with more complete semantic information. We further develop the semantic space as an urban geographic space. We analyze the topic evolution geographically using the measures of spatial autocorrelation, as if keywords are the changing lands in an evolving city. The keyword citations (keyword citation counts one when the paper containing this keyword obtains a citation) are used as an indicator of keyword popularity. Using the bibliographical datasets of the geographical natural hazard field, experimental results demonstrate that in some local areas, the popularity of keywords is affecting that of the surrounding keywords. However, there are no significant impacts on the evolution of all keywords. The spatial autocorrelation analysis identifies the interaction patterns (including High-High leading, High-Low suppressing) among the keywords in local areas. This approach can be regarded as an analyzing framework borrowed from geospatial modeling. Moreover, the prediction results in local areas are demonstrated to be more accurate if considering the spatial autocorrelations. 相似文献
67.
68.
Human collaborative relationship inference is a meaningful task for online social networks and is called link prediction in network science. Real-world networks contain multiple types of interacting components and can be modeled naturally as heterogeneous information networks (HINs). The current link prediction algorithms in HINs fail to effectively extract training samples from snapshots of HINs; moreover, they underutilise the differences between nodes and between meta-paths. Therefore, we propose a meta-circuit machine (MCM) that can learn and fuse node and meta-path features efficiently, and we use these features to inference the collaborative relationships in question-and-answer and bibliographic networks. We first utilise meta-circuit random walks to obtain training samples in which the basic idea is to perform biased meta-path random walks on the input and target network successively and then connect them. Then, a meta-circuit recurrent neural network (mcRNN) is designed for link prediction, which represents each node and meta-path by a dense vector and leverages an RNN to fuse the features of node sequences. Experiments on two real-world networks demonstrate the effectiveness of our framework. This study promotes the investigation of potential evolutionary mechanisms for collaborative relationships and offers practical guidance for designing more effective recommendation systems for online social networks. 相似文献
69.
Jamal Abdul Nasir Iraklis Varlamis Samreen Ishfaq 《Information processing & management》2019,56(5):1605-1617
Searching for relevant material that satisfies the information need of a user, within a large document collection is a critical activity for web search engines. Query Expansion techniques are widely used by search engines for the disambiguation of user’s information need and for improving the information retrieval (IR) performance. Knowledge-based, corpus-based and relevance feedback, are the main QE techniques, that employ different approaches for expanding the user query with synonyms of the search terms (word synonymy) in order to bring more relevant documents and for filtering documents that contain search terms but with a different meaning (also known as word polysemy problem) than the user intended. This work, surveys existing query expansion techniques, highlights their strengths and limitations and introduces a new method that combines the power of knowledge-based or corpus-based techniques with that of relevance feedback. Experimental evaluation on three information retrieval benchmark datasets shows that the application of knowledge or corpus-based query expansion techniques on the results of the relevance feedback step improves the information retrieval performance, with knowledge-based techniques providing significantly better results than their simple relevance feedback alternatives in all sets. 相似文献
70.
黄勤 《金陵科技学院学报(社会科学版)》2015,(2)
通过对2005—2014年图书情报学4刊论文著者的统计,对合著率、著者发文规律、高产著者年龄、地区及单位分布进行分析,并归纳国内图书情报学的发展规律。 相似文献