Electronic word of mouth analysis for service experience

Since eWOM provides a rich source of objective information about products or services, it has become one of the major ways in which consumers collect information about items they are interested in buying. However, the problem of eWOM overload makes it difficult to effectively collect this information, and may have adverse effects on their actual purchase behavior. eWOM content is characterized by unstructured text formats, oversimplified expressions, and newly coined phrases (textspeak), and these all contribute to the challenges that arise when analyzing eWOM. This study thus proposes an eWOM analysis method for analyzing eWOM, which may lead to a more effective method for analyzing eWOM content, extracting both positive and negative appraisals, and help consumers in their decision making. At the same time, the method proposed in this study can also be utilized as a tool to assist companies in better understanding product or service appraisals, thus translating these opinions into business intelligence and as the basis for product/service improvements.     

Knowledge-based manufacturability assessment: an object-oriented approach

To help the achievement of integrated product and process development, there is a need for tools that can assist designers in creating manufacturable parts with less design routines and tryouts. This paper presents a systematic approach to developing automated manufacturability assessment tools by identifying the functional and informational requirements and proposing an assessment model. The work presented in this paper includes: (1) identification of characteristics and tasks of design for the die-casting process; (2) determination of functional and informational requirements for automatic manufacturability assessment; (3) formalization and modularization of assessment knowledge; and (4) modeling of product definition data to support the assessment. Object-oriented techniques are employed to model the assessment knowledge and manage the complicated and diverse types of product definition data by taking advantage of data abstraction, modularity, inherent concurrence, and the concept of encapsulation and extendibility.     

Development of technology for customer requirement-based reference design retrieval

Engineering design is a knowledge-intensive process, and includes conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each task involves various aspects of knowledge and experience. Whether this knowledge and experience can be effectively shared is key to increasing product development capability and quality, and also to reducing the duration and cost of the development cycle. Therefore, offering engineering designers various query methods for retrieving engineering knowledge is one of the most important tasks in engineering knowledge management.The study develops a technology for customer requirement-based reference design retrieval to provide engineering designers with easy access to relevant design and associated knowledge. The tasks involved in this research include (i) designing a customer requirement-based reference design retrieval process, (ii) developing techniques related to the technology for customer requirement-based reference design retrieval, and (iii) implementing a customer requirement-based reference design retrieval mechanism. The retrieval process comprises the steps of customer requirement-based query, case searching and matching, and case ranking. The technology involves (1) a structured query model for customer requirement, (2) an index structure for historical design cases, (3) customer requirement-based case searching and matching mechanisms, (4) a customer requirement-based case ranking mechanism, and (5) a case-based representation of designed entities.     

Authenticated encryption schemes with message linkages for message flows

Two efficient authenticated encryption schemes with message linkages are proposed. One is a basic scheme, that it has the better performance in comparison with the all previously proposed schemes in terms of the communication and the computation costs. However, it has a property as same as the previously proposed schemes, that the message blocks can be recovered only after the entire signature blocks have been received. Therefore, the basic scheme is applicable to encrypt all-or-nothing flow. Thus, we improve the basic scheme and also propose a generalized scheme, which allows the receiver to recover the partial message blocks before receiving the entire signature blocks. That is, the receiver may perform the receiving and the recovering processes simultaneously. Therefore, the generalized scheme is applicable to message flows. The generalized scheme requires smaller bandwidth and computational time as compared to the previously proposed authenticated encryption schemes with message linkages for message flows.     

Developing a multi-layer reference design retrieval technology for knowledge management in engineering design

Engineering design is a knowledge-intensive process that encompasses conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each of these tasks involves various areas of knowledge and experience. The sharing of such knowledge and experience is critical to increasing the capacity for developing products and to increasing their quality. It is also critical to reducing the duration and cost of the development cycle. Accordingly, offering engineering designers various methods for retrieving engineering knowledge is one of the most important tasks in managing engineering knowledge.

This study develops a multi-layer reference design retrieval technology for engineering knowledge management to provide engineering designers with easy access to relevant design and related knowledge. The tasks performed in this research include (i) designing a multi-layer reference design retrieval process, (ii) developing techniques associated with multi-layer reference design retrieval technology, and (iii) implementing a multi-layer reference design retrieval mechanism. The retrieval process contains three main phases—‘customer requirement-based reference design retrieval’, ‘functional requirement-based reference design retrieval’ and ‘functional feature-based reference design retrieval’. This technology involves (1) customer requirement-based reference design retrieval, which involves a structured query model for customer requirements, a case-based representation of designed entities, a customer requirement-based index structure for historical design cases, and customer requirement-based case searching, matching and ranking mechanisms, (2) functional requirement-based reference design retrieval, which includes a structured query model for functional requirements, a functional requirement-based index structure for historical design cases, and functional requirement-based case searching, matching and ranking mechanisms, and (3) functional feature-based reference design retrieval, which is a binary code-based representation for functional features, an ART1 neural network for functional feature-based case clustering and functional feature-based case ranking.     

Gene selection and sample classification on microarray data based on adaptive genetic algorithm/k-nearest neighbor method

Recently, microarray technology has widely used on the study of gene expression in cancer diagnosis. The main distinguishing feature of microarray technology is that can measure thousands of genes at the same time. In the past, researchers always used parametric statistical methods to find the significant genes. However, microarray data often cannot obey some of the assumptions of parametric statistical methods, or type I error may be over expanded. Therefore, our aim is to establish a gene selection method without assumption restriction to reduce the dimension of the data set. In our study, adaptive genetic algorithm/k-nearest neighbor (AGA/KNN) was used to evolve gene subsets. We find that AGA/KNN can reduce the dimension of the data set, and all test samples can be classified correctly. In addition, the accuracy of AGA/KNN is higher than that of GA/KNN, and it only takes half the CPU time of GA/KNN. After using the proposed method, biologists can identify the relevant genes efficiently from the sub-gene set and classify the test samples correctly.     

On technology for functional requirement-based reference design retrieval in engineering knowledge management

Engineering design is a knowledge-intensive process, and includes conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each of these tasks involves various aspects of technical knowledge and experience. Whether this technical knowledge and experience can be effectively shared is key to increasing product development capability and quality, and also to reducing the duration and cost of the development cycle. Consequently, providing engineering designers various query methods for retrieving engineering knowledge is one of the most important tasks in engineering knowledge management.The study develops a technology for functional requirement-based reference design retrieval as a decision support mechanism, which can assist engineering designers to retrieve relevant design and associated knowledge for reference in conducting functional requirements of a product. This study involves the following tasks: (i) designing a functional requirement-based reference design retrieval process, (ii) developing techniques related to the technology for functional requirement-based reference design retrieval, and (iii) implementing a functional requirement-based reference design retrieval mechanism. The retrieval process includes the steps of functional requirement-based query, case searching and matching, and case ranking. The technology involves (i) a structured query model for functional requirements, (ii) an index structures for historical design cases, (iii) functional requirement-based case searching and matching mechanisms, (iv) a functional requirement-based case ranking mechanism, and (v) a case-based representation of designed entities. Finally, the experimental example with indexing and retrieving similar designed entities is conducted to demonstrate the proposed techniques worked efficiently.     

Projection-based partial periodic pattern mining for event sequences

Partial periodic pattern mining is one of the important issues in the field of data mining due to its practical applications. A partial periodic pattern consists of some periodic and non-periodic events in a specific period length, and is repeated with high frequency in an event sequence. In the past, a max-subpattern hit set algorithm was developed to discover partial periodic patterns, but its drawback is spending a large amount of time in calculating frequency counts from the redundant candidate nodes. In this study, we thus adopt an efficient encoding strategy to speed up the efficiency of processing period segments in an event sequence, and combined with the projection method to quickly find the partial periodic patterns in the recursive process. Finally, the experimental results show the superior performance of the proposed approach.