以商機分析理論應用於iPhone之研究

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姓名

廖品晴(Pin-Ching Liao) 查詢紙本館藏

畢業系所

企業管理學系

論文名稱

以商機分析理論應用於iPhone之研究
(The application of opportunity algorithm on iPhone)

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摘要(中)

以前的研究基於問卷和訪談進行客戶調查，然後利用調查數據來分析產品特性。近年來，消費者積極地在網路上發表評論，其中評論內容有大量關於客戶意見和期望的訊息。然而，之前的研究未能解決使用詞級別的分析而難以識別潛在的產品特徵以及對已識別產品的機會潛力分析考慮不足的問題。據此，本研究提出了一種機會挖掘方法，以線上評論數據的關鍵屬性和情感分析找出產品機會。對於多功能產品，這種方法可以識別產品客戶在網路上討論的潛在產品屬性，從而量化每個產品關鍵屬性的重要性。接下來，使用情感分析評估每個產品關鍵屬性的滿意度。最後，透過產品主題的重要性和滿意度以機會算法從客戶為中心的角度識別每個產品關鍵屬性的機會價值和改進方向，在快速發展的產品環境中分析不斷變化的客戶需求。

關鍵字：關鍵屬性、商機演算法

摘要(英)

Previous research conducted customer surveys based on questionnaires and interviews, and then used survey data to analyze product characteristics. In recent years, consumers have actively posted comments on the Internet, and the comments contained a lot of information about customer opinions and expectations. However, previous research failed to solve the problem of using term-level analysis to identify potential product features and insufficient consideration of the opportunity potential analysis of identified products. Based on this, this research proposes an opportunity mining method to find product opportunities based on the key attributes of online review data and sentiment analysis. For multi-functional products, this method can identify potential product attributes discussed by product customers on the Internet, thereby quantifying the importance of each product’s key attributes.
Next, use sentiment analysis to evaluate the satisfaction of each product′s key attributes. Finally, through the importance and satisfaction of the product theme, the opportunity algorithm identifies the opportunity value and improvement direction of each key attribute of the product from a customer-centric perspective, and analyzes the ever-changing customer needs in the fast-developing product environment.

關鍵字(中)

★ 關鍵屬性
★ 商機演算法

關鍵字(英)

論文目次

目錄
一、緒論 1
1-1研究背景與動機 1
1-2 研究目的 2
1-3研究架構 3
二、文獻探討 4
2-1提取關鍵屬性 4
2-2情緒分析 5
2.4 商機演算法 6
三、系統架構 8
3-1線上評論資料預處理 8
3-2 提取關鍵屬性 9
3-3 關鍵屬性的挑選 9
3-4 提取關鍵屬性的句子 10
3-5情感分析 10
3-6 ENNM 11
3-6-1 將情感結果轉化為分值 11
3-6-2 屬性重要性計算 11
3-6-2-1 各模型中的屬性重要性計算 12
3-6-2-2 標準化輸入層和隱藏層之間的權重 13
3-6-2-3計算每個隱藏元的權重 14
3-6-2-4 計算每個模型中的屬性權重 14
3-6-3模型權重計算 14
3-6-4消除離群值 15
3-6-5屬性重要性計算 16
3-6-6商機計算 16
四、資料分析 18
4-1 資料 18
4-2 使用線性判別分析（LDA）提取關鍵屬性 19
4-3 關鍵屬性的選擇 21
4-4 從網路評論中提取句子 22
4-5 情感分析 23
4-6 關鍵屬性計算 25
4-7 商機分析 30
五、結論 34
六、參考文獻 35

參考文獻

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指導教授

陳炫碩

審核日期

2021-7-22

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