The Program for Cooperative Cataloging’s Transformative Role as a Leader of Change     

Philip E. Schreur 《Cataloging & classification quarterly》2020,58(3-4):397-402

Abstract

The transformation of library metadata encoded in MARC to linked data will enable libraries to participate in the Semantic Web. This transformation, however, will be an iterative development dependent upon community-based decisions. The PCC, as a community-based organization, is ideally positioned to lead this transformation. As PCC guides this transition, three broad areas must be resolved: the conversion of legacy data to linked data, the use of identifiers to support controlled headings, and the transformation of current workflows to linked-data counterparts. By embracing the Web as a community, PCC can confirm its relevance in a complex web of global data.  相似文献   

Spatial Planning and its Need for National and Regional Bibliographies of Grey Literature     

Christian Erlinger 《Cataloging & classification quarterly》2019,57(1):59-72

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Applying artificial intelligence technique to predict knowledge hiding behavior     

《International Journal of Information Management》2019

Drawing on psychological ownership and social exchange theories, this study suggests theoretical arguments and empirical evidence for understanding employee reactions to distributive, procedural, and interactional (in)justice — three crucial bases of employees’ feelings of social self-worth. Utilizing field data and artificial intelligence technique, this paper reveals that distributive, procedural, and interactional (in)justice contribute to higher levels of knowledge hiding behavior among employees and that this impact is non-linear (asymmetric). By reuniting the discourses of organizational justice and knowledge management, this study indicates that feelings of psychological ownership of knowledge and the degree of social interaction are mechanisms that work with organizational (in)justice to influence knowledge hiding behavior. The current research may inform contemporary theories of business research and provide normative guidance for managers.  相似文献   

Web document summarization by exploiting social context with matrix co-factorization     

Minh-Tien Nguyen  Viet Cuong Tran  Xuan Hoai Nguyen  Le-Minh Nguyen 《Information processing & management》2019,56(3):495-515

In the context of social media, users usually post relevant information corresponding to the contents of events mentioned in a Web document. This information posses two important values in that (i) it reflects the content of an event and (ii) it shares hidden topics with sentences in the main document. In this paper, we present a novel model to capture the nature of relationships between document sentences and post information (comments or tweets) in sharing hidden topics for summarization of Web documents by utilizing relevant post information. Unlike previous methods which are usually based on hand-crafted features, our approach ranks document sentences and user posts based on their importance to the topics. The sentence-user-post relation is formulated in a share topic matrix, which presents their mutual reinforcement support. Our proposed matrix co-factorization algorithm computes the score of each document sentence and user post and extracts the top ranked document sentences and comments (or tweets) as a summary. We apply the model to the task of summarization on three datasets in two languages, English and Vietnamese, of social context summarization and also on DUC 2004 (a standard corpus of the traditional summarization task). According to the experimental results, our model significantly outperforms the basic matrix factorization and achieves competitive ROUGE-scores with state-of-the-art methods.  相似文献   

Neural embedding-based indices for semantic search     

Fatemeh Lashkari  Ebrahim Bagheri  Ali A. Ghorbani 《Information processing & management》2019,56(3):733-755

Traditional information retrieval techniques that primarily rely on keyword-based linking of the query and document spaces face challenges such as the vocabulary mismatch problem where relevant documents to a given query might not be retrieved simply due to the use of different terminology for describing the same concepts. As such, semantic search techniques aim to address such limitations of keyword-based retrieval models by incorporating semantic information from standard knowledge bases such as Freebase and DBpedia. The literature has already shown that while the sole consideration of semantic information might not lead to improved retrieval performance over keyword-based search, their consideration enables the retrieval of a set of relevant documents that cannot be retrieved by keyword-based methods. As such, building indices that store and provide access to semantic information during the retrieval process is important. While the process for building and querying keyword-based indices is quite well understood, the incorporation of semantic information within search indices is still an open challenge. Existing work have proposed to build one unified index encompassing both textual and semantic information or to build separate yet integrated indices for each information type but they face limitations such as increased query process time. In this paper, we propose to use neural embeddings-based representations of term, semantic entity, semantic type and documents within the same embedding space to facilitate the development of a unified search index that would consist of these four information types. We perform experiments on standard and widely used document collections including Clueweb09-B and Robust04 to evaluate our proposed indexing strategy from both effectiveness and efficiency perspectives. Based on our experiments, we find that when neural embeddings are used to build inverted indices; hence relaxing the requirement to explicitly observe the posting list key in the indexed document: (a) retrieval efficiency will increase compared to a standard inverted index, hence reduces the index size and query processing time, and (b) while retrieval efficiency, which is the main objective of an efficient indexing mechanism improves using our proposed method, retrieval effectiveness also retains competitive performance compared to the baseline in terms of retrieving a reasonable number of relevant documents from the indexed corpus.  相似文献   

Cognitive-inspired domain adaptation of sentiment lexicons     

Frank Z. Xing  Filippo Pallucchini  Erik Cambria 《Information processing & management》2019,56(3):554-564

Sentiment lexicons are essential tools for polarity classification and opinion mining. In contrast to machine learning methods that only leverage text features or raw text for sentiment analysis, methods that use sentiment lexicons embrace higher interpretability. Although a number of domain-specific sentiment lexicons are made available, it is impractical to build an ex ante lexicon that fully reflects the characteristics of the language usage in endless domains. In this article, we propose a novel approach to simultaneously train a vanilla sentiment classifier and adapt word polarities to the target domain. Specifically, we sequentially track the wrongly predicted sentences and use them as the supervision instead of addressing the gold standard as a whole to emulate the life-long cognitive process of lexicon learning. An exploration-exploitation mechanism is designed to trade off between searching for new sentiment words and updating the polarity score of one word. Experimental results on several popular datasets show that our approach significantly improves the sentiment classification performance for a variety of domains by means of improving the quality of sentiment lexicons. Case-studies also illustrate how polarity scores of the same words are discovered for different domains.  相似文献   

Contemporary school knowledge democracy: possible meanings,promising perspectives and necessary prerequisites     

Eleni Katsarou  Konstantinos Sipitanos 《Educational Action Research》2019,27(1):108-124

ABSTRACT

The basic aim of this paper is to discuss the concept ‘Knowledge Democracy’ (KD) and what it can mean in the school context, its implications on knowledge production and dissemination and on the educational practices. We try to enrich this discussion by presenting action research projects to provide case studies of how thinking about KD can reshape educational practice. We consider that the discussion on KD has to be enriched as the concept seems very promising with good prospects towards school’s democratization. On the other hand, as it is quite new, it can encompass internal contradictions that can cause problems at the level of practice. So, we consider very important any contribution to this discussion not as another theoretical sample of the debate on the ‘politics of knowledge’, but because any improvement at the thinking of the issue can be reflected on school practices. Any challenge to traditional politics of knowledge can lead to a deeper understanding of the world of schooling and to transformations through new discourses and new approaches to teaching and learning in school.  相似文献   

图书情报学领域学科交叉及其国家差异的动态分析     

王思茗  滕广青 《图书情报知识》2020,(3):109-118,F0003

[目的/意义]领域知识的跨学科交叉研究能够打破学科间的壁垒,有助于发现重大科学问题的解决方案。[研究设计/方法]基于图书情报学领域文献题录信息构建轻量级领域知识图谱,从中提取学科信息、国家信息、时间信息及其关联,采用时间与空间相结合的多维度分析方法,对学科交叉的演化进程以及国家差异进行跟踪与分析。[结论/发现]图书情报学领域内学科交叉现象日渐显著,各国家的学科交叉程度与倾向存在差异,一些目前尚不突出的交叉学科方向值得关注。[创新/价值]采用多维度视角分析学科交叉现象,相关结论可以为国家科技战略制定及学科发展规划提供有益参考。  相似文献   

人文社科专著众筹OA出版发展现状和思考——以Open Book Publishers和Knowledge Unlatched为例     

徐志玮 《图书情报工作》2021,64(22):77-84

[目的/意义] 梳理人文社科专著众筹OA出版的发展现状，分析具有公益性特点的OA出版物和具有商业性特点的众筹出版所引起的冲突，以期对学术专著众筹出版提出有价值的思考。[方法/过程] 从发起者、投资者和众筹平台3个基本要素梳理Open Book Publishers和Knowledge Unlatched的众筹模式，比较异同点，探讨两者在竞争中引起的问题。[结果/结论] 目前，欧美国家的学术专著众筹出版分为高校、众筹商和OA出版社3种模式。Knowledge Unlatched是期望通过对图书馆的优质服务获得收益的众筹商，Open Book Publishers是借助网络开展众筹出版的OA出版社，两者属于商业化大型公司和非营利性OA出版社的竞争关系，在OA出版物的商业化开发、财务公开透明、垄断性的销售模式和审核制度方面值得高度关注。  相似文献   

知识优势对企业竞争力的作用机理研究     

许照成  侯经川 《科技管理研究》2020,40(21):134-142

知识优势对企业竞争力的重要作用一直备受关注,但知识优势对企业竞争力的转化机理问题却很少有研究。在回顾国内外相关研究基础上,构建了知识优势对企业竞争力的作用机理模型,并选取华为企业进行案例分析。研究表明：(1)企业持续竞争优势的获取实际上就是企业打造知识优势的过程,知识优势对企业竞争力提升具有至关重要作用；(2)知识优势对企业竞争力的转化过程分别经历了“内部知晓-内部响应-外部知晓-外部响应”知识链环节,对应于“知识获取与吸收-知识内化”、“知识应用与创新-知识生产”、“知识积累与积淀-知识外化”三个部分。本研究揭示了企业竞争力形成的内在转化机理,为企业管理者培育和提升企业竞争力提供理论指导和决策参考。  相似文献