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dc.contributor.author羅淑娟en_US
dc.contributor.author柯秀奎en_US
dc.contributor.author林晶璟en_US
dc.contributor.authorShu-Chuan Loen_US
dc.contributor.authorShiou-Kuei Keen_US
dc.contributor.authorChing-Ching Linen_US
dc.date.accessioned2016-01-29T02:47:33Z-
dc.date.available2016-01-29T02:47:33Z-
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/11536/129072-
dc.description.abstract一個受歡迎的網站可能會從網路會員處收到千百封的留言,最重要的訊息是屬於顧客關於技術需求及不滿意的怨言。本研究提出一個自動機制(WebQC)基於文件探勘和支援向量機(SVM)技術來分類顧客的留言,此機制可以自動過濾抱怨的留言並且正確地增加客服部的生產力以及顧客滿意度。本研究在抱怨率上使用了不良率管制圖(p-control chart)來檢查服務品質是否低於綱站運行的期望水準,並以一社群網站案例作為實驗案例,根據實驗結果顯示,其分類正確率或檢定力(如果留言為抱怨,SVH可以辨識為抱怨)的正確率超過83%(平均值為89%),而不良率管制圖可適時地反應出非隨機的狀況。zh_TW
dc.description.abstractA popular Web site may receive hundreds of thousands of messages each day from site users. The moat useful customer feedback consists of technical requests and complaints. In this research, we propose the WebQC software to classify a user's feedback messages by using text-mining techniques and a support vector machine (SVM). Our software ran filter the messages as complaints or other kinds of messages automatically and thus effectively increase the productivity of the customer service department and as well as customer satisfaction. In this research, we employ the p-control chart on the complaint scale to check the quality of the Web site services if this quality is lower than expected. We used a community Web site as our test case. The empirical results show that our ability to classify a message accurately (i.e., if a message is a complaint, the SVM recognizes it as a complaint) is over 83% (on average 89%). Also, the p-control chart has the ability to reflect a normal situation in real-time.en_US
dc.language.isozh_TWzh_TW
dc.subject文件探勘zh_TW
dc.subject支援向量機zh_TW
dc.subject文件分類zh_TW
dc.subject補償不良率管制圖zh_TW
dc.subject網路服務品質zh_TW
dc.subjectText miningzh_TW
dc.subjectSupport vector machine SVMzh_TW
dc.subjectClassificationzh_TW
dc.subjectcompensating p-control chartzh_TW
dc.subjectWeb service qualityzh_TW
dc.title綱路服務品質探勘與管制zh_TW
dc.titleWeb-Service Data Quality Mining and Controlen_US
dc.identifier.journal交大管理學報zh_TW
dc.identifier.journalChiao Da Mangement Reviewen_US
dc.citation.volume1en_US
dc.citation.spage251en_US
dc.citation.epage268en_US
dc.contributor.departmentDepartment of Management Scienceen_US
dc.contributor.department管理科學學系zh_TW
Appears in Collections:Chiao Da Mangement Review


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