| Summary: | 碩士 === 國立臺灣科技大學 === 資訊管理系 === 97 === Goods price is one of successful factors in the network shopping market. However, transaction disputes caused by devious price labeling not only affect the repute of corporate company but also influence the reliance of consumer. While analyzing many case reports, we found that devious price labeling of goods on slotting and selling process could be prevented with a complete mistake avoidance checking system. In addition, improving the defect that online vender unchecked prices with competitor’s is also a functional way to avoid mistakes.
In this thesis, we try to use web content mining as a basic tool to establish price mistake avoidance checking system. Through analyzing numerous data collected by multiple searching engines, we can obtain a correct and reliable method to support merchandize and then show the risk factor as an alarm message.
Then, we compare the difference between cost and price of real products in online store, and combine with real time web mining data for designing the price mistake avoidance checking system. The experimental results reveal that the proposed strategy can control the trade crunch to legitimate range for online stores and reduce the occurrence of transaction disputes.
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