ACM Trans. Manag. Inf. Syst.最新文献_第6页

A Dispatch-Mediated Communication Model for Emergency Response Systems 应急响应系统的调度中介通信模型

ACM Trans. Manag. Inf. Syst. Pub Date : 2013-04-01 DOI: 10.1145/2445560.2445562

Rohit Valecha, R. Sharman, H. Rao, S. Upadhyaya

引用次数: 16

Contrasting Multiple Social Network Autocorrelations for Binary Outcomes, With Applications To Technology Adoption 对比二元结果的多个社会网络自相关性，以及技术采用的应用

ACM Trans. Manag. Inf. Syst. Pub Date : 2012-10-11 DOI: 10.1145/2407740.2407742

Bin Zhang, Andrew C. Thomas, P. Doreian, D. Krackhardt, R. Krishnan

{"title":"Contrasting Multiple Social Network Autocorrelations for Binary Outcomes, With Applications To Technology Adoption","authors":"Bin Zhang, Andrew C. Thomas, P. Doreian, D. Krackhardt, R. Krishnan","doi":"10.1145/2407740.2407742","DOIUrl":"https://doi.org/10.1145/2407740.2407742","url":null,"abstract":"The rise of socially targeted marketing suggests that decisions made by consumers can be predicted not only from their personal tastes and characteristics, but also from the decisions of people who are close to them in their networks. One obstacle to consider is that there may be several different measures for closeness that are appropriate, either through different types of friendships, or different functions of distance on one kind of friendship, where only a subset of these networks may actually be relevant. Another is that these decisions are often binary and more difficult to model with conventional approaches, both conceptually and computationally. To address these issues, we present a hierarchical auto-probit model for individual binary outcomes that uses and extends the machinery of the auto-probit method for binary data. We demonstrate the behavior of the parameters estimated by the multiple network-regime auto-probit model (m-NAP) under various sensitivity conditions, such as the impact of the prior distribution and the nature of the structure of the network. We also demonstrate several examples of correlated binary data outcomes in networks of interest to information systems, including the adoption of caller ring-back tones, whose use is governed by direct connection but explained by additional network topologies.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114895048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 23

Business Intelligence and Analytics Education, and Program Development: A Unique Opportunity for the Information Systems Discipline 商业智能和分析教育和程序开发:信息系统学科的独特机会

ACM Trans. Manag. Inf. Syst. Pub Date : 2012-10-01 DOI: 10.1145/2361256.2361257

R. Chiang, Paulo B. Góes, E. Stohr

引用次数: 151

Using a Network Analysis Approach for Organizing Social Bookmarking Tags and Enabling Web Content Discovery 使用网络分析方法组织社会书签标签和启用Web内容发现

ACM Trans. Manag. Inf. Syst. Pub Date : 2012-10-01 DOI: 10.1145/2361256.2361260

Wei Wei, S. Ram

引用次数: 6

Do Vendors’ Pricing Decisions Fully Reflect Information in Online Reviews? 供应商的定价决策是否充分反映了在线评论中的信息?

ACM Trans. Manag. Inf. Syst. Pub Date : 2012-10-01 DOI: 10.1145/2361256.2361261

Nan Hu, H. Cavusoglu, Lingbing Liu, Chenkai Ni

引用次数: 4

Who is Retweeting the Tweeters? Modeling, Originating, and Promoting Behaviors in the Twitter Network 谁在转发推特用户?推特网络中的行为建模、起源和促进

ACM Trans. Manag. Inf. Syst. Pub Date : 2012-10-01 DOI: 10.1145/2361256.2361258

Palakorn Achananuparp, Ee-Peng Lim, Jing Jiang, Tuan-Anh Hoang

{"title":"Who is Retweeting the Tweeters? Modeling, Originating, and Promoting Behaviors in the Twitter Network","authors":"Palakorn Achananuparp, Ee-Peng Lim, Jing Jiang, Tuan-Anh Hoang","doi":"10.1145/2361256.2361258","DOIUrl":"https://doi.org/10.1145/2361256.2361258","url":null,"abstract":"Real-time microblogging systems such as Twitter offer users an easy and lightweight means to exchange information. Instead of writing formal and lengthy messages, microbloggers prefer to frequently broadcast several short messages to be read by other users. Only when messages are interesting, are they propagated further by the readers. In this article, we examine user behavior relevant to information propagation through microblogging. We specifically use retweeting activities among Twitter users to define and model originating and promoting behavior. We propose a basic model for measuring the two behaviors, a mutual dependency model, which considers the mutual relationships between the two behaviors, and a range-based model, which considers the depth and reach of users’ original tweets. Next, we compare the three behavior models and contrast them with the existing work on modeling influential Twitter users. Last, to demonstrate their applicability, we further employ the behavior models to detect interesting events from sudden changes in aggregated information propagation behavior of Twitter users. The results will show that the proposed behavior models can be effectively applied to detect interesting events in the Twitter stream, compared to the baseline tweet-based approaches.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116897274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 43

Credit Rating Change Modeling Using News and Financial Ratios 使用新闻和财务比率的信用评级变化模型

ACM Trans. Manag. Inf. Syst. Pub Date : 2012-10-01 DOI: 10.1145/2361256.2361259

Hsin-Min Lu, Feng-Tse Tsai, Hsinchun Chen, Mao-Wei Hung, Shu-Hsing Li

{"title":"Credit Rating Change Modeling Using News and Financial Ratios","authors":"Hsin-Min Lu, Feng-Tse Tsai, Hsinchun Chen, Mao-Wei Hung, Shu-Hsing Li","doi":"10.1145/2361256.2361259","DOIUrl":"https://doi.org/10.1145/2361256.2361259","url":null,"abstract":"Credit ratings convey credit risk information to participants in financial markets, including investors, issuers, intermediaries, and regulators. Accurate credit rating information plays a crucial role in supporting sound financial decision-making processes. Most previous studies on credit rating modeling are based on accounting and market information. Text data are largely ignored despite the potential benefit of conveying timely information regarding a firm’s outlook. To leverage the additional information in news full-text for credit rating prediction, we designed and implemented a news full-text analysis system that provides firm-level coverage, topic, and sentiment variables. The novel topic-specific sentiment variables contain a large fraction of missing values because of uneven news coverage. The missing value problem creates a new challenge for credit rating prediction approaches. We address this issue by developing a missing-tolerant multinomial probit (MT-MNP) model, which imputes missing values based on the Bayesian theoretical framework. Our experiments using seven and a half years of real-world credit ratings and news full-text data show that (1) the overall news coverage can explain future credit rating changes while the aggregated news sentiment cannot; (2) topic-specific news coverage and sentiment have statistically significant impact on future credit rating changes; (3) topic-specific negative sentiment has a more salient impact on future credit rating changes compared to topic-specific positive sentiment; (4) MT-MNP performs better in predicting future credit rating changes compared to support vector machines (SVM). The performance gap as measured by macroaveraging F-measure is small but consistent.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122728045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21

Analyzing Online Review Helpfulness Using a Regressional ReliefF-Enhanced Text Mining Method 使用回归救济增强文本挖掘方法分析在线评论的有用性

ACM Trans. Manag. Inf. Syst. Pub Date : 2012-07-01 DOI: 10.1145/2229156.2229158

Thomas L. Ngo-Ye, Atish P. Sinha

{"title":"Analyzing Online Review Helpfulness Using a Regressional ReliefF-Enhanced Text Mining Method","authors":"Thomas L. Ngo-Ye, Atish P. Sinha","doi":"10.1145/2229156.2229158","DOIUrl":"https://doi.org/10.1145/2229156.2229158","url":null,"abstract":"Within the emerging context of Web 2.0 social media, online customer reviews are playing an increasingly important role in disseminating information, facilitating trust, and promoting commerce in the e-marketplace. The sheer volume of customer reviews on the web produces information overload for readers. Developing a system that can automatically identify the most helpful reviews would be valuable to businesses that are interested in gathering informative and meaningful customer feedback. Because the target variable---review helpfulness---is continuous, common feature selection techniques from text classification cannot be applied. In this article, we propose and investigate a text mining model, enhanced using the Regressional ReliefF (RReliefF) feature selection method, for predicting the helpfulness of online reviews from Amazon.com. We find that RReliefF significantly outperforms two popular dimension reduction methods. This study is the first to investigate and compare different dimension reduction techniques in the context of applying text regression for predicting online review helpfulness. Another contribution is that our analysis of the keywords selected by RReliefF reveals meaningful feature groupings.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130209637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 33

Optimal Adapter Creation for Process Composition in Synchronous vs. Asynchronous Communication 同步与异步通信中进程组合的最佳适配器创建

ACM Trans. Manag. Inf. Syst. Pub Date : 2012-07-01 DOI: 10.1145/2229156.2229160

Zhe Shan, Akhil Kumar

{"title":"Optimal Adapter Creation for Process Composition in Synchronous vs. Asynchronous Communication","authors":"Zhe Shan, Akhil Kumar","doi":"10.1145/2229156.2229160","DOIUrl":"https://doi.org/10.1145/2229156.2229160","url":null,"abstract":"A key issue in process-aware e-commerce collaboration is to orchestrate business processes of multiple business partners throughout a supply chain network in an automated and seamless way. Since each partner has its own internal processes with different control flow structures and message interfaces, the real challenge lies in verifying the correctness of process collaboration, and reconciling conflicts in an automated manner to make collaboration successful. The purpose of business process adaptation is to mediate the communication between independent processes to overcome their mismatches and incompatibilities. The goal of this article is to develop and compare efficient approaches of optimal adapter (i.e. one that minimizes the number of messages to be adapted) creation for multiple interacting processes under both synchronous and asynchronous communication. We start with an analysis of interactions of each message pair, and show how to identify incompatible cases and their adaptation elements for both types of communication. Then, we show how to extend this analysis into more general cases involving M messages and N processes (M, N > 2). Further, we present optimal adapter creation algorithms for both scenarios based on our analysis technique. The algorithms were implemented in a Java-based prototype system, and results of two experiments are reported. We compare and discuss the insights gained about adapter creation in these two scenarios.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125261111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Two New Prediction-Driven Approaches to Discrete Choice Prediction 两种新的预测驱动的离散选择预测方法

ACM Trans. Manag. Inf. Syst. Pub Date : 2012-07-01 DOI: 10.1145/2229156.2229159

Zan Huang, Huimin Zhao, Dan Zhu

{"title":"Two New Prediction-Driven Approaches to Discrete Choice Prediction","authors":"Zan Huang, Huimin Zhao, Dan Zhu","doi":"10.1145/2229156.2229159","DOIUrl":"https://doi.org/10.1145/2229156.2229159","url":null,"abstract":"The ability to predict consumer choices is essential in understanding the demand structure of products and services. Typical discrete choice models that are targeted at providing an understanding of the behavioral process leading to choice outcomes are developed around two main assumptions: the existence of a utility function that represents the preferences over a choice set and the relatively simple and interpretable functional form for the utility function with respect to attributes of alternatives and decision makers. These assumptions lead to models that can be easily interpreted to provide insights into the effects of individual variables, such as price and promotion, on consumer choices. However, these restrictive assumptions might impede the ability of such theory-driven models to deliver accurate predictions and forecasts. In this article, we develop novel approaches targeted at providing more accurate choice predictions. Specifically, we propose two prediction-driven approaches: pairwise preference learning using classification techniques and ranking function learning using evolutionary computation. We compare our proposed approaches with a multiclass classification approach, as well as a standard discrete choice model. Our empirical results show that the proposed approaches achieved significantly higher choice prediction accuracy.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120954043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9