A Collaborative Platform to Support the Enterprise 2.0 in Active Interactions with Customers

In recent years a new model of Enterprise 2.0, which interacts actively with customers using web 2.0 tools (chat, forum, blog, wiki), is developing. The enterprises, listening opinions and suggestions of customers, can improve the product/service. For a company, customer's opinions are very important both for the improvement of products and also for the reinforcement of the customer loyalty. The customer will be motivated to be loyal if the enterprise shows a strong attention to his/her needs. This paper presents a model of a collaborative and interactive platform that supports the Enterprise 2.0 in the management of communications and relationships with all stakeholder of the supply chain and in particular with customers. A good e-reputation of the company improves business performances

TEXTUAL DATA MINING FOR NEXT GENERATION INTELLIGENT DECISION MAKING IN INDUSTRIAL ENVIRONMENT: A SURVEY

This paper proposes textual data mining as a next generation intelligent decision making technology for sustainable knowledge management solutions in any industrial environment. A detailed survey of applications of Data Mining techniques for exploiting information from different data formats and transforming this information into knowledge is presented in the literature survey. The focus of the survey is to show the power of different data mining techniques for exploiting information from data. The literature surveyed in this paper shows that intelligent decision making is of great importance in many contexts within manufacturing, construction and business generally. Business intelligence tools, which can be interpreted as decision support tools, are of increasing importance to companies for their success within competitive global markets. However, these tools are dependent on the relevancy, accuracy and overall quality of the knowledge on which they are based and which they use. Thus the research work presented in the paper uncover the importance and power of different data mining techniques supported by text mining methods used to exploit information from semi-structured or un-structured data formats. A great source of information is available in these formats and when exploited by combined efforts of data and text mining tools help the decision maker to take effective decision for the enhancement of business of industry and discovery of useful knowledge is made for next generation of intelligent decision making. Thus the survey shows the power of textual data mining as the next generation technology for intelligent decision making in the industrial environment

Software Inspection Team Formation Based on the Learning Style of Individual Inspectors

To improve the software quality, researchers have focused their effort on developing and validating effective methods of finding and fixing defects early in the development process. Software inspections are most widely used defect detection method. Also, researchers showed that the overall effectiveness of an inspection team is affected by the effectiveness of individual inspectors. But researchers have not been able to completely understand the inherent characteristic that makes an individual inspector effective. This paper investigates this problem by analyzing the learning style (LS) preferences of individuals who make up inspection team. Also presents a tool that provides ability to researchers to study the relationship between inspectors? LS and his/her effectiveness in uncovering defects in software requirement document. Cluster and Discriminant analysis techniques were used to sort inspection teams based on their LS preferences. Researchers can use this tool to study further correlations between inspector?s LS and their performance in team

The Automation of Software Development Metrics

With the push to streamline medical records and the use of electronic medical records system technology on the rise, successful implementation is important. The push is due in part for the need to reduce unnecessary paperwork, increase reimbursement, increase quality of medical records and increase overall quality of care. Factors to consider are the effects of implementation on quality of care, quality of medical records, physician and staff perceptions, working conditions, patient satisfaction, cost and barriers. Implementation may have a positive, negative or neutral effect on these factors making the need to review literature and report outcomes significant

Analysis of relationship between software metrics and process models

This thesis studies the correlation between software process models and software metrics. To support our studies we have defined a Process - Metric Evaluation Framework and derived an evaluation template from it. The template served as a basic tool in studding the relationships between various process models, artifacts and software metrics. We have evaluated a number of process models according to our template and have identified suitable software metrics. We have also recommended a root cause analysis approach at various points of the process models. The suggested software metrics can be derived from various product and process artifacts. They can be used to curb the risks generated at each phase of the development process, identify issues, and do better planning and project management. The evaluation template can also be used to evaluate other models and identify effective metrics