10012054
A development environment for customer-oriented Internet business: eBizBench
Abstract An important challenge in the age of Internet business is the proper alignment of customers’ needs with the business system. In order to improve an Internet business system according to customers’ needs continuously, reuse of design results is of particular importance. This paper proposes a development environment, called eBizBench, which provides support for this alignment and reusability. The eBizBench includes seven functions: (1) project management, (2) customer analysis, (3) value analysis, (4) web design, (5) implementation design, (6) repository management, and (7) repository. The eBizBench can help develop and maintain Internet business systems in a systematic fashion. The repository is useful for the conversion of design results among development environments. A real-life web site is illustrated to demonstrate the usefulness of the eBizBench.
13929475
Effects of Web retail service quality and product categories on consumer behavior: a research model and empirical exploration
This paper explores how Web retail service quality at the point of purchase influences consumers' perceptions of value and willingness to buy. In particular, this study highlights how Web retail service quality has different effects on perceived product quality, value, and willingness to buy according to product categories. We provide a research model on the basis of service quality, product categories on the Web, and marketing theories for consumers' purchase behavior. Consumer perceptions of Web retail service quality are collected from a sample of shoppers who actively search for products over the Internet. The results imply that functional Web retail service quality has a direct effect on willingness to buy and technical Web retail service quality influences consumer perceptions of product quality and value. Furthermore, product categories moderate the relationships among Web retail service quality, perceived product quality, perceived value, and willingness to buy. Implications for Internet marketing and future research directions are discussed.
206110402
Knowledge management strategy and its link to knowledge creation process
Abstract Knowledge has become to be considered as valuable strategic assets that can provide proprietary competitive advantages. It is more important for companies to distinguish themselves through knowledge management strategies. Without a constant creation of knowledge, a business is condemned to poor performance. However, it is still unclear how these strategies affect knowledge creation. Knowledge management strategies can be categorized as being either human or system oriented. This paper proposes a model to illustrate the link between the strategies and its creating process. The model is derived on the basis of samples from 58 Korean firms. The model depicts how companies should align the strategies with four knowledge creation modes such as socialization, externalization, combination, and internalization. It is found that human strategy is more likely to be effective for socialization while system strategy is more likely to be effective for combination. Furthermore, the survey result suggests that managers should adjust knowledge management strategies in view of the characteristics of their departments.
11364385
An organizational memory for facilitating knowledge: an application to e-business architecture
Abstract Our economy is increasingly dependent on knowledge. Organizational memory (OM) contains knowledge that companies need to manage. This paper proposes a knowledge facilitating organizational memory (KFOM) to decipher a harmony mechanism of OM from the Oriental Yin and Yang perspective. KFOM clarifies an architecture to catapult the OM to organizational effectiveness. This architecture is made up of two layers: storage layer and facilitation layer. Storage layer represents task and domain knowledge. Facilitation layer identifies the harmony mechanism for utilizing knowledge. This harmony mechanism leverages the knowledge chain with agent, collaborator, transactor, object and registry facilitators. In order to demonstrate its practical usefulness, we explore how KFOM can sharpen an international e-business technical standard. Furthermore, an extension to a real-life B2B collaboration project for Korean steel and automotive companies confirms that KFOM can lead to business practices which most knowledge-oriented companies can adopt.
42601258
On the Optimality of Holistic Algorithms for Twig Queries
Streaming XML documents has many emerging applications. However, in this paper, we show that the restrictions imposed by data streaming are too restrictive for processing twig queries – the core operation for XML query processing. Previous proposed algorithm TwigStack is an optimal algorithm for processing twig queries with only descendent edges over streams of nodes. The cause of the suboptimality of the TwigStack algorithm is the structurally recursions appearing in XML documents. We show that without relaxing the data streaming model, it is not possible to develop an optimal holistic algorithm for twig queries. Also the computation of the twig queries is not memory bounded. This motivates us to study two variations of the data streaming model: (1) offline sorting is allowed and the algorithm is allowed to select the correct nodes to be streamed and (2) multiple scans on the data streams are allowed. We show the lower bounds of the two variations.
17009479
Bidirectional hierarchical clustering for Web mining
We propose a new bidirectional hierarchical clustering system for addressing challenges of Web mining. The key feature of the approach is that it aims to maximize the intra-cluster similarity in the bottom-up cluster-merging phase and it ensures to minimize the inter-cluster similarity in the top-down refinement phase. This two-pass approach achieves better clustering than existing one-pass approaches. We also propose a new cluster-merging criterion for allowing more than two clusters to be merged in each step and a new measure of similarity for taking into consideration not only the inter-connectivity between clusters but also the internal connectivity within the clusters. These result in reducing the average complexity for creating the final hierarchical structure of clusters from O(n/sup 2/) to O(n). The hierarchical structure represents a semantic structure between concepts of clusters and is directly applicable to the future of semantic net.
38524318
Making Sense of Search Results by Automatic Web-page Classifications
This paper reports the development of a system for automatically organizing Internet web pages into meaningful categories. The aim of the system is to allow Internet users to find useful information in less time. The current problem with using the Internet is how to find the information that we need. With the explosive growth in the Internet, the information overload situation is getting worse. The proposed system automatically classifies web pages based on three types of information: (1) The system analyzes organizational information among web pages (inter-web-page relationship), such as an URL and links within a web page. (2) It analyzes the meta-web-page information such as data contained in META tags and formatting data of a web page. And (3), it analyzes web-page-content information such as keywords and phrases in the content of a web page. Our results show that combining all three types of information provides better accuracy.
10179927
Automatic web page classification in a dynamic and hierarchical way
Automatic classification of web pages is an effective way to deal with the difficulty of retrieving information from the Internet. Although there are many automatic classification algorithms and systems that have been proposed, most of them ignore the conflict between the fixed number of categories and the growing number of web pages going into the system. They also require searching through all existing categories to make any classification. We propose a dynamic and hierarchical classification system that is capable of adding new categories as required, organizing the web pages into a tree structure, and classifying web pages by searching through only one path of the tree structure. Our test results show that our proposed single-path search technique reduces the search complexity and increases the accuracy by 6% comparing to related algorithms. Our dynamic-category expansion technique also achieves satisfying results on adding new categories into our system as required.
7584097
An Adaptive Web Cache Access Predictor Using Neural Network
This paper presents a novel approach to successfully predict Web pages that are most likely to be re-accessed in a given period of time. We present the design of an intelligent predictor that can be implemented on a Web server to guide caching strategies. Our approach is adaptive and learns the changing access patterns of pages in a Web site. The core of our predictor is a neural network that uses a backpropagation learning rule. We present results of the application of this predictor on static data using log files; it can be extended to learn the distribution of live Web page access patterns. Our simulations show fast learning, uniformly good prediction, and up to 82% correct prediction for the following six months based on a one-day training data. This long-range prediction accuracy is attributed to the static structure of the test Web site.