信息时代的社店互动

从出版社的实际出发,通过考察和系统分析,设计出一套具有出版社市场经营特色的社店互动信息化解决方案。通过本方案,出版社能够借助信息化手段高效地进行新书入库、客户管理、订单管理等工作。     

互动问答搜索及其对图书馆网络咨询的启示

论文介绍了互动问答搜索产生的背景和发展的状况，并通过网上调查和非介入式测试对国内三家网站提供的互动问答搜索服务的功能和质量进行了测试和评价，分析了其特色以及面临的问题，最后探讨了互动问答搜索给目前以CVRS为代表的图书馆网上参考咨询带来的某些启示。     

Self-training on refined clause patterns for relation extraction

Within the context of Information Extraction (IE), relation extraction is oriented towards identifying a variety of relation phrases and their arguments in arbitrary sentences. In this paper, we present a clause-based framework for information extraction in textual documents. Our framework focuses on two important challenges in information extraction: 1) Open Information Extraction and (OIE), and 2) Relation Extraction (RE). In the plethora of research that focus on the use of syntactic and dependency parsing for the purposes of detecting relations, there has been increasing evidence of incoherent and uninformative extractions. The extracted relations may even be erroneous at times and fail to provide a meaningful interpretation. In our work, we use the English clause structure and clause types in an effort to generate propositions that can be deemed as extractable relations. Moreover, we propose refinements to the grammatical structure of syntactic and dependency parsing that help reduce the number of incoherent and uninformative extractions from clauses. In our experiments both in the open information extraction and relation extraction domains, we carefully evaluate our system on various benchmark datasets and compare the performance of our work against existing state-of-the-art information extraction systems. Our work shows improved performance compared to the state-of-the-art techniques.     

Using semantic similarity to reduce wrong labels in distant supervision for relation extraction

Distant supervision (DS) has the advantage of automatically generating large amounts of labelled training data and has been widely used for relation extraction. However, there are usually many wrong labels in the automatically labelled data in distant supervision (Riedel, Yao, & McCallum, 2010). This paper presents a novel method to reduce the wrong labels. The proposed method uses the semantic Jaccard with word embedding to measure the semantic similarity between the relation phrase in the knowledge base and the dependency phrases between two entities in a sentence to filter the wrong labels. In the process of reducing wrong labels, the semantic Jaccard algorithm selects a core dependency phrase to represent the candidate relation in a sentence, which can capture features for relation classification and avoid the negative impact from irrelevant term sequences that previous neural network models of relation extraction often suffer. In the process of relation classification, the core dependency phrases are also used as the input of a convolutional neural network (CNN) for relation classification. The experimental results show that compared with the methods using original DS data, the methods using filtered DS data performed much better in relation extraction. It indicates that the semantic similarity based method is effective in reducing wrong labels. The relation extraction performance of the CNN model using the core dependency phrases as input is the best of all, which indicates that using the core dependency phrases as input of CNN is enough to capture the features for relation classification and could avoid negative impact from irrelevant terms.     

Engagement as Co-Generative Theorizing

To meet current and ever shifting problems people continually need new and better ways to attend to, talk about, and respond in the world. All communities can have an impoverished language for talking about human interaction and making decisions in times of fundamental and rapid change. Three current impoverishments are discussed. Engaged scholarship using co-generative theorizing can initiate productive conversations enriching the languages of both scholarly and everyday life communities.     

Parental Self-efficacy and Sensitivity During Playtime Interactions with Young Children: Unpacking the Curvilinear Association

Although scholars and service providers typically assume that parental self-efficacy (PSE) facilitates sensitive parenting, this study finds that the association between PSE and observer ratings of parents' sensitivity during free play actually is curvilinear. Parents (33 mothers, 5 fathers) from an intergenerational learning program serving low-income families completed the Self-Efficacy for Parenting Tasks Index and were videotaped during a 15-minute play period with their infant/toddler at program entry. Parents' self-reported PSE is positively, albeit weakly, associated with observer ratings of parental sensitivity from low to moderate levels of self-efficacy but inversely associated with sensitivity from moderate to high self-efficacy. Qualitative analyses show that mothers who report high PSE but are rated as low in sensitivity introduce toys when their child is already engaged, restrict their child's access to toys, physically manipulate their child, and violate their child's proximal space. Parenting education programs need to develop strategies for reaching parents who enter with high levels of confidence but lack knowledge of competent parenting practices.     

赣州市中小企业劳动关系问题研究——基于雇主的视角

本文在专家访谈和问卷调查的基础上,以赣州市中小企业雇主的劳动关系自我认知为研究视角,对赣州市中小企业劳动关系的现状进行了实证分析,得出影响赣州市中小企业劳动关系的主要因素,期望为促进赣州市中小企业劳资双方的和谐共生发展提供借鉴。     

海森堡模型中的量子纠缠

量子纠缠是量子信息处理的重要资源,海森堡模型是一种简单的能够在固态系统中实现的模型,研究海森堡模型中的纠缠将极大地推动固态量子计算机的发展。本文简单介绍了海森堡模型,外磁场和Dzyaloshinskii-Moriya（DM）相互作用参量对系统纠缠的影响,以及现阶段的研究进展。此外,文章还进一步提出了在该领域的研究中需要解决的一些问题。     

提问交互模型（QICT）教学应用方法的实践研究

提问交互模型（QICT）是异步在线交流环境中促进学生批判性思维的有效工具,其教学应用方法结合了脚手架的思想和异步在线交流的特点．将整个批判性思维的教学过程分为预备、教师引导、学习伙伴引导和自我引导四个阶段。研究结合“传播学”课程教学．以课程网站的论坛为异步在线交流平台,运用实验研究法、问誊调查法和内容分析法对QICT模型的教学应用方法进行了实践研究。研究发现．QICT模型的教学应用方法对学生批判性思维具有促进作用．证明该方法对批判性思维教学具有积极影响。同时还发现,教师引导阶段对后续学习伙伴引导阶段和自我引导阶段起到良好的示范作用．地位至关重要。     

从间接言语行为分析电影《蒙娜丽莎的微笑》的师生互动

本文基于语用学的间接言语行为理论来分析电影《蒙娜丽莎的微笑》的师生互动,得出以下两点启发:1.教师在教学中适当运用间接言语行为可增强师生互动;2.教师需重视培养学生在有效沟通中的语用能力。