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本文根据MCRC引进装置的情况,对加拿大Delta公司的MCRC硫回收工艺作了初步探索,介绍了该方法的工艺特征,并评述了引进装置的性能考核结果。文中还结合四川气田建厂的环保要求,评价了MCRC方法的使用价值及意义。     

TWILITE: A recommendation system for Twitter using a probabilistic model based on latent Dirichlet allocation

Twitter provides search services to help people find users to follow by recommending popular users or the friends of their friends. However, these services neither offer the most relevant users to follow nor provide a way to find the most interesting tweet messages for each user. Recently, collaborative filtering techniques for recommendations based on friend relationships in social networks have been widely investigated. However, since such techniques do not work well when friend relationships are not sufficient, we need to take advantage of as much other information as possible to improve the performance of recommendations.In this paper, we propose TWILITE, a recommendation system for Twitter using probabilistic modeling based on latent Dirichlet allocation which recommends top-K users to follow and top-K tweets to read for a user. Our model can capture the realistic process of posting tweet messages by generalizing an LDA model as well as the process of connecting to friends by utilizing matrix factorization. We next develop an inference algorithm based on the variational EM algorithm for learning model parameters. Based on the estimated model parameters, we also present effective personalized recommendation algorithms to find the users to follow as well as the interesting tweet messages to read. The performance study with real-life data sets confirms the effectiveness of the proposed model and the accuracy of our personalized recommendations.     

A multi-document summarization system based on statistics and linguistic treatment

The massive quantity of data available today in the Internet has reached such a huge volume that it has become humanly unfeasible to efficiently sieve useful information from it. One solution to this problem is offered by using text summarization techniques. Text summarization, the process of automatically creating a shorter version of one or more text documents, is an important way of finding relevant information in large text libraries or in the Internet. This paper presents a multi-document summarization system that concisely extracts the main aspects of a set of documents, trying to avoid the typical problems of this type of summarization: information redundancy and diversity. Such a purpose is achieved through a new sentence clustering algorithm based on a graph model that makes use of statistic similarities and linguistic treatment. The DUC 2002 dataset was used to assess the performance of the proposed system, surpassing DUC competitors by a 50% margin of f-measure, in the best case.     

呼和浩特石化公司凝结水回收改造工程总结

本文主要对呼和浩特石化公司凝结水回收系统改造前的状况、采取的改造措施及改造后的效果进行了总结，并就今后可能的改造作了预测分析。     

融熔硫磺成形方法综述

硫磺是生产硫酸的主要原料，我国从石油和天然气中回收硫及硫的成形技术正在日益发展。介绍了融熔硫磺的各种成形方法，建议国内今后应朝着水小粒法、空气小料法的成形技术发展。     

Sourcing the Arab Spring: A Case Study of Andy Carvin's Sources on Twitter During the Tunisian and Egyptian Revolutions

News sourcing practices are critical as they shape from whom journalists get their information and what information they obtain, mostly from elite sources. This study evaluates whether social media platforms expand the range of actors involved in the news through a quantitative content analysis of the sources cited by NPR's Andy Carvin on Twitter during the Arab Spring. Results show that, on balance, nonelite sources had a greater representation in the content than elite sources. Alternative actors accounted for nearly half of the messages. The study points to the innovative forms of production that can emerge with new communication technologies, with the journalist as a central node trusted to authenticate and interpret news flows on social awareness streams.     

面向新闻情报分析的自动摘要技术研究

随着现代化网络技术的快速发展和广泛使用,信息处理技术获得了很大的发展和进步,对于新闻情报信息来说怎样利用计算机自动地从情报信息中提取摘要变得越来越重要。摘要应该覆盖新闻情报中的最核心的内容以及对用户最有价值的信息,再通过言简意赅的文章段落的表现形式生成,以实现将新闻情报中重要的信息及时、方便的呈现给用户,为用户提供高效的新闻情报分析体验,这种关于新闻情报分析的自动摘要技术对于新闻事业有着重要的意义。     

College students and risk-taking behaviour on Twitter versus Facebook

The propensity of college students to post content that they know may be unacceptable to future employers or other authority figures has been well established. Yet research on this topic has tended to focus exclusively on Facebook, which is problematic for two reasons. First, many young social media users are shifting away from Facebook and towards Twitter and other services. Second, college students have changed their use of social media over time and may now be more cautious about what they post on Facebook. To address this issue, a survey-based field study was conducted to compare student comfort levels with authority figures viewing their Facebook and Twitter accounts. Specifically, undergraduate business students attending a large university in the midwest of the USA were surveyed about their Facebook and Twitter accounts. Findings indicate that college students are markedly less comfortable with authority figures viewing their Twitter accounts. Paradoxically, a great majority of the study respondents were found to have public Twitter accounts, while only a very small minority have public Facebook accounts. This finding suggests that students perceive less risk on Twitter versus Facebook or that they are writing to different imagined audiences on the two platforms. Implications include the need for further inquiry and an awareness of educators and human resources professionals about students’ current social media practices.     

Video summarization via minimum sparse reconstruction

The rapid growth of video data demands both effective and efficient video summarization methods so that users are empowered to quickly browse and comprehend a large amount of video content. In this paper, we formulate the video summarization task with a novel minimum sparse reconstruction (MSR) problem. That is, the original video sequence can be best reconstructed with as few selected keyframes as possible. Different from the recently proposed convex relaxation based sparse dictionary selection method, our proposed method utilizes the true sparse constraint L₀ norm, instead of the relaxed constraint _L2,1$L_{2,1}$ norm, such that keyframes are directly selected as a sparse dictionary that can well reconstruct all the video frames. An on-line version is further developed owing to the real-time efficiency of the proposed MSR principle. In addition, a percentage of reconstruction (POR) criterion is proposed to intuitively guide users in obtaining a summary with an appropriate length. Experimental results on two benchmark datasets with various types of videos demonstrate that the proposed methods outperform the state of the art.     

基于混合方法的中文微博自动摘要技术研究

针对微博内容驳杂、信息稀疏的问题,深入研究传统自动摘要技术,结合微博数据特点,在微博事件提取的基础上提出一种基于统计和理解的混合摘要方法。首先根据词频、句子位置等文本特征得到基于统计的初始摘要;然后通过语义词典,计算句子相似度、确定事件主体进行基于语义理解的可读性加工,使最终摘要更具可读性;最后采用合理的摘要评价方法评价所得摘要。实验结果表明,该方法在不同压缩比例下均能获得质量稳定且可读性良好的摘要。