Zhongqi Sheng

Visualized Technique for Trend Analysis of News Articles

In order to visualize keyword trends in texts of news articles, this paper proposes a method named FACT-Graph by extending co-occurrence graph. The method uses four classes of keywords, considers three patterns of class transitions, and expresses three types of co-occurrence relationships between two analysis periods. Classes of keywords are characterized by the shapes of their nodes, the transition patterns of keyword classes are shown by the colors of the nodes, and the co-occurrences relationships between two keywords are represented by the types of edges their nodes have. FACT-Graph is applied to a sample of 220,000 newspaper articles and is found to be effective in visualizing keyword trends embedded in volumes of text data.

FACT-Graph: Trend Visualization by Frequency and Co-occurrence

In order to visualize keyword trends embedded in documents, this paper proposes FACT-Graph (Frequency and Co-occurrence-based Trend Graph). First, we introduce four classes of keywords by TF (Term Frequency) and DF (Document Frequency). Then while some keywords stay in the same class between two periods, others stay in the difference classes. Paying attention to such class transition between periods, we make it a clue of trend analysis. Next, we identify relationship between keywords by their co-occurrence strength and their transition between two periods. Then, we propose FACT-Graph by combining class transition information and co-occurrence transition information. Finally, an application to newspaper article is also discussed.

Risk bias externalization for offshore software outsourcing by conjoint analysis

With the steady increase of volumes of software development, most Japanese companies are interested in offshore software outsourcing. In order to find out the know-how of experienced project managers and assess the risk bias brought by vendor countries and software types, this paper utilizes conjoint analysis method on questionnaire for project preference to externalize the tacit knowledge. After analyzing the range, maximum, minimum and average value of total utilities of three kinds of properties, we have the following findings: 1) the project property is the main item affecting success of outsourcing projects, which could lead to big success or severe failure, 2) the risk analysis result for vendors of India is different from that of China, which should be deeply investigated, 3) the risk value of middleware software is lower than that of the other two software types, which should be paid more attention to.

Preliminary Analysis for Risk Finding in Offshore Software Outsourcing from Vendor’s Viewpoint

It is meaningful to investigate the know-how of experienced project managers on the side of vendors about the risk in offshore software outsourcing. A survey is conducted to find out the main risk factors from the vendor’s viewpoint. The questions asked include background information of vendor and respondent, suggestions to the client, and evaluations on experienced offshore projects. In all, 131 respondents from 77 vendors evaluate 241 offshore software outsourcing projects upon 30 items. The background information about the respondents and the vendors is summarized first. The preliminary analysis on the characters and the achievements of experienced offshore projects is reported in this paper. Some conclusions are drawn at last.

Visualization Study of the Relationships between Responses in Choice-Type Questionnaire

Questionnaire is often used to investigate the respondent’ s opinion toward some product or service. To realize the knowledge mining from response data of questionnaire, this paper proposes one kind of visualization technique based on frequency analysis together with co-occurrence analysis. In created visualization graph, the nodes express the result of frequency analysis and the links between nodes show the result of co-occurrence analysis. Different from traditional co-occurrence analysis in which single case of the respondent’ s attribute such as age and gender is focused on, proposed technique allows to integrate the information of two graphs about two cases of an attribute in single graph. Appling this technique to an example dataset including two attributes and five questions, this paper discusses the applicability and limitation of this visualization technique.

Correlation-based similarity metrics in MBR for ordered data

To improve the precision of memory-based reasoning (MBR) for ordinal data, this article presents correlation-based similarity metrics. The basic idea of this research is an intuitive assumption: if the correlation between the answer and one feature in a sample data set is large, the weight of this feature for predication should be large. To validate this proposal, we promote “leave-one-out cross-validation” for 53 examples which were collected from Japanese client companies who outsource software development to vendor companies. Three measures, including mean absolute error, variance of error, and precision, are compared among the proposed methods: the per-category feature importance (PCF), the per-feature category importance (PFC), the averaged category feature importance (ACF), and the cross-category feature importance (CCF). The Wilcoxon matched-pairs signed ranks test is also discussed.

Quantitative Research on Causes of Channel Conflict Based on Analytic Hierarchy Process

This paper analyzes the causes of channel conflict based on Analytic Hierarchy Process (AHP) quantitatively. In the viewpoint of the system, the causes of channel conflict are divided into a number of factors according to the corresponding relations of domination. A hierarchical structure model is established, on which a quantitative research is carried out to investigate the causes of channel conflict using AHP. The main causes of channel conflict are found out and the suitable quantitative data is offered for the decision-making.

Dynamic Management System of Channel Conflict and Early Warning

Channel conflict is changed with the changes of internal and external environment, and presents dynamic characteristic, so the management of channel conflict should also be dynamic management. This paper discusses channel conflict dynamic management system based on the related channel conflict management. Considering the channel conflict’s strong penetration and diffusion effect, it would cause great losses of enterprises once it happens, therefore, the best channel conflict management is to prevent and control conflict before channel conflict breaks out. This paper introduces the idea of early warning management, selects reasonable early warning indicators, and uses the related early warning method to monitor the channel conflict, effectively measure and identify potentially destructive channel conflict, which has targeted to take appropriate measures to prevent channel conflict, and eliminating destructive channel conflict in the incubation period.

Knowledge Mining for Risk Analysis of Offshore Software Development

Offshore software development is playing an increasingly important role in the technology strategies of software companies in the era of globalization and specialization. It is a significant task to analyze the risk for the success of offshore software development projects. This paper introduces two kinds of questionnaire designed to realize the knowledge miming of offshore software development from experienced project managers in the side of both clients and vendors. Knowledge mining methods used in questionnaire analysis are presented together with some analysis examples. The research is summarized and future work is given at last.