An Empirical Study Evaluating Social Networking Continuance and Success

Social networking site (SNS) use decisions have led to major economic and social transformations worldwide. While many organizations seek to use SNSs from a strategic perspective to reach their customer, it is important to understand what makes SNSs successful in order to use them for competitive purposes. The current research evaluates the influence of the social capital theory on SNS success measures. A model was developed and empirically tested using two data samples to ensure valid and reliable results for success of SNSs. The results display the importance of social capital in SNS success followed by practitioner and academic implications.     

主题搜索引擎中网络蜘蛛搜索策略的研究

主题网络蜘蛛的搜索策略是主题搜索引擎的核心部分,是近年来主题搜索引擎研究中的热点问题之一。深入研究了主题网络蜘蛛的关键技术,阐述了多线程网络蜘蛛的实现过程,并对传统的VSM算法和PageRank算法进行了改进,提高了主题网络蜘蛛采集信息的有效性和准确性。     

搜索引擎在学术期刊编辑工作中的作用与应用策略

本文通过阐述分析网络信息资料库的特点,讲述了学术期刊编辑如何使用搜索引擎来更简单方便的检索工作所需要的信息,并点明了在使用搜索引擎时应注意的问题,从而使编辑在工作中减少无用功,提高工作效率。     

搜索引擎优化策略研究

随着Internet的发展及网络资源越来越丰富,搜索引擎所起的作用也越来越大。因此搜索引擎优化作为一种可以提升网站在搜索引擎中的排名的网站优化技术,得到了广泛的关注。如何获得高的搜索引擎排名对网站特别是商务网站显得越来越重要。文章对搜索引擎优化策略进行了系统的总结,讨论了一些具体的优化方法,并对搜索引擎优化的发展前景进行了展望。     

网络搜索引擎的性能优化策略和相关技术

由于检索结果的不准确性,使网络搜索引擎有时难以满足用户的查询需求。因此,在传统搜索引擎技术的基础上,采用其它理论和技术来提高搜索引擎的查准率,可以对搜索引擎进行性能优化。该文提出了几种对网络搜索引擎进行性能优化的策略,并对相关的实现技术进行了探讨。根据网络资源的权威性及其与用户查询的相关性对检索结果进行排序,可以有效提高结果的准确度;通过基于概念的信息检索技术和信息的自动分类技术可以有效地对用户查询进行语义的扩充和理解,更好地满足用户需求;实现搜索引擎的个性化查询和专业化查询,也是提高搜索引擎性能的重要途径。     

论利用服务器日志优化搜索引擎的研究

网站建立好了以后,就要想着如何使自己的网站让更多的人知道,如何吸引更多的人访问它,从而给自己争取更多的潜在客户。推广的办法有很多,比如说可以做路牌灯箱广告或者在电视台和纸媒体做宣传,但是这种宣传的价格有点偏贵,要么你可以在某些人气很旺的BBS上或者其他网站上面加入自己的链接,要么就干脆给人发电子邮件来宣传自己,但是这种情况的收效又不是很大。而且有点"小打小闹"的感觉,可能更加适合于那些个人主页的宣传。相比之下,注册搜索引擎的办法综合起来说效果不错,影响的范围比较广,有效时间也比较长。本文主要介绍支持向量机(SVM)分类原理,探讨了如何利用改进的SVM算法从用户行为日志中学习更新检索函数,满足不同群体的用户需求,最后利用Nutch构建了一个搜索引擎来验证我们的方法。     

提供个性化服务的搜索引擎页面排序算法

目前搜索引擎的技术发展迅速，但仍然存在一些问题。当用户输入关键字进行查询时，机器有时无法确知用户真正想要的信息。该文提出了一种对用户进行聚类的分析方法，将关键字和用户的个人偏好结合起来的算法，利用机器学习的方法来推测用户想要看到的信息。将最可能的相关链接排在最前面，以此来提高用户查询的效率。     

Determinants of users’ continuance of social networking sites: A self-regulation perspective

Social networking sites (SNS) have transformed how individuals interact, build and maintain social relationships. We proposed a research model on the determinants of user continuance using Bagozzi's framework of self-regulation as the theoretical foundation. Following the process of appraisal → emotional reactions → coping responses, we developed the model by leveraging findings from social presence and IS continuance research. Based on survey data from Facebook users, we found that appraisal factors (pleasure, awareness, connectedness, and system quality) were strong determinants of emotional reaction (user satisfaction and sense of belonging). User satisfaction and sense of belonging together positively influenced continuance intention.     

Association of demographics,motives and intensity of using Social Networking Sites with the formation of bonding and bridging social capital in Pakistan

The objectives of this confirmatory study were to investigate the association of socio-economic demographics (age, education of respondent, gender, monthly family income, parentage education), motives (communication and information, self-actualization and outward looking) of using Social Networking Sites (SNSs) and attitudinal and behavior variable (intensity of using SNS, self-esteem, gratification with university life, duration of use, and number of ties) with the formation of bonding and bridging social capital. Total 461 students, aged 18–35 years filled the questionnaire, from randomly selected departments of University of the Punjab, Lahore, Pakistan. Regression analysis was used to assess the association among variables. The study indicated that Facebook is the most popular SNS among university students in Pakistan. Intensity of using SNS, duration of using SNSs, and motives of using SNSs were found to be positively associated with formation of bonding and bridging social capital. Self-esteem and gratifications with university life were found to be significant predictors in formation of bonding social capital only. The demographics variables (education, parentage education, monthly family income) had no influence on formation of both bonding and bridging social capital.     

Who puts the best “face” forward on Facebook?: Positive self-presentation in online social networking and the role of self-consciousness,actual-to-total Friends ratio,and culture

The present research investigated how individual, interpersonal, and cultural variables influence positive self-presentation in online social networking. In particular, we examined the role of self-consciousness, actual-to-total Friends ratio, and culture in positive self-presentation on Facebook. A cross-sectional survey was conducted with college-age participants in the United States (n = 183) and South Korea (n = 137). Results showed that self-consciousness (public vs. private) and actual-to-total Friends ratio were not significantly associated with positive self-presentation on Facebook; however, culture showed a statistically significant association with positive self-presentation on Facebook, with the U.S. participants engaging in positive self-presentation on Facebook to a greater extent than the South Korean participants. More interestingly, culture significantly moderated the relationship between public self-consciousness and positive self-presentation as well as the relationship between actual-to-total Friends ratio and positive self-presentation. Specifically, positive self-presentation showed a significant positive association with public self-consciousness and a significant negative association with actual-to-total Friends ratio only among the South Korean participants and not among the U.S. participants. Theoretical and practical implications for understanding cross-cultural differences in self-presentation behaviors on social network sites were discussed.     

Search Engine Optimization: Comparison of Link Building and Social Sharing

The practice of Search Engine Optimization (SEO) can significantly increase a website’s search rankings, driving more traffic to the website, and thereby increasing revenue. Three primary SEO strategies are Content, Link Building, and Social Sharing. Our study compares the performance of three similar content-rich websites; each uses a different SEO strategy – one focused on Content only, the second uses Content and proactive Link Building, and the third uses Content and Social Media campaign designed to elicit social mentions and social sharing. We use Google Analytics to collect, analyze, and compare their site traffic, domain authority, search ranks, and ad revenue before and after SEO implementation, over the course of 18 months. Our study suggests that link building and social media both improve website traffic and revenue. Social media can be an effective method for quickly building traffic (for events); however, link building provides better return on investment in the long run.     

An Integrated Model for Customer Relationship Management: An Analysis and Empirical Study

Ensuring customer satisfaction and maintaining long‐term relationships with customers have become essential for survival among competitive service industries. The present study addresses this need by proposing a conceptually integrated four‐phase model that incorporates elements of customer relationship management (CRM) and customer satisfaction (represented by the extended American Customer Satisfaction Index model). Then, this study formulates structural equation modeling to test various research hypotheses related to the effect of the CRM initiative. An empirical study of 143 leading Taiwanese service firms distributed among seven service industries was conducted. The implementation levels of various constructs, input (customer knowledge), service provision (customer interactions), output quality, perceived quality, perceived value, perception of customer satisfaction, customer loyalty, purchasing intention, and profits of CRM are assessed in a range of service industries by means of a questionnaire survey and in‐depth interviews. The results of the empirical study reveal statistically significant influences among various constructs of the CRM integrated model. These results also represent a useful reference for managers of service organizations that could be used to improve the profitability and implementation level of CRM. The present study represents an important investigation in the development of an integrated CRM implementation system for service industries. © 2012 Wiley Periodicals, Inc.     

Retraction of ‘An Empirical Study of an Internet Marketing Strategy for Search Engine Optimization. Human Factors and Ergonomics in Manufacturing & Service Industries, 23, 528–540. doi: 10.1002/hfm.20348

The article listed above, published online on Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editors‐in‐Chief, Gavriel Salvendy and Waldemar Karwowski, and Wiley Periodicals, Inc. The retraction has been agreed due to evidence indicating that the peer review of this paper was compromised. It is believed that the paper was accepted based on recommendations from reviewers with conflicts of interest. In addition, ISI provided the publisher with evidence of inappropriate manipulation of citations.     

Predicting selfie-posting behavior on social networking sites: An extension of theory of planned behavior

Over the past few years, a notable trend has emerged in social networking sites (SNSs). With the growing popularity of image-based SNSs such as Instagram, users increasingly communicate and present themselves by posting photographs they take of themselves (“selfies”). As the phenomenon of selfies becomes widespread across a range of SNSs as a unique means of self-presentation, an interesting question arises, what makes people post their selfies on SNSs. To delve into this rising issue, the present study investigates the antecedents of selfie-posting behavior on SNSs by applying and extending Ajzen's Theory of Planned Behavior (TPB). A conceptual model, which is primarily drawn from the TPB and incorporates narcissism as an additional antecedent, is proposed and empirically tested. Results show that attitude toward selfie-posting, subjective norm, perceived behavioral control, and narcissism are the significant determinants of an individual's intention to post selfies on SNSs. Further, one's selfie-posting behavior on SNSs is significantly predicted by his or her intention to post selfies. Implications of the findings are discussed with suggestions for future research.     

混合编码和声搜索算法在动态优化中的应用

采用混合双重编码方法,提出一种混合编码二进制和声搜索算法HBHSA,用以求解动态位匹配问题和时变背包问题。仿真结果表明,与DS_BPSO、HBDE和PDGA算法相比,HBHSA具有更好的鲁棒性和通用性,在动态环境中的搜索能力和对最优解的跟踪能力更优。     

Teens’ concern for privacy when using social networking sites: An analysis of socialization agents and relationships with privacy-protecting behaviors

U.S. teens are spending substantial time on social networking sites (SNSs). Yet, only a few studies have documented teens’ privacy-protecting behaviors on SNSs. Using data of Facebook teen users and their parents in the U.S. from the Pew Internet’s Teens & Privacy Management Survey (N = 622), this study investigated the socialization agents of teens’ level of online privacy concern, and the relationship between teens’ level of online privacy concern and their privacy-protecting behaviors on SNSs. Based on path analysis results, this study identified parents and SNS use as the two significant socialization agents. In particular, this study revealed the role of parents’ privacy concern and the role of SNS use in motivating teens to increase online privacy concern, which, in turn, drives teens to adopt various privacy-setting strategies on SNSs and to set their Facebook profiles to private. Implications for policymakers and educators were discussed.     

一种针对区分性训练的受限线性搜索优化方法

提出一种称为“受限线性搜索”的优化方法,并用于语音识别中混合高斯的连续密度隐马尔科夫(CDHMM)模型的区分性训练。该方法可用于优化基于最大互信息(MMI)准则的区分性训练目标函数。在该方法中,首先把隐马尔科夫模型(HMM)的区分性训练问题看成一个受限的优化问题,并利用模型间的KL度量作为优化过程中的一个限制。再基于线性搜索的思想,指出通过限制更新前后模型间的KL度量,可将HMM的参数表示成一种简单的二次形式。该方法可用于优化混合高斯CDHMM模型中的任何参数,包括均值、协方差矩阵、高斯权重等。将该方法分别用于中英文两个标准语音识别任务上,包括英文TIDIGITS数据库和中文863数据库。实验结果表明,该方法相对传统的扩展Baum-Welch方法在识别性能和收敛特性上都取得一致提升。     

基于区块链的车联网安全通信策略

为完善车联网信任评估机制并建立车辆间的信任关系,提出一种基于区块链技术的车联网安全通信策略.利用椭圆曲线加密算法进行车辆身份注册与验证,结合基于Beta分布的直接信任值与基于PageRank算法的推荐信任值求得车辆综合信任值.通过智能合约技术对车辆综合信任值及交互信息进行管控,实现车辆综合信任值的上链、更改与更新.仿真...     

EOFDM:一种面向众核架构的最低能耗搜索方法

面向能耗优化的面积(核数)-功率(频率)分配问题是当前众核处理器研究热点之一.通过性能-功耗模型了解其在核数-频率空间的分布规律,然后在核数和频率级别这2个维度上通过实测执行逐步搜索,可以获取“核数-频率”配置的最优解,从而达到能耗优化的目的;然而本领域现有方法在核数-频率空间内实测搜索最低能耗时收敛速度慢、搜索开销大、可扩展性差.针对此问题,提出了一种基于求解最优化问题的经典数学方法——可行方向法的最低能耗搜索方法(energy-efficient optimization based on feasible direction method,EOFDM),每次执行都能从核数和频率2个维度上同时减小搜索空间,在迭代执行中快速收敛至最低能耗点.该方法与现有研究中最优的启发式爬山法(hill-climbing heuristic,HCH)进行了对比实验,平均执行次数、执行时间和能耗分别降低39.5％,46.8％,48.3％,提高了收敛速度,降低了搜索开销;当核数增加一倍时,平均执行次数、执行时间和能耗分别降低48.8％,51.6％,50.9％;当频率级数增加一倍时,平均执行次数、执行时间和能耗分别降低45.5％,49.8％,54.4％,在收敛速度、搜索开销和可扩展性方面均有提高.     

粒子群优化算法中惯性权值调整的一种新策略

惯性权值的设置对粒子群优化（PSO）算法的性能起着关键作用,现有的基于惯性权值的改进算法提高了算法的性能,但都把惯性权值作为全局参数,很难控制算法的搜索能力。本文在充分分析惯性权值的关键作用基础上给出一种新的惯性权值调整策略及其相应的粒子群优化算法,使用不同的惯性权值更新同一代种群。测试结果表明,新算法提高了算算法的性能,并具有更快的收敛速度和跳出局部最优的能力。