Syllable-based reading improvement: Effects on word reading and reading comprehension in Grade 2     

《Learning and Instruction》2020

This study examined the effects of a syllable-based reading intervention for German second graders who demonstrated difficulties in the recognition of written words. The intervention focused on fostering word reading via syllable segmentation. The materials consisted of the 500 most frequent syllables typically read by 6- to 8-year-old children. The aims were to practice phonological recoding, consolidate orthographic representations of syllables, and routinize the access to these representations. Compared to children randomly assigned to a wait-list group, poor readers in the treatment condition showed significant improvements in standardized measures of phonological recoding, direct word recognition, and text-based reading comprehension after the 24-session intervention. Poor readers in the treatment condition also showed greater improvements in development of word recognition compared to children with efficient word recognition skills. The results provide evidence that a syllable-based reading intervention is a promising approach to increase struggling readers’ word recognition skills, which in turn will improve their reading comprehension.  相似文献   

海洋类中文科技期刊发展思考——以《海洋科学进展》为例     

李燕  胡筱敏  陈靖  王燕 《中国科技期刊研究》2018,29(1):79-83

【目的】 分析《海洋科学进展》和《海洋学报》的高被引论文，为《海洋科学进展》的发展和创新提供参考。【方法】 通过中国知网检索《海洋科学进展》和《海洋学报》的高被引论文，从被引频次、下载次数、论文类型、学科分布及第一作者等信息分析了两刊优势学科、高被引论文类型，并对两刊被引频次及下载次数进行相关性分析。【结果】 对两刊近10年被引频次排名前20论文的下载次数和被引频次进行了相关性分析，发现其相关系数均大于0.5；对两刊在网络盛行前后各5年被引频次排名前50论文的被引频次及下载次数进行相关性分析，发现网络发展使得其相关性均有下降趋势。【结论】 网络发展加剧了期刊间的竞争，期刊的数字化建设不容忽视。在日趋平等、便利的网络平台上，准确的期刊定位和具有原创性观点的高质量论文仍是科技期刊发展的根本。  相似文献   

基于核心论文数量和被引频次双重分布的百分位数指标改进研究     

汪莉 《中国科技期刊研究》2018,29(4):400-405

【目的】 改进现有百分位数指标在揭示期刊载文量特征方面的不足，构建基于被引频次与载文量双重分布的期刊评价指标PRC。【方法】 以2016版《期刊引证报告》生物学学科的85种期刊为研究样本，通过二八定律筛选核心论文样本集，利用布拉德福区域分析法设计基于文献密度分布的载文量权重，利用百分位数建立基于被引频次分布的引文指标，构建期刊综合影响力评价指标PRC。比较PRC与其他文献计量指标的相关性，验证指标评价效果。【结果】 PRC不仅在一定程度上克服了影响因子的内在缺陷，也能合理揭示期刊的出版规模效应，很好地均衡了相对值和绝对值两类指标，改进了百分位数指标的评价效果。【结论】 PRC指标兼顾被引频次和载文量双重分布，从数量和质量两个维度衡量期刊影响力，可用于评价科技期刊的学术影响力。  相似文献   

Local word vectors guiding keyphrase extraction     

Eirini Papagiannopoulou  Grigorios Tsoumakas 《Information processing & management》2018,54(6):888-902

Automated keyphrase extraction is a fundamental textual information processing task concerned with the selection of representative phrases from a document that summarize its content. This work presents a novel unsupervised method for keyphrase extraction, whose main innovation is the use of local word embeddings (in particular GloVe vectors), i.e., embeddings trained from the single document under consideration. We argue that such local representation of words and keyphrases are able to accurately capture their semantics in the context of the document they are part of, and therefore can help in improving keyphrase extraction quality. Empirical results offer evidence that indeed local representations lead to better keyphrase extraction results compared to both embeddings trained on very large third corpora or larger corpora consisting of several documents of the same scientific field and to other state-of-the-art unsupervised keyphrase extraction methods.  相似文献   

专利被引频次的时间影响研究     

罗文馨  赵亚娟 《图书情报工作》2019,63(9):47-60

[目的/意义]研究时间因素对专利被引频次的影响,可以减少时间因素对技术评价活动的制约,提高评价的准确性和可信度。[方法/过程]采集1975-2017年的美国专利数据,开展基于固定效应法的专利被引频次的修正研究。将专利按照不同公开年份和不同技术领域分组,选定组内均值和6个TOP分位数为被引频次基准,统计当前时间点的被引频次基准线及基准线的历史时序变化情况。建立神经网络模型,拟合基准线的时序变化规律,并预测未来统计时间点的基准线。[结果/结论]专利公开年份和统计年份的时间差异,使得专利被引频次无法直接进行比较。本文建立了基于不同技术领域、不同公开年份和不同统计年份的专利被引频次基准线,为专利评估提供参考。  相似文献   

基于深度学习的中文专利自动分类方法研究   总被引：2，自引：0，他引：2  

吕璐成  韩涛  周健  赵亚娟 《图书情报工作》2020,64(10):75-85

[目的/意义] 面向当前国内专利审查和专利情报分析工作中对于海量专利分类的客观需求，设计了7种基于深度学习的专利自动分类方法，对比各种方法的分类效果，从而助力专利分类效率和效果的提升。[方法/过程] 针对传统机器学习方法存在的缺陷，基于Word2Vec、CNN、RNN、Attention机制等深度学习技术，考虑专利文本语序特征、上下文特征以及分类关键特征，设计Word2Vec+TextCNN、Word2Vec+GRU、Word2Vec+BiGRU、Word2Vec+BiGRU+TextCNN等7种深度学习模型，以中国专利为例，选取IPC主分类号的"部"作为分类依据，对比这7种模型与3种传统分类模型在中文专利分类任务中的效果。[结果/结论] 实证研究效果显示，采用考虑语序特征、上下文特征及强化关键特征的深度学习方法进行中文专利分类具有更优的分类效果。  相似文献   

Executive functioning and word reading in Hong Kong Chinese children: A 1-year longitudinal perspective     

Wing Kai Fung  Kevin Kien Hoa Chung  Chun Bun Lam 《Journal of Research in Reading》2020,43(3):382-393

This study examined the bidirectionality between kindergarten children's executive functioning (EF) and word reading across two time points. Participants were 523 Hong Kong Chinese-speaking children (mean age at Time 2 = 64.59 months; 52.9% male) and their parents. At Time 1, children were administered the measures of EF skills: inhibitory control, attention shifting, working memory and Chinese word reading. They were reassessed with these measures at Time 2 one year later. Results from the cross-lagged panel model revealed that, controlling for child age, gender and parental education levels, children's word reading at Time 1 was significantly predictive of their working memory at Time 2, but that the three EF skills at Time 1 were not predictive of word reading at Time 2. These findings underscored the role of early word reading in promoting children's working memory.  相似文献   

动态助词“来”的历时发展及其衰落动因考察     

《信阳师范学院学报(哲学社会科学版)》2021,(5):124-130

古代汉语中,"来"的用法异常复杂,仅其助词属性下就又可以细分出六七种不同的用法,但这些用法大多并未能沿用到现代汉语共同语中,这也包括用作动态助词的"来"。从历时发展来看,动态助词"来"产生之后,在唐五代、宋元、明清三个阶段的使用并未呈现出持续上升的态势,而是在共同语中逐渐衰落了,今天仅在偏南方的一些方言中还有所使用。作为动态助词,"来"的衰落动因是多方面的,既有"来"自身功能负担过重,以及在使用中受限制过多的内因作用,也有系统内部成员竞争的外因作用。  相似文献   

Predicting the early growth of word and nonword reading fluency in a consistent syllabic orthography     

Tomohiro Inoue  George K. Georgiou  Naoko Muroya  Miyuki Hosokawa  Hisao Maekawa  Rauno Parrila 《Journal of Research in Reading》2020,43(3):364-381

  相似文献   

Word sense disambiguation based on context selection using knowledge-based word similarity     

Sunjae Kwon  Dongsuk Oh  Youngjoong Ko 《Information processing & management》2021,58(4):102551

In this paper, we introduce a novel knowledge-based word-sense disambiguation (WSD) system. In particular, the main goal of our research is to find an effective way to filter out unnecessary information by using word similarity. For this, we adopt two methods in our WSD system. First, we propose a novel encoding method for word vector representation by considering the graphical semantic relationships from the lexical knowledge bases, and the word vector representation is utilized to determine the word similarity in our WSD system. Second, we present an effective method for extracting the contextual words from a text for analyzing an ambiguous word based on word similarity. The results demonstrate that the suggested methods significantly enhance the baseline WSD performance in all corpora. In particular, the performance on nouns is similar to those of the state-of-the-art knowledge-based WSD models, and the performance on verbs surpasses that of the existing knowledge-based WSD models.  相似文献