【正文】 ored in the various tables are in a specified format (defined during the construction of the database). Sometimes, it is useful to transform the data into a new format in order to mine additional information. For example, a new column svc_repair_time (service repair time) is created by calculating the difference, measured in number of days, between svc_start_dt and svc_end_dt in the SERVICE_REPORT table. This new attribute is useful in analyzing the performance of the service engineers. 、 Data warehousing Data warehousing is the process of visioning, planning, building, using, managing, maintaining and enhancing databases. The data suitable for mining are collected from the various tables of the customer service database and stored in DB Miner39。 this is inefficient, especially for large case database. Other CBR systems use hierarchical indexing such as CART , decision trees , and although this performs efficient retrieval, building a hierarchical index needs the knowledge of an expert during the caseauthoring phase. The neural work approach provides an efficient learning capability when provided detailed examples. Neural works may be either supervised or unsupervised, depending on the method of training. It performs retrieval based on nearest neighbor matching, since it stores the weight vectors as the codebook or exemplar vector for the input patterns. The matching is based on a petitive process that determines the output unit that is the best match for the input vector, similar to the nearest neighbor rule. However, the search space in a neural work is greatly reduced because of the generalizations of knowledge through training. In contrast, the CBR systems need to store all the cases in the case database in order to perform accurate retrieval. The CBR systems that store only relevant cases for an efficient retrieval lack the accuracy as well as the learning feature. Thus, neural works are very suitable for case indexing and retrieval. Other data mining techniques include rulebased reasoning, fuzzy logic, geic algorithms, decision trees, inductive learning systems, and statistical pattern classification systems. In addition, hybrid approaches, such as hybrid casebased reasoning and neural work , have also been developed. Here, a data mining technique that integrates case based reasoning, neural work and rulebased reasoning is defined. These two are incorporated into the framework of the CBR cycle. Instead of using the nearest neighbor technique of traditional CBR systems, a neural work is used for indexing and retrieval of most appropriate service records based on user39。s premise for an onsite repair. During such trips, the service engineer will take past records of the customer39。 it would search the unstructured customer service records for machine fault diagnosis. The proposed technique has been implemented to support intelligent fault diagnosis over the World Wide Web. Author Keywords: Data mining。 ., more than one data mining techniques. For example, Darwin from Thinking Machine Corp. supports neural works, regression tree (CART), kmeans algorithm, and case based reasoning for classification, prediction, and clustering functions. There are also some tools that only aim at a special data mining function. This provides 175。s data warehouse. OLAP data marts are then generated from the data warehouse, which contains customized data at a higher level of summarization. Data cubes can be constructed from data marts to provide multidimensional views of the data. Online analytical mining can then be performed using the multi dimensional data cube structure for knowledge discovery .It shows a piece of the multidimensional (3D) view of a data cube using the three dimensions, mc_fault_gp, months and svc_member_id for the three axes. The size of each individual cube represents its number of records, whereas the color of the cube indicates the total value of the attribute svc_repair_time for the records contained in the cube. Pivoting, drilling, slicing and dicing operations can be performed on the data cube for further exploration. As higher service repair time indicates longer machine down time, this may result in customer dissatisfaction. The pany should look into those cases with high service repair time in order to enhance service efficiency. 、 Data mining DB Miner is used to perform the data mining functions, including summarization, association, classification, prediction and clustering. Two examples of data mining functions are now described: The first example illustrates the use of a summarization function. It presents a summary of the machine models serviced by service e