基于XML和关联规则的Web挖掘研究*

首先对Web挖掘、关联规则分析及XML作了简要介绍，提出了基于XML和关联规则的Web挖掘研究思想，随后对XML结构挖掘、XML内容挖掘和基于XML的Web日志挖掘进行讨论，建立了一个较为完整的XML挖掘体系。     

IA的底层信息组织与概念空间（2）

在探讨IA自底向上（Bottom-up）信息组织方法的基础上探索概念空间构建的原理、方法以及步骤，并举例说明其在医学信息检索领域的应用。     

数据挖掘技术在科研信息服务中的应用研究

针对网络信息检索的现状，本文从数据挖掘、序化、组织和应用等方面，论述了基于数据挖掘技术的网络信息检索优势，对拓展科研信息服务提出了几点建议。     

图书馆Apache服务器日志文件数据的分析

按照标准的服务器日志格式，对图书馆Web服务器日志文件的记录进行分析，并通过对其一定时间段的数据挖掘，对图书馆网站的使用状况进行了有益的探讨。     

Analysis of Academic Libraries' Facebook Posts: Text and Data Analytics

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.     

Concept Relationships in Knowledge Organization Systems: Elements for Analysis and Common Research Among Fields

Knowledge organization systems have been studied in several fields and for different and complementary aspects. Among the aspects that concentrate common interests, in this article we highlight those related to the terminological and conceptual relationships among the components of any knowledge organization system. This research aims to contribute to the critical analysis of knowledge organization systems, especially ontologies, thesauri, and classification systems, by the comprehension of its similarities and differences when dealing with concepts and their ways of relating to each other as well as to the conceptual design that is adopted.     

Trends of infodemiology studies: a scoping review

Introduction

The health care industry is rich in data and information. Web technologies, such as search engines and social media, have provided an opportunity for the management of user generated data in real time in the form of infodemiology studies. The aim of this study was to investigate infodemiology studies conducted during 2002–2016, and compare them based on developed, developing and in transition countries.

Methods

This scoping review was conducted in 2017 with the help of the PRISMA guidelines. PubMed, Scopus, Science Direct, Web of Knowledge, Google Scholar, Wiley and Springer databases were searched between the years 2002 and 2016. Finally, 56 articles were included in the review and analysed.

Results

The initial infodemiology studies pertain to the quality assessment of the hospital's websites. Most of the studies were on developed countries, based on flu, and published in the Journal of Medical Internet Research.

Conclusion

The infodemiology approach provides unmatched opportunities for the management of health data and information generated by the users. Using this potential will provide unique opportunities for the health information need assessment in real time by health librarians and thereby provide evidence based health information to the people.

     

The more multidisciplinary the better? – The prevalence and interdisciplinarity of research collaborations in multidisciplinary institutions

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.     

中文电子病历的分词及实体识别研究

[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。