網路口碑已成為消費者尋找醫療院所的一個重要依據，但隨著網路上分享的資訊越來越多，從大量口碑中找到自己所需的資訊已變成一項費時的任務。因此口碑推薦系統成為各大網站必備工具，雖然口碑已被廣泛的作為推薦系統的基礎，但不同於一般消費決策，醫療決策具有高度專業性，因此以醫院口碑為基礎的推薦系統少有人探討。故本研究目的為建立一套適用於評估醫療院所口碑的推薦系統。
　　本研究利用以內容為基礎的推薦系統做為主要的研究方法，由於醫療服務的推薦不同於產品推薦具有一定的規則，因此在口碑分析的部份利用建立控制字彙並透過問卷調查給予各詞彙分數的方式對口碑進行分析。本研究蒐集了台灣使用率最高的三個論壇網站（Mobile01、Ptt實業坊與Yahoo!奇摩知識+）共5,124筆口碑，建構一套牙醫推薦系統。
　　為了解本推薦系統的實用性，本研究利用個案研究法將本系統和Google搜尋引擎進行比較，分別評估兩者的搜尋時間、系統品質、系統效能、系統觀感和使用者行為意向五個部份。經由202位使用者實際操作之實驗結果得知，本系統能夠有效減少搜尋醫院資訊上的時間，且在系統品質、推薦的影響程度上都有不錯的水準。換言之，使用理性決策模式將詞彙進行分類，並依據大眾的觀感給予詞彙分數所建立出來的控制字彙，可以有效的提升醫療院所的推薦滿意程度。

Online word of mouth (WOM) has been shown to be one of the most important sources of information for healthcare decisions. However, explosively growing information on the internet makes it difficult for consumers to effectively identify and appraise relevant WOMs. To provide a solution, this study proposed a novel personalized recommender system using text mining techniques, namely Hosearch. A total of 5,124 WOMs were collected from the selected public online forums in Taiwan, and the data were then used to develop the Hosearch recommender system. The empirical evaluations reveal that the proposed system is useful in associating the recommended items with user’s preferences more effectively than common search engines (e.g., Google).

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