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社会化标注体现了Web2.0时代的集体智慧,隐含了丰富的语义信息。本文分析了社会化标注的认知过程,探讨了社会化标注的浮出语义,提出了一种社会化标注的语义聚类算法。从语义的角度对社会化标注进行分析,有助于理解和挖掘社会化标注的隐含语义,指导平面化的自由分类法进行本体构建,丰富语义网资源。 相似文献
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在Web2.0环境下,社会化标注的出现给网络舆情分析提供了新的视角。首先对当前的网络舆论环境进行了分析,在此基础上,着重对舆情参与者个人、关键舆情参与者识别以及舆情参与者的社区划分三个方面进行了重点剖析,并给出了相应的思路与实施方法,最后给出了社会化标注环境下舆情控制的相关建议。 相似文献
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[目的/意义]在社会化标注系统自组织运行的基础上，构建个性化信息推荐的多维度融合与优化模型，进而在大数据环境下，为用户提供精准的个性化信息推荐服务，从而进一步丰富个性化信息推荐的理论体系以及拓展个性化信息推荐的研究方法。[方法/过程]首先，对每一种个性化信息推荐方法的优点和不足进行深入分析；然后，将基于图论（社会网络关系）、基于协同过滤以及基于内容（主题）3种个性化信息推荐方法进行多维度深度融合，构建个性化信息推荐多维度融合模型；最后，对社会化标注系统中个性化信息推荐多维度融合模型进行优化，从而解决个性化推荐过程中用户"冷启动"、数据稀疏性和用户偏好漂移等问题。[结果/结论]通过综合考虑现有的基于图论（社会网络关系）、基于协同过滤以及基于内容（主题）的个性化信息推荐方法各自的贡献和不足，实现3种方法之间的多维度深度融合，并结合心理认知、用户情境以及时间、空间等优化因素，最终构建出社会化标注系统中个性化信息推荐多维度融合与优化模型。 相似文献
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本文利用SOM神经网络的自组织特征,对delicious网站的典型标签族进行分类,从而识别社会化标注系统中标签的语义维度,为信息用户对标签的使用提供语义方面的参考。 相似文献
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本文阐述了网络标注所具有的时代性、技术性及社会性等文化属性,同时阐述了网络标注在文化传承、文化融合及信息管理方面的文化功能。 相似文献
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随着我国专利申请量、授权量的增加,生产的专利产品将越来越多,对专利产品进行相关专利信息的标注也会越来越普遍。尽管国家知识产权局2012年5月份公布了新的《专利标识标注办法》(以下简称新《标注办法》),但是在实际执行过程中还会存在操作上的实际问题,例如,专利许可、专利权利转移的过程中专利标识的标注问题等。本文拟结合新《标注办法》以及现有法律、法规、规章,分析我国专利标识制度目前存在的问题,及提出相应的建议。 相似文献
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信息扩散是社会化网络的重要特征之一,信息扩散模型和扩散最大化是信息扩散研究中的两个基本问题。分析了信息扩散的两类基本模型:级联模型和门槛模型,并基于选择性注意理论,提出了一种改进的扩散模型。"影响力个体或意见领袖"的挖掘是信息扩散最大化研究的核心问题,从不同角度分析了信息节点重要性的衡量方法,并提出了社会化标注网络中标签用户影响力的NRCS计算模型。 相似文献
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《Information processing & management》2016,52(1):139-162
In this paper, we focus on applying sentiment analysis to resources from online art collections, by exploiting, as information source, tags intended as textual traces that visitors leave to comment artworks on social platforms. We present a framework where methods and tools from a set of disciplines, ranging from Semantic and Social Web to Natural Language Processing, provide us the building blocks for creating a semantic social space to organize artworks according to an ontology of emotions. The ontology is inspired by the Plutchik’s circumplex model, a well-founded psychological model of human emotions. Users can be involved in the creation of the emotional space, through a graphical interactive interface. The development of such semantic space enables new ways of accessing and exploring art collections.The affective categorization model and the emotion detection output are encoded into W3C ontology languages. This gives us the twofold advantage to enable tractable reasoning on detected emotions and related artworks, and to foster the interoperability and integration of tools developed in the Semantic Web and Linked Data community. The proposal has been evaluated against a real-word case study, a dataset of tagged multimedia artworks from the ArsMeteo Italian online collection, and validated through a user study. 相似文献
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David Y. Hu 《Information processing & management》1983,19(5):285-293
The utilization of computers for bibliographic control, information database management and other library operations in Taiwan was revealed at the ASIS-82 Special Symposium on Computer Processing of Chinese Library Materials and Computer Assisted Chinese Language Instruction, held on 19 October 1982, in Columbus, Ohio. Based on this Symposium, the paper briefs the most remarkable progress in library automation and information systems made in the Republic of China during the last two years. 相似文献
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网络环境下文献信息的数字化对文学研究中作家作品论带来冲击；作家作品论在资料准备阶段面临新的选择与机遇；图书馆创新服务模式，开拓学科馆员服务将是推动二者良性互动的有效举措。 相似文献
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随着Web2.0的逐步发展, 海量用户生成的图像信息充斥于各大网络平台, 图像自动标注技术逐步成为图像检索以及图像理解的关键问题之一。该文主要通过对现有图像自动标注方法的文献进行收集和整理, 在比较、分析各种方法相关理论和实现技术的基础上, 对图像自动标注方法研究进展进行评述;并归纳了各种方法的优势与不足。得出结论:图像自动标注方法和图像处理技术仍然需要从机器学习方面进一步的研究与改进, 且可以从图像信息的标注拓展到视频信息的标注。 相似文献
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Rong Qu Yongyi Fang Wen Bai Yuncheng Jiang 《Information processing & management》2018,54(6):1002-1021
Computing Semantic Similarity (SS) between concepts is one of the most critical issues in many domains such as Natural Language Processing and Artificial Intelligence. Over the years, several SS measurement methods have been proposed by exploiting different knowledge resources. Wikipedia provides a large domain-independent encyclopedic repository and a semantic network for computing SS between concepts. Traditional feature-based measures rely on linear combinations of different properties with two main limitations, the insufficient information and the loss of semantic information. In this paper, we propose several hybrid SS measurement approaches by using the Information Content (IC) and features of concepts, which avoid the limitations introduced above. Considering integrating discrete properties into one component, we present two models of semantic representation, called CORM and CARM. Then, we compute SS based on these models and take the IC of categories as a supplement of SS measurement. The evaluation, based on several widely used benchmarks and a benchmark developed by ourselves, sustains the intuitions with respect to human judgments. In summary, our approaches are more efficient in determining SS between concepts and have a better human correlation than previous methods such as Word2Vec and NASARI. 相似文献
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摘要：社会网络作为影响市场机遇信息搜索的重要因素之一,在研究和实际中得到了越来越多的关注。本文结合社会网络理论对企业市场机遇信息搜索社会网络(ESNSMOI)进行研究,以提高企业的市场机遇信息搜索能力。首先分析了ESNSMOI的特性,接着提出四种类型的ESNSMOI,并对其功能和结构进行了分析和比较,最后通过案例分析对某银行的ESNSMOI进行了进一步讨论。 相似文献
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随着21世纪互联网的发展及计算机网络在初、高等教育中的普及,社交网络在中国各大高校发展得如火如荼。社交网络渐渐地融入了高校大学生的日常生活,潜移默化地影响着大学生的思想活动、道德行为、心理健康及学习态度等。作为影响大学生思想教育新载体的社交网络应该受到各大高校教育者对于大学生思想教育工作方面的重视。社交网络产生的影响不仅促进大学生与同群体及外界的交流,也可能因其信息传播的不当而对产生负面影响。因而,高校教育者面对既是机遇,又是挑战的思想教育新形式的社交网络,必须顺应信息时代的发展,剔除社交网络对大学生思想教育的不利因素,从而开辟大学生思想教育新天地,积极地对其进行疏导和科学的指引。 相似文献
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The advent of the participatory Web and social network applications has changed our communication behaviour and the way we express ourselves on the Web. Social network application providers benefit from the increasing amount of personally identifiable information willingly displayed on their sites but, at the same time, risks of data misuse threaten the information privacy of individual users as well as the providers’ business model. From recent research, this paper reports the major requirements for developing privacy-preserving social network applications and proposes a privacy threat model that can be used to enhance the information privacy in data or social network portability initiatives by determining the issues at stake related to the processing of personally identifiable information. 相似文献
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《Information processing & management》2022,59(1):102740
One of the most time-critical challenges for the Natural Language Processing (NLP) community is to combat the spread of fake news and misinformation. Existing approaches for misinformation detection use neural network models, statistical methods, linguistic traits, fact-checking strategies, etc. However, the menace of fake news seems to grow more vigorous with the advent of humongous and unusually creative language models. Relevant literature reveals that one major characteristic of the virality of fake news is the presence of an element of surprise in the story, which attracts immediate attention and invokes strong emotional stimulus in the reader. In this work, we leverage this idea and propose textual novelty detection and emotion prediction as the two tasks relating to automatic misinformation detection. We re-purpose textual entailment for novelty detection and use the models trained on large-scale datasets of entailment and emotion to classify fake information. Our results correlate with the idea as we achieve state-of-the-art (SOTA) performance (7.92%, 1.54%, 17.31% and 8.13% improvement in terms of accuracy) on four large-scale misinformation datasets. We hope that our current probe will motivate the community to explore further research on misinformation detection along this line. The source code is available at the GitHub.2 相似文献