江苏体彩7位数201遗漏

基于循环神经网络和注意力模型的文本情感分析 作者： 胡荣磊 1 芮璐 1 齐筱 1 张昕然 1 作者单位： 1. 北京电子科技学院 电子与通信工程系 提交时间： 2018-08-13 摘要: 文本情感分析是自然语言处理领域的一大分支，其发展不仅在自然语言处理领域有重大的影响，更是在政治、经济、社会科学等受人们主观观点影响较大的领域有着深远的影响。深度学习在文本情感分析中的作用越来越重要。将循环神经网络中的长短期记忆网络和前馈注意力模型相结合，提出一种文本情感分析方案。在基本长短期记忆网络中加入前馈注意力模型，并在Tensorflow深度学习框架下对方案进行了实现。根据准确率、召回率和F1测度等衡量指标，与现有的方案对比表明，提出的方案较传统的机器学习方法和单纯的长短期记忆网络的方法有明显的优势。 Abstract: Sentiment analysis is a big branch in the field of natural language processing. The development of text sentiment analysis not only has a great influence in the field of natural language processing, but also has a profound influence in the fields of politics, economy and social sciences which are influenced by people's subjective view. The role of deep learning in text sentiment analysis is becoming more and more important. A text sentiment analysis scheme was proposed based on Long Short-Term Memory(LSTM) networks and feedforward attention model. It adopts feedforward attention model in basic Long Short-Term Memory networks. The scheme was implemented under the framework of Tensorflow depth learning. According to the parameters of precision, recall and F1 measures, the scheme was compared with the existing scheme. The results show that the model proposed in this paper has improved significantly compared with the traditional machine learning method and the traditional Long Short-Term Memory networks. 文本情感分析 深度学习 长短期记忆模型 注意力模型 期刊： 计算机应用研究 分类： 计算机科学 >> 计算机科学的集成理论 引用： ChinaXiv:201808.00087 (或此版本 ChinaXiv:201808.00087V1 ) doi:10.12074/201808.00087 CSTR:32003.36.ChinaXiv.201808.00087.V1 推荐引用方式： 胡荣磊,芮璐,齐筱,张昕然.(2018).基于循环神经网络和注意力模型的文本情感分析.计算机应用研究.[ChinaXiv:201808.00087] 版本历史 [V1] 2018-08-13 09:26:14 ChinaXiv:201808.00087V1 下载全文

全民觉醒：我隐藏了空间系是(周五夜来风雨)新书,这是一个现代人回到古代，回到一个完全没有任何超凡的真实世界，靠着将一切数据属性化的异能，慢慢崛起的故事。 精彩尽在全民觉醒：我隐藏了空间系

他从兜里掏出一包《大型智能化无人蔬菜工厂》给张小强上烟，张小强就着何文斌的打火机点了烟，深吸一口气，吐着烟圈对何文斌说道：“几天没见了，忙啥呢？

团宠+万人迷】九幽剑尊时雾死了。但是她又活了。她穿越到了五百年后，一身的修为也没了。此时她的五个徒弟都成了大佬。老大接手她的宗门，老二成了药王谷谷主，老三杀回魔界，老四统一妖族，小五上位仙盟盟主。但不幸的是他们都因她的离去而黑化成了反派。没错，这是一个小说世界。在她死去多年后，女主出现，凭借和她相似的容貌救赎了她的徒弟们。她前四个男徒弟纷纷爱上女主，小五成了女主的闺蜜。五个人

新书《剑修本源》已发叶家傻女一朝重生！坐拥万能神鼎，身怀灵植空间，她不再是人见人欺的废材弃女！药毒无双，神医也要靠边站；灵兽求契约，不好意思，兽神都喊咱老大；渣爹，敢抛妻弃女，她就让他家破人亡；世人，敢欺她辱她，她必百倍还之；再世为人，她王者归来,岂料惹上了邪魅嗜血的他。他明明是杀伐决断的鬼帝，却化身呆萌无害的敌国质子……

职场网络不文明行为：现实与虚拟的溢出和反溢出机制 作者： 严瑜 1 衷敬红 1 作者单位： 1. 武汉大学哲学学院心理学系, 武汉 430072 提交时间： 2023-03-28 摘要: 以往研究主要关注职场不文明行为的面对面形式, 发现了其在工作领域和家庭领域间的溢出和交叉效应。但近来研究指出, 职场不文明行为的虚拟形式有其特殊之处, 并具有更加恶劣的影响后果。在综述已有的网络不文明行为研究基础之上, 引入社会临场感的概念, 总结了职场不文明行为在现实工作领域和虚拟工作领域之间的溢出与反溢出机制; 并基于此提出多个研究展望, 建议未来研究以此为出发点, 考察职场网络不文明行为的不同演变模式。 Abstract: Previous research on workplace incivility has primarily focused on those occurring face-to-face, and demonstrated that it has spillover and crossover effects between the work domain and family domain. However, recent studies suggested that workplace cyber incivility, the virtual form of workplace incivility, has its own unique features and has worse consequences. Based on the review of existing literature on workplace cyber incivility, we introduce the concept of social presence, and summarize potential spillover and anti-spillover mechanisms between the reality and the virtual world for workplace incivility. In addition, we propose several research propositions, and encourage future research to uses these propositions to examine different forms of workplace cyber incivility. 网络不文明行为 溢出效应 反溢出效应 社会临场感 期刊： 心理科学进展 分类： 心理学 >> 发展心理学 引用： ChinaXiv:202303.09246 (或此版本 ChinaXiv:202303.09246V1 ) DOI:10.3724/SP.J.1042.2018.02204 CSTR:32003.36.ChinaXiv.202303.09246.V1 推荐引用方式： 严瑜,衷敬红.(2023).职场网络不文明行为：现实与虚拟的溢出和反溢出机制.心理科学进展.doi:10.3724/SP.J.1042.2018.02204 版本历史 [V1] 2023-03-28 00:30:26 ChinaXiv:202303.09246V1 下载全文

我国科研诚信政策变迁计量分析 Quantitative Analysis of the Changes of Research Integrity Policy in China 作者： 冯凌子 1,2 刘敬 3,4 袁军鹏 1,2 作者单位： 1. 1 中国科学院文献情报中心 北京 100190 2. 2 中国科学院大学经济与管理学院图书情报与档案管理系 北京 100190 3. 3 中国科学院信息工程研究所 北京 100093 4. 4 中国科学院大学网络空间安全学院 北京 100049 提交时间： 2023-04-01 摘要: [目的/意义] 对我国中央发布的科研诚信政策和地方响应情况的现状及变迁作了分析，以求把握政策发展态势与阶段重点，为科研诚信建设提供支撑，为我国科研诚信政策发展研究提供帮助。[方法/过程] 搜集整理108份与科研诚信相关的中央政策及80份参照落实中央政策的地方政策，使用政策文本计算与政策文献量化方法，对政策发布时间、发布机构、政策内容及政策响应情况的现状及其变迁进行分析梳理，得到了政策发布的时间特征、重要机构特征、内容侧重点变化以及政策响应的特征。[结果/结论] ①科研诚信相关治理措施早在1980年就有涉及，近年来围绕国家创新建设的需求发文数量骤增，治理的态度更坚决，措施办法也更加具体。②科研诚信的治理由中央政府领导，教育部与科技部是各个阶段的主要管理部门，相关部门逐渐加入进行共同治理，目前已形成合力的格局。③各部门的科研诚信治理着力点、对象与方法略有差异，但总体而言，从方法与目标上来看，逐渐从自我约束、道德教育转变到制度建设与道德建设齐抓共管。④全国范围内绝大多数的地方省市都积极响应了中央政策，采取措施进行科研诚信治理，但相对而言有一定的时滞。 Abstract: [Purpose/significance] This paper analyses the current situation and changes of the research integrity policy issued by the Chinese central government and the local response, in order to grasp the development trend and stage focus of the policy, provide support for the construction of research integrity, and provide help for the development of research integrity policy in China. [Method/process] This paper collected 108 policies related to research integrity issued by the central government and ministries, and 80 local policies for the implementation of the central policy. By using the policy text computing and policy documents quantitative research method, this paper analyzed and combed the current situation and changes of policy release time, publishing institutions, policy content and policy response, and obtained the time characteristics of policy release. Finally, this paper got the characteristics of the time of policy release, the characteristics of important institutions, the change of content focus and the characteristics of policy response. [Result/conclusion] ①Relevant governance measures of research integrity have been involved earlier. In recent years, China has put forward the need to build an innovative country, so the number of policy papers has increased sharply, the attitude to the governance of research integrity is more resolute, and the measures are more specific. ②The management of scientific research integrity is led by the central government. The Ministry of Education and the Ministry of Science and Technology are the main administrative departments at all stages. Relevant departments have gradually joined in the joint management. At present, a pattern of joint efforts has been formed. ③There are slight differences in the focus, object and method of research integrity governance among different departments, but generally speaking, the trend is to gradually shift from self-restraint, moral education to system construction and moral construction. ④The vast majority of local provinces and municipalities throughout the country have responded positively to the central policy and taken measures to improve scientific research integrity, but there is a relative time lag. 科研诚信 政策文本计算 政策文献量化 政策变迁 政策分析 期刊： 图书情报工作 分类： 图书馆学、情报学 >> 情报学 引用： ChinaXiv:202304.00251 (或此版本 ChinaXiv:202304.00251V1 ) doi:10.12074/202304.00251 CSTR:32003.36.ChinaXiv.202304.00251.V1 推荐引用方式： 冯凌子,刘敬,袁军鹏.(2023).我国科研诚信政策变迁计量分析.图书情报工作.[ChinaXiv:202304.00251] 版本历史 [V1] 2023-04-01 16:15:53 ChinaXiv:202304.00251V1 下载全文

基于深度循环神经网络的跨领域文本情感分析 A Cross-domain Text Sentiment Analysis Based on Deep Recurrent Neural Network 作者： 余传明 1 作者单位： 1. 中南财经政法大学信息与安全工程学院 武汉 430073 提交时间： 2023-08-26 摘要: [目的/意义]通过在标注资源丰富的源领域（Source Domain）中学习，并将目标领域（Target Domain）的文档投影到与源领域相同的特征空间（Feature Space）中去，从而解决目标领域因标注数据量较小而难以获得好的分类模型的问题。[方法/过程]选择亚马逊在书籍、DVD和音乐类目下的中文评论作为实验数据，以跨领域情感分析作为研究任务，提出一种跨领域深度循环神经网络（Cross Domain Deep Recurrent Neural Network，CD-DRNN）模型，实现不同领域环境下的知识迁移。CD-DRNN模型在跨领域环境下的平均分类准确度达到了81.70%，优于传统的栈式长短时记忆网络（Stacked Long Short Term Memory，Stacked-LSTM）模型（79.90%）、双向长短时记忆网络模型（Bidirectional Long Short Term Memory，Bi-LSTM）模型（80.50%）、卷积神经网络长短时记忆网络串联（Convolution Neural Network with Long Short Term Memory，CNN-LSTM）（74.70%）模型以及卷积神经网络长短时记忆网络并联（Merged Convolution Neural Network with Long Short Term Memory，Merged-CNN-LSTM）模型（80.90%）。[结果/结论]源领域和目标领域的知识迁移能够有效解决监督学习在小数据集上难以获得好的分类效果的问题，通过CD-DRNN模型能够从无标注数据中有效地筛选特征，从而大大降低目标领域数据标注相关的工作量。 Abstract: [Purpose/significance] In order to solve the problem of classification model in target domain that caused by the lack of data, this study firstly trains the model of source domain that includes rich labeling/tagging data, and then, projects source and target domain documents into the same feature space. [Method/process] The reviews of three product categories, i.e. books, DVD and music, from Amazon, which are written in Chinese, are taken as the experimental data, and the cross-domain text sentiment analysis is considered as the research task. A novel model, i.e. the Cross Domain Deep Recurrent Neural Network (CD-DRNN), is proposed to achieve knowledge transfer among domains. The average accuracy value of CD-DRNN achieves 81.70%,which excels the values of Stacked Long Short Term Memory (79.90%), Bidirectional Long Short Term Memory(80.50%), Convolution Neural Network with Long Short Term Memory (74.70%) and Merged Convolution Neural Network with Long Short Term Memory (80.90%). [Result/conclusion] Knowledge transfer in source domain and target domain could effectively solve the difficulties of achieving good classification performances on small data sets. The proposed method can be leveraged to effectively select features from unlabeled data, thereby greatly reducing the workload related to data annotation in the target domain. 跨领域 迁移学习 深度循环神经网络 情感分析 期刊： 图书情报工作 分类： 图书馆学、情报学 >> 图书馆学 引用： ChinaXiv:202308.00284 (或此版本 ChinaXiv:202308.00284V1 ) doi:10.12074/202308.00284 CSTR:32003.36.ChinaXiv.202308.00284.V1 推荐引用方式： 余传明.(2023).基于深度循环神经网络的跨领域文本情感分析.图书情报工作.[ChinaXiv:202308.00284] 版本历史 [V1] 2023-08-26 23:57:18 ChinaXiv:202308.00284V1 下载全文

我在诡异世界里封神是(卡拉肖克·咕)新书,这是一个现代人回到古代，回到一个完全没有任何超凡的真实世界，靠着将一切数据属性化的异能，慢慢崛起的故事。 精彩尽在我在诡异世界里封神