基于论文与专利整合数据的研究方向发现模型研究          下载免费PDF全文

任智军  詹淑琳  范婷婷 《情报工程》2015,1(4):088-094

海量信息分析及基于分析结果得出相应的结论是一项非常重要的工作,该工作需要投入大量的时间和精力。本文涉及了基于论文与专利整合数据的研究方向发现模型,从论文和专利共同研究方向和新兴技术两个方面来揭示论文和专利之间关系,最后,我们对电动汽车论文和专利数据进行了实例验证。  相似文献   

浅析南方离子型稀土原地浸矿开采前水文地质调查的重要性     

计策  秦东 《大众科技》2015,(5)

采矿工程与矿区水文地质条件密不可分,二者相互影响相互制约,根据南方离子型稀土原地浸矿开采机理特征,其开采过程不仅可能影响其所在地区的水文地质条件,而且反过来矿区水文地质条件也将影响矿山的开采作业方式、技术措施和经济效益,因此必须重视开采前水文地质调查。  相似文献   

Online visibility of software-related web sites: The case of biomedical text mining tools     

Gael Pérez-Rodríguez  Martín Pérez-Pérez  Florentino Fdez-Riverola  Anália Lourenço 《Information processing & management》2019,56(3):565-583

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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   

Time gap analysis by the topic model-based temporal technique     

《Journal of Informetrics》2014,8(3):776-790

This study proposes a temporal analysis method to utilize heterogeneous resources such as papers, patents, and web news articles in an integrated manner. We analyzed the time gap phenomena between three resources and two academic areas by conducting text mining-based content analysis. To this end, a topic modeling technique, Latent Dirichlet Allocation (LDA) was used to estimate the optimal time gaps among three resources (papers, patents, and web news articles) in two research domains. The contributions of this study are summarized as follows: firstly, we propose a new temporal analysis method to understand the content characteristics and trends of heterogeneous multiple resources in an integrated manner. We applied it to measure the exact time intervals between academic areas by understanding the time gap phenomena. The results of temporal analysis showed that the resources of the medical field had more up-to-date property than those of the computer field, and thus prompter disclosure to the public. Secondly, we adopted a power-law exponent measurement and content analysis to evaluate the proposed method. With the proposed method, we demonstrate how to analyze heterogeneous resources more precisely and comprehensively.  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   

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   

中文电子病历的分词及实体识别研究   总被引：1，自引：0，他引：1  

王若佳  赵常煜  王继民 《图书情报工作》2019,63(2):34-42

[目的/意义]健康医疗大数据是我国重要的基础性战略资源，本研究对中文电子病历分词与实体识别的探讨与实证较好地完成了医疗数据的信息抽取任务，对今后医疗大数据在语义层面的应用发展具有重要意义。[方法/过程]本研究首先融合权威词表、官方标准、健康网站数据及其他医学补充词库构建了词语数量级达到10万的医学词表；然后对电子病历的字段进行分词，对比了jieba工具、导入词典后的jieba、无监督学习及AC自动机4种模型的分词效果；最后，以自动分词和人工标注结果为语料，实现基于条件随机场的电子病历实体识别研究，并比较不同实体类别以及不同文本特征下的实体识别效果，选出最优模板。[结果/结论]分词结果显示，AC自动机的效果最好，F值可达82%；实体识别结果表明，"检查"和"疾病"实体的识别效果最好，而"症状"的识别效果不太理想。  相似文献   

黄石市中小企业电子商务发展现状研究     

唐雁凌 《黄石理工学院学报(人文社科版)》2015,(2):60-63

黄石市作为矿冶城市,由于受传统矿冶营销思维的影响,在现代市场营销特别是电子商务推进方面启动较晚,在电子商务发展迅速的今天,处于一种尴尬的局面,特别是中小企业电子商务的进程更显滞后。文章收集了大量的资料,分析了黄石市中小企业电子商务发展的现状,提出了改进措施与建议。  相似文献   

利用AIS数据计算港口间竞争度的方法     

向哲  施朝健  胡勤友  杨春 《上海海事大学学报》2016,37(1):60-64

为能更有效地提供有价值的航运情报, 借鉴网络分析法相关原理，挖掘船舶AIS数据，获取港口之间的竞争度.该法通过船舶数据模型、港口数据模型、船舶抵达港口事件模型、船舶挂靠港记录、港口之间运力、港口网络等建立港口间竞争度模型. 选取2014年4—8月中国沿海船舶AIS数据和17个主要港口数据，利用模型计算出对上海港竞争度排名前三的港口依次是宁波港、张家港港和南通港.  相似文献