How have Japanese companies become world leaders in the automotive and electronics industries, among others? What is the secret of their success? Two leading Japanese business experts, Ikujiro Nonaka and Hirotaka Takeuchi, are the first to tie the success of Japanese companies to their ability to create new knowledge and use it to produce successful products and technologies. In The Knowledge-Creating Company, Nonaka and Takeuchi provide an inside look at how Japanese companies go about creating this new knowledge organizationally. The authors point out that there are two types of knowledge: explicit knowledge, contained in manuals and procedures, and tacit knowledge, learned only by experience, and communicated only indirectly, through metaphor and analogy. U.S. managers focus on explicit knowledge. The Japanese, on the other hand, focus on tacit knowledge. And this, the authors argue, is the key to their success--the Japanese have learned how to transform tacit into explicit knowledge. To explain how this is done--and illuminate Japanese business practices as they do so--the authors range from Greek philosophy to Zen Buddhism, from classical economists to modern management gurus, illustrating the theory of organizational knowledge creation with case studies drawn from such firms as Honda, Canon, Matsushita, NEC, Nissan, 3M, GE, and even the U.S. Marines. For instance, using Matsushita's development of the Home Bakery (the world's first fully automated bread-baking machine for home use), they show how tacit knowledge can be converted to explicit knowledge: when the designers couldn't perfect the dough kneading mechanism, a software programmer apprenticed herself withthe master baker at Osaka International Hotel, gained a tacit understanding of kneading, and then conveyed this information to the engineers. In addition, the authors show that, to create knowledge, the best management style is neither top-down nor bottom-up, but rather what they call "middle-up-down," in which the middle managers form a bridge between the ideals of top management and the chaotic realities of the frontline. As we make the turn into the 21st century, a new society is emerging. Peter Drucker calls it the "knowledge society," one that is drastically different from the "industrial society," and one in which acquiring and applying knowledge will become key competitive factors. Nonaka and Takeuchi go a step further, arguing that creating knowledge will become the key to sustaining a competitive advantage in the future. Because the competitive environment and customer preferences changes constantly, knowledge perishes quickly. With The Knowledge-Creating Company, managers have at their fingertips years of insight from Japanese firms that reveal how to create knowledge continuously, and how to exploit it to make successful new products, services, and systems.

The knowledge-creating company

The international journal of lexicography

Web mining is the extraction of interesting and potentially useful patterns and hidden information from web documents and web activities by applying data mining technology. The most important challenge of electronic commerce (E-commerce) is to understand as much as possible the customers’ wants, desires, and buying patterns to ensure competitiveness in the E-commerce era. Nowadays, any information related to consumer behavior has an important value in the highly competitive nature of the E-commerce market. Therefore, web mining can be used to find those obvious data that have potential value to reduce competition and simultaneously increase business profit. This paper aims to study the classification of web mining to extract customer behavior in E-commerce, investigate customer behavior through the techniques and processes of the web data mining used, explore the application of web mining in Ecommerce, and increase profit.

/pdf/a-study-of-customer-behaviour-through-web-mining-20lm72gx7e.pdf

A Study of Customer Behaviour Through Web Mining

Received: 07/Nov/2017, Revised: 19/Nov/2017, Accepted: 14/Dec/2017, Published: 31/Dec/2017 AbstractThis paper attempts to determine the veiled information and identifying user behavior on the web by using the web data sources. With the help of this information, Prediction of user behavior can be done very easily. The user pattern is analyzed by applying the free tool similar web and page score on the website of the particular organization. This tool tries to conduct web mining in a domain independent manner. The experimental results provide an easier way to navigate the website and improve the website design architecture. This work deliberates the detailed results of a website in a specific education domain application. The main objective of conducting the study on websites of the different universities is to discern the pattern of behavioural expressions and user characteristics so that the organization can improve the structure of website and can upload the more information in a proper way.

/pdf/customer-behaviour-analysis-using-web-usage-mining-i6yaekh8w7.pdf

Customer Behaviour Analysis using Web Usage Mining

Vehicular Edge Computing (VEC) provides users with low-latency and highly responsive services by deploying Edge Servers (ESs) close to applications. In practice, vehicles are usually moving rapidly. To ensure the continuity of services, edge service migration technology is in high need, by which an application, infrastructure or any edge-hosted applications or services are not locked into a single vendor and allowed to shift between different edge resource vendors. Nevertheless, due to their complex and dynamic nature, real edge computing environments are error and fault prone and thus the reliability of edge service migrations can be easily compromised if the proactive measures are not taken to counter failures at different levels. In this paper, we propose a novel fault-tolerant approach for Dynamic Redundant Path Selection service migration (DRPS). The DRPS approach consists of path selection algorithm and service migration algorithm. The path selection algorithm is capable of evaluating time-varying failure rates of ESs by leveraging a sliding window-based model and identifying a set of service migration paths. The service migration algorithm incorporates resubmission and replication mechanisms as well and decides edge service migration schemes by choosing multiple redundant migration paths. We also conduct extensive simulations and show that our proposed method outperforms traditional solutions by 17.45%, 13.17%, and 7.22% in terms of ACT, TCR, and AFC, respectively.

/pdf/a-novel-fault-tolerant-approach-for-dynamic-redundant-path-3aoxelkm.pdf

A Novel Fault-Tolerant Approach for Dynamic Redundant Path Selection Service Migration in Vehicular Edge Computing

Resource utilization and cost optimization oriented container placement for edge computing in industrial internet

In practice area, with the globalization as well as the knowledge economy era's coming, enterprises are realizing the importance of knowledge management. More and more enterprises started implementing knowledge management. Knowledge Management includes a flexible and effective integration of specific content management, cooperation mechanisms and data analysis functionalities. In the paper an overview of knowledge management is given and the definition and concept is introduced. Then the detailed research on the process of knowledge innovation and some measures of knowledge innovation management are presented.

Research on Knowledge Management in Enterprise

In order to provide the personal service for online system, a personalized recommendation system framework based on web mining is proposed. Individual recommendations in accordance with user’s custom and interest can improve the quality of service.

A Studying System Based on Web Mining

Most of the current framework for Web services are based on keyword matching, Web services which contains semantics multiplicity still cannot realize service discovery and bind automatically. To solve the lack of efficient discovery mechanism for Web service, a semantic web technology based Web services discovery approach is presented. A semantic based index in the services registry to improve the lower matching efficiency of traditional services semantic matchmaking model is built. The multilayer flexible matchmaking mechanism according to the model is also proposed in the paper. The mechanism fully utilizes the semantic information to improve the accuracy of services matching.

A Semantic-Based Multilayer Flexible Mechanism for Matching Web Services

To determine the target users of a company, a new data mining model is proposed. The new method can serve as an efficient vehicle for firms not only to predict the products or services that should be provided or improved for their target user groups, but also to identify the right users for a specific product family or service.

A New Method of Selecting Target User

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