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1.
本文通过对课文教学模式的转变,提高学生学习的积极性、增强培养学生的交际能力和创新能力.  相似文献   
2.
数据挖掘在数字图书馆中的应用   总被引:15,自引:0,他引:15  
在描述数据挖掘技术与方法基础之上,探讨了数据挖掘在数字图书馆中的应用空间以及其所具有的巨大应用价值。  相似文献   
3.
在技术时代,公共图书馆作为实体空间的"场所"价值,是关乎图书馆未来发展的重要内容。从公众认知角度探索图书馆"场所"价值,能够发现影响图书馆事业发展的重要因素。经过全面梳理和系统分析,选择上海图书馆、浦东图书馆和滨海新区图书馆三所代表性公共图书馆在公共平台上的网络评论信息,综合运用Python、Jieba分词、SnowNLP等数据采集与分析工具,从高频词分布、情感分析和时间序列三个维度,对社会公众认知情况进行了文本挖掘。分析结果表明,公共图书馆仍然是重要的公共阅读"场所";公共图书馆"场所"服务颇受欢迎,社会评价极为正面;促进文旅融合发展,是当前社会公众对公共图书馆"场所"价值认知的特征所在。在技术时代,公共图书馆应当高度重视"场所"价值的公众认知新变化,可以将文旅融合作为未来发展阶段的重要内容,助力公共图书馆高质量发展。  相似文献   
4.
基于统计频率的文本分类特征选择算法研究*   总被引:1,自引:0,他引:1  
通过分析χ2统计量(Chi-square, CHI)的缺陷和不足,针对它对低文档频的特征项不可靠,而且不能说明词条和类别的相关性的缺点,对其进行改进,提出统计频率(Statistical Frequency, SF )算法。实验结果表明,统计频率算法能够弥补这些不足,在文本分类中表现出良好的分类效果。  相似文献   
5.
Two-stage statistical language models for text database selection   总被引:2,自引:0,他引:2  
As the number and diversity of distributed Web databases on the Internet exponentially increase, it is difficult for user to know which databases are appropriate to search. Given database language models that describe the content of each database, database selection services can provide assistance in locating databases relevant to the information needs of users. In this paper, we propose a database selection approach based on statistical language modeling. The basic idea behind the approach is that, for databases that are categorized into a topic hierarchy, individual language models are estimated at different search stages, and then the databases are ranked by the similarity to the query according to the estimated language model. Two-stage smoothed language models are presented to circumvent inaccuracy due to word sparseness. Experimental results demonstrate that such a language modeling approach is competitive with current state-of-the-art database selection approaches.  相似文献   
6.
基于机器学习的自动文本分类模型研究   总被引:2,自引:0,他引:2  
基于机器学习的方法是自动文本分类中非常重要的一大类方法。本文先给出了形式化的定义,提出了自动文本分类的流程模型,然后选取了支持向量机(Support Vector Machine,SVM)算法作为一个典型例子进行分析,最后作者通过一个中文文本分类实验评价了该算法的效果。  相似文献   
7.
This research analyzed a dataset of academic libraries' posts on Facebook. It applied a text and data analytics approach to a dataset collected from the Facebook posts of academic libraries at the top 100 English-speaking universities, as listed by the 2014 Shanghai World University Rankings. The dataset is from a two-year posting history of 18,333 unique posts, 113,621 likes, and 3401 comments. Less than a quarter of the libraries had more than 2000 post-related likes, and only seven received more than 100 comments on their postings. Content analysis identified the most prevalent single word (unigrams), bigrams (two-word sequences), and trigrams (three-word sequences) in high and low engagement content. Semantic analysis identified the semantic categories for posts with high and low engagement. The findings can assist academic libraries in their social media strategies for engagement, marketing, and visibility.  相似文献   
8.
Scientific research is increasingly relying on collaborations to address complex real-world problems. Many researchers, policymakers, and administrators consider a multidisciplinary environment an important factor for fostering research collaborations, especially interdisciplinary ones that involve researchers from different disciplines. However, it remains unknown whether a higher level of multidisciplinarity within an academic institution is associated with internal collaborations that are more prevalent and more interdisciplinary. Analyzing 90,000 publications by 2500 faculty members in over 100 academic institutions from three multidisciplinary areas, information, public policy, and neuroscience, we investigated the connection between multidisciplinarity and research collaborations. Based on social network analysis and text mining, our analysis suggests that more multidisciplinary institutions are not necessarily more collaborative, although they do feature collaborations that are more interdisciplinary. Our findings provide implications for academic administrators and policymakers to promote research collaborations and interdisciplinarity in academic institutions.  相似文献   
9.
Handwriter identification aims to simplify the task of forensic experts by providing them with semi-automated tools in order to enable them to narrow down the search to determine the final identification of an unknown handwritten sample. An identification algorithm aims to produce a list of predicted writers of the unknown handwritten sample ranked in terms of confidence measure metrics for use by the forensic expert will make the final decision.Most existing handwriter identification systems use either statistical or model-based approaches. To further improve the performances this paper proposes to deploy a combination of both approaches using Oriented Basic Image features and the concept of graphemes codebook. To reduce the resulting high dimensionality of the feature vector a Kernel Principal Component Analysis has been used. To gauge the effectiveness of the proposed method a performance analysis, using IAM dataset for English handwriting and ICFHR 2012 dataset for Arabic handwriting, has been carried out. The results obtained achieved an accuracy of 96% thus demonstrating its superiority when compared against similar techniques.  相似文献   
10.
Automatic Chinese text summarization for dialogue style is a relatively new research area. In this paper, Latent Semantic Analysis (LSA) is first used to extract semantic knowledge from a given document, all question paragraphs are identified, an automatic text segmentation approach analogous to Text'filing is exploited to improve the precision of correlating question paragraphs and answer paragraphs, and finally some "important" sentences are extracted from the generic content and the question-answer pairs to generate a complete summary. Experimental results showed that our approach is highly efficient and improves significantly the coherence of the summary while not compromising informativeness.  相似文献   
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