Bookmarks Recommendation in Bibsonomy using Community Detection

Several academic social networks have emerged to help researchers who need to search for documents relevant to their interests. The recommendation has been adopted in many websites to suggest relevant documents to users according to their profiles. However, many academic social networks and digital libraries still lack recommendations. In this paper, we propose a new document recommendation approach for the academic social bookmarking website: Bibsonomy. In our method, we use a community detection technique to identify related users. Then, for each target user, the recommended documents are selected from their learning communities. Experimental results show that the proposed method performs better than state-of-the-art recommendation methods.     

Mining History of Gamification Towards Finding Expertise in Question and Answering Communities: Experience and Practice with Stack Exchange

Recently, an online Q&A tool has become an essential part of individual communities and organizations of experts on specific topics. Using the answers to questions about specific topics will help such communities work more efficiently in their fields. Currently, Q&A online communities are adopting gamification to engage users by granting awards to successful users. In this paper, we investigate how to mine award achievement histories to find expertise. We propose the use of sequence analysis and clustering techniques. Specifically, we study the history of Stack Exchange, a large Q&A community that employs gamification. To the best of our knowledge, this is the first study of using award achievement history to find expertise in Q&A communities.     

The Contents-Based Website Classification for the Internet Advertising Planning: An Empirical Application of the Natural Language Analysis

This study proposes a model for website classification using website content, and discusses applications for the Internet advertising (ad) strategies. Internet ad agencies have a vast amount of ad-spaces embedded in websites and have to choose which advertisements are feasible for place. Therefore, ad agencies have to know the properties and topics of each website to optimize advertising submission strategy. However, since website content is in natural languages, they have to convert these qualitative sentences into quantitative data if they want to classify websites using statistical models. To address this issue, this study applies statistical analysis to website information written in natural languages. We apply a dictionary of neologisms to decompose website sentences into words and create a data set of indicator matrices to classify the websites. From the data set, we estimate the topics of each website using latent Dirichlet allocation, which is fast and robust method for sparse matrices. Finally, we discuss how to apply the results obtained to optimize ad strategies.     

Designing an Interactive Visualization to Explore Eye-movement Data

For many user applications large data sets may be collected passively and unobtrusively in the flow of their activity, and on scales ranging from the individual to increasingly larger communities. Large data sets, however, bring a concomitant need for tools to help understand what the data indicates. With the emergence of smart eyewear and the availability of sophisticated but affordable eye-tracking devices, eye movement data becomes a source of detailed information about a user’s focus and indirectly about their cognition and attention. Visualizing this usefully in terms meaningful for diagnosis however, remains a challenge. In this paper we report a new data representation from significant data sets generated by a gaze-controlled digital reading application for second language speakers. Current tools provide data sets aimed primarily towards statistical analysis of patterns: our focus is on end-user exploration of data sets in domain terms, so that practical implications can be readily identified. The visualization of horizontal eye movement data allows rapid diagnosis of problem areas in texts, informing educators immediately of individual or wider issues. The general applicability of this visualization to other applications is discussed.     

Research Note: A High Resolution Graph Viewer for Multi-monitor Visualization Environment

Bigdata analysis is a hot topic in all fields of science. Particularly in scientific fields investigating data relations, observation and analysis of relation among diverse data sets has begun to play a role of great importance. A graph is a representative expression for the purpose and many graph viewers and tools prevail today. However, most of these graph viewers do not offer the capability for displaying graphs on a multi-monitor visualization environment, even though multi-monitor visualization environment facilitates scientists in understanding data in a more detailed and intuitive manner. In this paper, our first exploration towards a high resolution graph viewer for a multi-monitor visualization environment is explored and reported.     

Correlation and Regression Analysis for Characterizations of a University Hospital

One of the most important issues in hospital management is how to determine the indicators for revenue of a large-scale hospital. Although it has been pointed out that the averaged value of length of stay in a hospital is an indicator of its revenue, quantitative evaluation has not been conducted. In this paper, we propose an analytic process based on methods for correlation and regression analysis to evaluate this indicator by using stored data in hospital information systems. We applied this method to data combined with discharge summaries and medical treatment fees, collected from 1997 to 2000 in Chiba University Hospital. The result shows that the length of stay can explain around 60-90% of the revenue during this period.     

对话于庆洲

实际上,我们现在所服务的行业,多方面已经实现了领跑者的理想。领跑者实际上就是要做别人没做、别人没想到的事情。我们要在客户还没想到的情况下,就提出解决方案。那时候客户才会猛然发现＂你的解决方案就是我想要的＂。     

A Conjoint Analysis of Demand for the Japanese Mobile Phone Market

The Japanese mobile phone market is 55.8% of the total market in the telecommunications industry. This paper is a conjoint analysis on Japanese consumer preferences for Japanese mobile phones. The analysis in this paper is presented after a questionnaire survey was given to 3,412 Japanese mobile phone users over 15 years old. The results of this analysis show that a decline in the price of mobile phone sets, an increase in transmission speed, the application of family discounts, and the continuation of contracts with the same telecommunication companies, all raise demand for mobile networks. In addition, the author found that user groups of NTT DOCOMO, au (KDDI), Softbank, and MVNO have different utility functions. According to the estimation of Mean Willingness to Pay (MWTP) in this paper, suppliers of mobile phone networks may be able to optimize and maximize demand by adjusting attributions and their levels.     

A Taxi Zoning Analysis Using Large-Scale Probe Data: A Case Study for Metropolitan Bangkok

Taxis are considered one of the most convenient means of transportation, especially when people have to travel off-route, where public transportation is not a feasible option, and also when they need to reach a destination according to what is most convenient for them. However, many issues exist about taxi services, such as the problems of passengers who are unable to get taxi service at the location of their choice, or problems concerning when they need the taxi service to arrive. These problems may be due to the unavailability of the taxi at that particular location or due to the taxi driver not wanting to provide service. A taxi driver may not want to provide service to a potential passenger, because they may have preferences on the direction and areas they want to go or because of the different types of service zoning. Understanding the behaviors of taxi drivers and the characteristics of the trip/travel might be helpful to solving such issues. In this study, we conducted an analysis from a questionnaire survey and large-scale taxi probe data to understand taxi service behavior, travel characteristics, and to discover taxi service zoning characteristics. As a result, four types of taxi service zones including isolated zones, interactive zones, special service zones, and target zones were encountered. Travel characteristics were calculated and analyzed at different criteria, such as weekdays, weekends, and various time windows in a single day. The result of these characteristics was explained according to their similarities and dissimilarities in each type of zone. The discovery of the different zones and their respective definitions might be a good initiative for further development of a policy for taxi drivers to provide better service for passengers.     

Research Note: Analysis of the Characteristics of Victims in Information Security Incident Damages: The Case of Japanese Internet Users

In this article, the authors investigate the attributes of victims in information security incident damages for the purpose of reducing the damages. The Information-Technology Promotion Agency, Japan, in 2010, conducted an Internet survey targeted to Japanese Internet home users entitled, “Survey of awareness toward information security incidents” that is used in this article. Using micro data collected from this survey, they employed multinomial logit regression analysis to show factors affecting the user’s experience of the incidents of damage through particular incidents. They concluded that the overconfidence regarding information security knowledge increased the probability for phishing and spoofing.     

An Exploratory Look at Supply Chains in Japan from Multiscale Network Perspectives

In social network analysis, advances in social networking and computing techniques have increasingly become a popular approach for extracting features and rules of real-world networks. The network language—\(G=\{V, E \}\) provides a common representation of various networks, where G, V, and E denote the system, components, and interactions, respectively. In this study, we employ this emerging technique to discuss supply chains in Japan. We construct the supply network (i.e., system) based on the firms (i.e., components) and their transactional relationships (i.e., interactions). In comparison with the traditional approaches of industrial sectors and regional clusters, this study represents an exploratory look at supply networks, and investigates different scales of supply networks from three perspectives. (1) In the macro-scale perspective, we evaluate the “small-world” separation of supply networks using average path length. (2) In the meso-scale perspective, we detect communities of the supply networks, which can be marked for cross-location and cross-industry features. (3) In the micro-scale perspective, we investigate the “scale-free” nature of supply networks and each community using node degree-prior connections, which can find “hub” firms and simultaneously estimate the robustness of supply networks using a sequential elimination choice strategy of these hubs.     

Subcontracting Structure and Productivity in the Japanese Software Industry

This paper presents an empirical analysis of the factors determining the productivity of the software industry in Japan, using individual data from the Survey of the State of the Information Service Industry conducted in August 2006 by IPA (Information-Technology Promotion Agency, Japan). This paper focuses on the relationship between the subcontracting structure and productivity in the Japanese software industry. Software enterprises are classified as prime contractors, intermediate subcontractors, end-contractors, and independent enterprise. A comparison of their productivity levels reveals that intermediate subcontractors are the least productive. However, it is observed that the intermediate subcontractors possessing a high quality of human resources measured the proportion of employees passing the Information Technology Engineers Examination (ITEE), or the intermediate subcontractors adopting the IT skill standard which defines the skills for IT human resources clearly and systematically, has a high productivity level. It can raise the productivity in software industry as a whole.     

Data Mining Approach for Direct Marketing of Banking Products with Profit/Cost Analysis

Nowadays, many businesses, such as banks, use direct marketing methods to reach customers to minimize the campaigning cost and maximize the return rate. To achieve this, huge customer data should be analyzed to determine the most appropriate product offer for each customer and the most effective channel to reach her/him. However, since only a very small amount of responses collected from the customers are positive to the offers, the dataset is very imbalanced. This decreases sensitivity ratio of prediction results and makes it difficult to make a successful product and channel selection for the offer. In this paper, we propose a hybrid system, which first classifies the customers to decide if s/he is interested in the offered product, and then clusters them for product and channel suggestions. Experiments with real life banking data show very promising accuracy results for predicting the proper product and channel for the customers. Moreover, cost-profit analysis is also added to this problem. Our experiment results show that the proposed method decreases a fraction of the total profit, but since the decrease in the total cost is very large, there is a huge increase in the overall profit/cost ratio.     

An Emergency Evacuation Planning Model Using the Universally Quickest Flow

In recent years, catastrophic disasters by massive earthquakes have been increasing in the world, and disaster management is required more than ever. In the case of disasters such as tsunamis, a slight delay in evacuation may deprive evacuees of life. In this article, we formalize the emergency evacuation planning model for evacuation from tsunamis and other disasters based on the idea of the universally quickest flow. We show that there does not always exist a universally quickest flow when the capacity constraint of refuges is taken into account. Therefore, we propose an alternative criterion that approximates a universally quickest flow, and presents an algorithm for finding an optimal flow for this criterion. Numerical experiments are carried out for the evacuation of a local city in Japan where tsunami damages are assumed to occur when a large earthquake occurs in the ocean nearby.     

Parallel Consultant-Guided Search with Crossover

Consultant-guided search (CGS) is a recent metaheuristic method. This approach is an algorithm in which a virtual person called a client creates a solution based on consultation with a virtual person called a consultant. In this study, we propose a parallel CGS algorithm with a genetic algorithm’s crossover and selection, and calculate an approximation solution for the traveling salesman problem. We execute a computer experiment using the benchmark problems (TSPLIB). Our algorithm provides a solution with less than 3.3% error rate for problem instances using less than 6000 cities.     

A Pricing Strategy with Consumption Externality when the Reference Group is Large

This paper provides an analysis of firms’ optimal prices when individual utility exhibits both material and other consumer effects. We construct a model and conduct an analysis in the following four steps: (1) By using a conjoint analysis of data, we set up a hierarchical Bayesian model and estimate its parameters, which are composed of individual utility functions. (2) We calculate the number of sales in each time period and derive the total sales throughout the given period. (3) We estimate the demand functions in the presence and absence of consumption externalities. (4) Finally, we calculate the profit functions and derive the optimal prices taking into account various product attributes. By applying our analysis to the book market of Japan, we find that the optimal price is lower when an externality is present than when absent. The intuition behind this result is that pricing low and selling a large number of books from an early stage increases the externality effect, yielding a higher profit for firms.     

Facebook e-Portfolios for Career Education Focused on Japanese Employment Practice: A Case Study

The authors propose the effectiveness of Facebook functions in the promotion of career education. In recent years, career education in Japanese universities has differed slightly from that in other countries. Japanese students are trained to be competitive in the job-hunting process; they need to obtain the technical skills and knowledge necessary to pass a company entrance examination or a university oral interview. This practice is in stark contrast with the intrinsic meaning of vocational/career education, which is the process by which students acquire the abilities and independence required by a certain industry. This meaning is manifested in the purpose of the career education program of Hokkai-Gakuen University’s Faculty of Business Administration. The program’s purpose is to foster independence in its students rather than the acquisition of skills for the job-hunting process. The professional independence of every student is important to their career development after graduating from the university. On the other hand, it is known that e-portfolios generally encourage students to record and assess their activities. To promote the activities that students tackle in the program, we introduced an e-portfolio using Facebook. This study shows the characteristics and achievements of our e-portfolio.     

Simulation Analysis of a Dynamic Reallocation-based Routing Functionality for SAGE Application

A large amount of scientific data is generated through computation and analysis. Also, today’s scientific research necessitates an aggregation of diverse expertise from experts with different backgrounds. Therefore, visualizing and sharing these data among scientists in an intuitive and easy manner is of more importance in scientific collaborative research than ever. We have focused on SAGE, a middleware that realizes a large-scale remote visualization leveraging network streaming technique as a promising building block technology. However, no advanced network control function for efficient use of the network is equipped with SAGE although SAGE relies on a network streaming techniques. Our previous research integrated a functionality that detected network failures avoided such failure by rerouting network flows of SAGE into the functionality. Nonetheless, a network congestion avoidance functionality to adapt a collection of network flows generated by SAGE to the underlying network has not been developed yet. In this paper we explore the feasibility of a reallocation-based dynamic routing functionality for SAGE, with which all network flows on the network are rearranged. For feasibility research, we perform simulation experiments to observe the behavior of the functionality. The evaluation confirms that our proposed functionality works correctly and brings better throughput for each flow.     

Comments’ Extraction by User ID,Keywords, and Anchor Texts from the Thread of a Bulletin Board System

Bulletin Board Systems (BBSs) on the Web are used by many users posting comments on threads. Each thread carries a subject of discussion. Most users post comments related to a subject. However, unrelated comments are also posted. The unrelated comments distract users and diminish their understanding of the entire story of a thread. Comments unrelated to a subject have to be filtered automatically. This paper proposes a method that extracts comments related to a thread subject from a thread of BBS. The method extracts two types of comments: comments related to a thread subject (main comments), and comments related to main comments (sub-comments). The main comments are extracted by a user ID and keywords in the comments. The sub-comments are extracted by explicit and implicit anchor texts in the comments. We experimented with the proposed method and verified that comments extracted by the proposed method support participants in understanding the entire story of a thread.     

The Boosting Effect of E-WOM on Macro-level Consumption: A Cross-Industry Empirical Analysis in Japan

In this study, we carry out an empirical analysis on how electronic word-of-mouth (hereinafter “e-WOM”) marketing on e-WOM websites and electronic-commerce websites on the Internet boosts consumption on a macro-level. In our analysis, we conduct a model analysis of consumer behavior using data composed of more than 30,000 questionnaire surveys and quantitatively find the elasticity coefficient of the boost to consumption by performing a two-step GMM (generalized method of moments), which uses instrumental variables. The results of the analysis show e-WOM significantly increased expenditures in six fields: computers, electrical appliances, etc.; music; hobbies; clothing, accessories, etc.; beauty products, etc.; and goods for everyday life, etc. Furthermore, there was no field that had a significantly negative value. These results showed that, in the majority of the target fields, e-WOM had not only the effect of winning customers from the competition, but also the effect of boosting consumption on a macro-level. In addition, even from people’s subjective evaluations, there were many in all the generational groups who said that e-WOM boosted expenditures.