我国5种医药大学学报在国内外数据库中高被引论文的对比分析

【目的】 对比国内高被引论文在国外的被引情况与国外高被引论文在国内的被引情况,探讨二者的相关性,以了解国内外高被引论文的差异。【方法】 选择2017年《中国科技期刊引证报告(核心版)》医药大学学报类综合评价总分排名前5位的期刊,选取2008—2017年各期刊在CNKI中的高被引论文共512篇及WoS中高被引论文共486篇,统计分析所选文献的被引频次等相关指标。【结果】 5种期刊的CNKI高被引论文的被引频次差异较小,而WoS高被引论文的被引频次差异较大;CNKI高被引论文的被引频次远高于WoS高被引论文的被引频次;除《南方医科大学学报》外,CNKI/WoS高被引论文的被引频次与其在WoS/CNKI中的被引频次的差异不具有统计学意义(P>0.05)。【结论】 我国5种国内学术影响力较高的医药大学学报的国际影响力均较低,这些期刊国内/外高被引论文的被引频次与其在国外/内的被引频次之间的相关性均不明显,国内外对5种期刊的引用存在差异。     

基于因子分析和曲线拟合的集装箱吞吐量预测

为提高集装箱吞吐量的预测精度,提出基于因子分析和曲线拟合的集装箱吞吐量预测模型。以上海港为例,通过因子分析,分析影响集装箱吞吐量的主要因素,筛选出主因子,得到不同年份的综合经济发展值;再运用曲线拟合方法,建立以综合经济发展值为自变量,以集装箱吞吐量为因变量的三次曲线模型;运用自回归积分移动平均(autoregressive integrated moving average,ARIMA)模型预测2016—2020年的综合经济发展值,进而求得2016—2020年上海港集装箱吞吐量预测值。结果表明:该模型的拟合效果和预测精度均较高,可以运用到集装箱吞吐量预测中。给出上海港在国内经济新常态下转型升级的建议。     

灰色预测法在情报研究中的应用研究综述

[目的/意义] 灰色预测法可有效处理情报研究中广泛存在的小样本数据，通过对灰色预测法在情报研究中的应用情况进行梳理，总结其在应用过程中存在的不足，为灰色预测法在情报研究中的进一步应用提供参考。[方法/过程] 通过综述情报研究中涉及灰色预测法的相关文献，从数据选取、模型构建和解决的问题等方面对情报研究中灰色预测法的应用进行概述，总结当前情报研究中灰色预测法的应用所存在的问题，并提出改进建议。[结果/结论] 在方法应用上，已有研究主要采用数列灰预测，且模型集中在单变量灰色预测模型，根据预测对象不同，灰色预测法已经在包括期刊分析、图书馆运行管理、热点主题分析及科研机构评价方面得到了很好的应用，未来可根据预测对象特点及研究目标尝试不同的灰色预测方法，扩宽灰色预测法在其他方面的情报研究问题中的应用。     

Location extraction from tweets

Five hundred million tweets are posted daily, making Twitter a major social media platform from which topical information on events can be extracted. These events are represented by three main dimensions: time, location and entity-related information. The focus of this paper is location, which is an essential dimension for geo-spatial applications, either when helping rescue operations during a disaster or when used for contextual recommendations. While the first type of application needs high recall, the second is more precision-oriented. This paper studies the recall/precision trade-off, combining different methods to extract locations. In the context of short posts, applying tools that have been developed for natural language is not sufficient given the nature of tweets which are generally too short to be linguistically correct. Also bearing in mind the high number of posts that need to be handled, we hypothesize that predicting whether a post contains a location or not could make the location extractors more focused and thus more effective. We introduce a model to predict whether a tweet contains a location or not and show that location prediction is a useful pre-processing step for location extraction. We define a number of new tweet features and we conduct an intensive evaluation. Our findings are that (1) combining existing location extraction tools is effective for precision-oriented or recall-oriented results, (2) enriching tweet representation is effective for predicting whether a tweet contains a location or not, (3) words appearing in a geography gazetteer and the occurrence of a preposition just before a proper noun are the two most important features for predicting the occurrence of a location in tweets, and (4) the accuracy of location extraction improves when it is possible to predict that there is a location in a tweet.     

Investigations on the step-based research indices of Chambers and Miller

In a recent paper, Chambers and Miller introduced two fundamental axioms for scientific research indices. We perform a detailed analysis of these two axioms, thereby providing clean combinatorial characterizations of the research indices that satisfy these axioms and of the so-called step-based indices. We single out the staircase indices as a particularly simple subfamily of the step-based indices, and we provide a simple axiomatic characterization for them.     

基于短时交通流量预测对路网微观交通仿真的研究

针对早高峰短时交通流量预测数据少、波动大的特点,提出用灰色模型进行预测。将灰色GM(2,1)改进为灰色GM(2,1,λ,ρ)预测模型,以提高预测精度。针对粒子群算法(PSO)的早熟现象,将Logistic混沌搜索嵌入到PSO算法,应用混沌粒子群算法(CPSO)寻找灰色GM(2,1,λ,ρ)预测模型最优的参数λ和ρ。结合两者提出了基于CPSO–GM(2,1,λ,ρ)的早高峰短时交通流预测模型。利用VISSIM对研究路网进行微观交通仿真,通过VISSIM–Excel、VBA–Matlab平台实现了短时交通流量预测和路网微观交通仿真数据的交互,对集成交通控制系统的架构进行了方案设计。仿真结果表明,结合流量预测的路网优于固定信号配时下的路网仿真。     

Coupled matrix factorization and topic modeling for aspect mining

Aspect mining, which aims to extract ad hoc aspects from online reviews and predict rating or opinion on each aspect, can satisfy the personalized needs for evaluation of specific aspect on product quality. Recently, with the increase of related research, how to effectively integrate rating and review information has become the key issue for addressing this problem. Considering that matrix factorization is an effective tool for rating prediction and topic modeling is widely used for review processing, it is a natural idea to combine matrix factorization and topic modeling for aspect mining (or called aspect rating prediction). However, this idea faces several challenges on how to address suitable sharing factors, scale mismatch, and dependency relation of rating and review information. In this paper, we propose a novel model to effectively integrate Matrix factorization and Topic modeling for Aspect rating prediction (MaToAsp). To overcome the above challenges and ensure the performance, MaToAsp employs items as the sharing factors to combine matrix factorization and topic modeling, and introduces an interpretive preference probability to eliminate scale mismatch. In the hybrid model, we establish a dependency relation from ratings to sentiment terms in phrases. The experiments on two real datasets including Chinese Dianping and English Tripadvisor prove that MaToAsp not only obtains reasonable aspect identification but also achieves the best aspect rating prediction performance, compared to recent representative baselines.     

An axiomatic analysis of Egghe’s g-index

The g-index is a well-known index for measuring and comparing the output of scientific researchers, which has been introduced by Leo Egghe in 2006 as an improvement of the Hirsch-index. This article gives an axiomatic characterization of the g-index in terms of three natural axioms.     

Influences of Chinese educational journals—research based on 2000–2004 CSSCI

Based on the analyses on the quality of educational periodicals and the number of publications and citations in Chinese Social Sciences Citation Index (CSSCI), this paper intends to make an analysis and introduction of the general situation of Chinese educational journals and publications during 2000–2004. Results show that the quantity of educational periodicals and papers published in China, their influence, “impact factor” and the quantity of language varieties and quotation types are not completely compatible. __________ Translated from Jiaoyu Yanjiu 教育研究 (Educational Research), 2006, (9): 8–18     

An Analytic Strategy to Assist Institutional Recruitment and Marketing Efforts

This article demonstrates how to fit a statistical model to historical data, test whether the model can accurately predict enrollment out-of-sample, and use the results to segment admitted students into groups so that different recruitment and marketing interventions can be applied. Conceptual and practical issues are discussed, as well as policy considerations.