民國九十七年四月第
38
卷第
2
期
1============================================================ Inside of Internet Data
Nien-Yi Jan Ming-Tsung Chen Wan-Ting Chang Wei Shen Chow
Abstract
Along with the Internet technology development and the Web 2.0 times coming, Internet has already become one important part of daily life for people. The global average hours of each month accesses the Internet reached to 31.3 hours. Amount of data is quickly increasing with the increasingly access hours, but simultaneously also provide a contact plane to understand thoroughly customer behavior and to catch the customer portfolio. But, Anonymous users or meaningless browsing behavior often cause large time spent on preprocessing data. Therefore, we need to design a well-defined, effectively operated system framework to handle all analyzing process and applications. Papers and researches in computer or even in marketing area are focused on providing a new or improved algorithm for some specific purpose or issue. We cannot find papers discussed generally and thoroughly the properties of Internet data and how to collect or use them. So, we try to consider both marketing and system aspects to introduce deeply Internet data and all related application.
Keyword
網路資料採礦、網路資料採礦系統、網路資料
2============================================================ The Research and Application of Web Text Mining
Wei-Ting Cheng Ming-Tsung Chen
Additionally, change of customers’ behaviors is occurring at an accelerating rate. As a result, a company can only merit a better benefit by comprehending his competitors and customers completely. Since the data in World Wide Web are varied and easy to capture, we propose the structure of text mining in World Wide Web to find the information of competitors and customers. The structure can benefit the business strategy and
marketing activities. In the paper, first of all, we survey some relative research and issues about web text mining. Second of all, we introduce the structure of web text mining. Last but not least, we come to some conclusions about the future work.
Keyword
資訊檢索、資料檢索、商業智慧、資料採礦、網路採礦、文字採礦、Web Service
3============================================================ Generating Personalized Internet Advertisements with Web Mining Technique
Wen-Chin Chen
Abstract
With the exploded growth of internet population and the approach of Web2 .0, the business opportunity of the web advertising market is expanded day by day. Since the web advertising is still in evolving, it is a very important subject for the advertisers to set up the broadcasting mechanism and operating model by its characteristic superior to traditional advertising. On this new developing media of internet, the article puts forward a set of intact personalized advertising mechanisms by reciprocal using two kinds of data mining methods: Factor Analysis method and Cluster Analysis method. In this way, we can separate the internet users into different groups and deliver them the proper web advertising by going over which websites do they prefer browsing.
Keyword
4============================================================ Social Network Mining in Telephone Call Graph by Using Spectral Clustering
Ming-Tsung Chen Nien-Yi Jan Chiang-Hui Wang
Abstract
In general, the theory of six degrees of separation has shown that there are weak interpersonal connections in the society. These connections make up most heavy and most complicated social networks. Deploying social network analysis and data mining techniques to explore the characteristics or behavior from within communities has drawn attention in academic research and practical applications. Though social network analysis has been successfully applied to analyze the communities in the webpage relations and the blog discussion, applying the technology to analyze the social networks of phone call records, which is crucial to marketing, was is not addressed before. In this paper, we introduce the business applications of the social networks, the properties of Laplacian Matrix, and spectral clustering algorithm. By demonstrating the spectral clustering to analyze the social network constructed by call records, the communities of this social network can be found. The behavior characteristics of the communities can be reviewed to serve new services for marketing.
Keyword
頻譜群集法、通話行為、社交網路、網路資料採礦、社交網路分析、拉普拉斯矩 陣、費德勒向量、最小圖形分割。
5============================================================ Using Associative Classification Tree to Summarize Associative Classification Rules
Tzu-Hsuan Hong Chih-Tung Lai
Abstract
Association rule mining is one of the most popular areas in data mining. It is to discover items that co-occur frequently within a set of transactions, and to discover rules based
problem for years (associative classification). However, once rules have been generated, their lacking of organization causes readability problem, i.e., it is difficult for user to analyze them and get a good understanding of the domain. To resolve this weakness, our work presented two algorithms that can use decision tree to summarize associative classification rules. As a classification model, it connects the advantages of both associative classification and decision tree. On one hand, it is a more readable, compact, well-organized form and easier to use when compared to associative classification. On the other hand, it is more accurate than traditional TDIDT (abbreviated from Top-Down Induction of Decision Trees) classification algorithm.
Keyword
資料探勘，以規則為基礎的分類演算法，規則摘要法
6============================================================ A Study of Applying Data Mining to Business Strategy Planning
Hsing Hung Lin
Abstract
Strategy planning plays a critical role in enterprise administration for maintaining competitive position in the fast changing market. Business strategies have to be realized via two major functions of cooperation – marketing and innovation. Problem
discovering and solving are the foundation of implement marketing and innovation. Analyzing the data that was converted from relative facts and experiences in the business operation process help to clarify the architecture and hierarchy, therefore knowledge of the problem solving and business strategy will be found. Data mining is the key step of knowledge discovering in database (KDD). This study attempts to employ data mining technique to perform business strategy planning. This framework utilizes decision tree induction to seek the pattern and relation among data as well as analytic hierarchy process to enhance the difference degree of criteria in order to plan optimal business strategy for enterprise.
關鍵字
7============================================================ The Metadata Management in the Data Warehouse
Hue-Ling Chen Chao-Tsung Wu Wei-Shen Chow
Abstract
The strategies of a data warehouse integrate heterogeneous data in different organizations. These data are extracted, transformed, and then loaded into a data warehouse by metadata. Metadata is used to abstract out the representational details of data and capture the information content during the technical or business process. The complete and well-defined metadata in a data warehouse can support the decision making of business intelligent. However, as modern technologies change so fast, the heterogeneity of the metadata becomes a problem since a data warehouse integrates more heterogeneous information resources consisting of a variety of digital data. In this paper, we explore the metadata collection during the data processing in a data warehouse. We present the structure of the metadata sharing management which can help trace the data variety and adjust the metadata appropriately. Moreover, we take the multimedia data as an example to present the process to collect and manage the metadata in a data warehouse.
Keyword
商業智慧、Metadata、資料倉儲、ETL、資料採礦
8============================================================ Data Mining with a Spatial Index in a Spatial Data Warehouse
Hue-Ling Chen
Abstract
The growing production of maps and mobile networks is generating huge volume of data stored in the spatial data warehouses. Due to complicated characteristics of spatial data, huge volume of data exceeds the human analysis capabilities. Spatial data mining extracts the knowledge from the spatial data warehouse on spatial relationships between spatial data, including topology, direction, and distance relations. These spatial relationships correspond to the spatial join operators and can be quickly obtained by the
solve the problems of data redundancy and overlaps in other spatial indices, quadtree and R-tree. Moreover, NA-tree can be used to save the topological and the directional relationships of spatial data. Therefore, this paper focuses on the research of spatial indices, especially on the NA-tree, to provide an easy and efficient support of spatial data mining.
Keyword
空間資料倉儲, 空間資料採礦, 空間資料索引, 空間關係, 空間資料
9============================================================ The Applications of Qualitative Research in Telecommunication Services
Hung, Ching-Yi Fang, Chia Li Chen, Li Fen
Abstract
With the trend of legalization of VoIP and voice call getting cheaper, the operator’s voice revenue will continue to decline in the future. Data revenue carries an important opportunity to slow the speed of revenue decreasing. However, the current domestic revenue in the operation of data on the hard work has been no improvement. The data revenue is only 7% of total mobile revenue. This percentage is much lower than that of Japan and Korea. It becomes the most urgent problem to the mobile operators. Besides, the digital home applications would be hot topic to the telecommunications industry in recent years. The telecommunications industry wants to catch up the trend of the digital home applications. Thus, they try to look for new market opportunities and applications to improve the overall revenue. As consumer awareness rise, the operator will have to be more in-depth excavation and deep understanding of the actual needs of customers. Depth interviews and the focus group are the usual ways to collect customer information in other industries. They are more likely qualitative research methods. In addition to these methods, ethnographic research and participatory design research are also the ways used to develop the new market. This study has two examples of qualitative research of telecommunications services. 1. The customers’ adoption will in the market of mobile data service – Deep consumer awareness of
customers digging (By using depth interviews and Means-End Chains) 2. Business opportunities of digital home services exploration – New services market opportunities tapping (By using ethnographic research and participatory design research). Besides the results of these two examples of qualitative research, it could provide with the quality of marketing research methods to the telecommunication services market in the future. The “user centric thinking” marketing research helps to understand customers’ needs deeper and to design the services which really meet customers want. By aligning existing products and services, it makes win-win situation between companies and customers.
Keyword
Telecommunications Services, Qualitative Research, Means-End Chains(MEC), in-depth interview, Ethnographic Research, Participatory Design
10============================================================ The Applications and Services of the CPE-based IP VPN Technique
Wen-Chuan Tai Kuo-Tsai Chen Yen-Jen Chen Yu-Huang Chu Jun-Jyi Lin Abstract
The CPE-based IP VPN is to provide virtual private connectivity among specific network endpoints on the Internet. This technology is a proven network solution not only for enterprise customers who can be used to save communication costs, but also for telecommunication carriers who can leverage this CPE-Based IP VPN technology on their network based VPN solution to capitalize the global communication growth. The carriers generate more revenue streams by providing more new value-added services, such as web-hosting and network security anti-virus protection enabled by their CPE-based IP VPN. This article will focus on CPE-based IP VPN technologies and its service models introducing similar VPN services that are available in the markets. Product surveys and their functionalities will also be described.
2. CPE-based IP VPN 3. Network-based IP VPN
4. NGN( Next Generation Network) 5. QoS
