Case Study In Tmall Com And Taobao. Com

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Chapter 4 Case Study in Tmall.com & Taobao.com
4.1 Feature of Text information E-Commerce
In this chapter I introduce my own research about how to evaluate customer review data mining and using rough set approach to calculate the decision rules about product. The product I choose is cell phone. The product I choose is Samsung galaxy note III (三星) from taobao.com and tmall.com. With the price rate of 3000-4000 Rmb and take a review from 20 different sellers. This phone itself right now is in so many in the Chinese and worldwide market. First of all I all I select a view seller of Samsung galaxy note III from tmall.com and taobao.com (B2C). After that from the tmall.com and taobao.com seller page, I take some customers review about Samsung galaxy note III. From customer’s review from tmall.com and taobao.com, 20 sellers pick up. The example of the customers review is like example above:
Ex4.1 show customers review from taobao.com

Ex 4.2 show customers review from tmall.com

4.2 Analysis Procedure
Customer’s review data from taobao.com and tmall.com is taken. From collected 20 seller we collect some customer’s review data mining. Separate the noun and adjective from customer review. One by one is divided in two table. After separate noun and adjective, I do some survey to 20 people to find the synonym or similarity. From the similarity, I can eliminate some of the criteria of 26 criteria to 18 category. It can continue to next step of rough set based mining.
Customer’s review Data Mining system smooth software so good system is not smooth pretty good screen delicate screen average screen battery durable battery average pretty good packaging good call quality
Expensive prize

good accessories full accessories accessories genuin...

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...omers review from taobao.com and tmall.com, I give marking to each category (table 4.1). After rating it one by one by used the algebra formula it produced table 4.4 and table 4.5.
In the second experiment, is using the 4emkA2 software by input the data from the experiment (table 4.1). The result is shown in Figure 4.4. The use of the software is to fins the decision result. After using the software is found there is 11 generated decision rules (Figure 4.5). Finally the final process of 4emka2 software it is found that Figure 4.6 is reclassification result for the customers review mining.
Future research is needed to compare the classification abilities of this method in various situations with other case-based classification methods is needed to see some other result how to evaluate the customers review by using DRSA method and 4emka2 software decision result.

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