產品生命週期常被行銷人員作為規劃、控制和預測的工具，因為產品所處的生命週期階段可以解釋產品與市場的動態。但常由於資料取得的困難與決策資訊的不足，而對產品生命週期造成誤判。因此本研究根據消費者行為模式的推論，對產品討論量與時間的關係進行分析，藉由產品討量去探索該產品在顧客中的「地位」，進而繪製出的產品生命週期圖。最後透過資料探勘與資訊擷取技術，來分析討論量變化與產品討論內容，以期獲得會影響產品生命週期的相關產品事件資訊。由研究結果發現網路上產品討論量確實能反應特定產品發售、停止銷售與相關行銷事件之時間點；而透過對產品討論文章數量的分析，亦有助於產品事件之自動偵測與分析。相信經由對組織外顧客知識的分析，對於企業行銷決策的制定會有相當的助益。本研究的主要貢獻如下：

Product life cycle (PLC) may be used as a managerial tool. Marketing strategies must change as the product goes through its life cycle. If managers understand the cycle concept, they are in a better position to forecast the future sales activities and plan marketing strategies. However, people often make the wrong PLC because of the difficulty of data access and lacking decision-making information. Therefore, this thesis applies customer behavior model to analyze the relationship between the frequency and the duration time from the product discussion, and it calculates the PLC pattern to explore the product’s current position in customers’ mind. Finally, the PLC curve will be constructed by using the information that we got from previous analysis. Moreover, we also employ data mining and information retrieval technique to diagnose the variance of discussion frequency and the content of discussion article to extract the distinctive event that influenced PLC curve. The main contributions of this thesis are described as the following sentence:

目 錄
第1章 緒論 1
1.1. 研究背景與動機 1
1.2. 研究目的 4
1.3. 研究範圍與限制 5
1.4. 研究方法 5
1.5. 論文架構 6
第2章 文獻探討 7
2.1. 產品生命週期 7
2.1.1. 產品生命週期的定義 7
2.1.2. 產品生命週期相關理論 8
2.1.3. 產品生命週期的形式 8
2.1.4. 產品生命週期階段之界定 9
2.1.5. 產品生命週期的應用 12
2.2. 消費者行為模式 14
2.3. 中文資訊擷取相關技術 15
2.3.1. 資訊擷取技術的分類 15
2.3.2. PAT-Tree-Based的中文資訊擷取技術 16
2.3.3. 關鍵字詞篩選 21
2.4. 資料分群 22
2.4.1. 自我組織映射圖網路(Self-Organization Map) 22
第3章 產品生命週期之系統分析與設計 32
3.1. 討論文章擷取與資料轉換 33
3.1.1. 討論文章擷取 33
3.1.2. 討論文章資料轉換 36
3.2. 擷取產品相關字詞 36
3.3. 產品生命週期與事件偵測 37
3.3.1. 產品生命週期 37
3.3.2. 產品事件偵測 40
3.4. 產品事件分析 47
第4章 系統實作流程 49
4.1. 討論文章擷取子系統 51
4.1.1. 擷取產品討論文章 52
4.1.2. 時間格式與中文編碼處理 52
4.1.3. 擷取產品型號 52
4.2. 產品相關字詞擷取子系統 55
4.2.1. 中文字詞的擷取 55
4.2.2. 英文字詞的擷取 56
4.2.3. 產品型號的輔助 57
4.3. 產品生命週期與產品事件偵測子系統 57
4.3.1. 討論文章之型號與事件分類 58
4.3.2. 討論量時間單位轉換與平均線計算 59
4.3.3. 圖形化分析引擎 60
4.3.4. 產品事件偵測 62
4.4. 產品事件分析子系統 65
4.4.1. 關鍵詞篩選(Feature Selection) 67
4.4.2. 分群結果檢示與事件分析 69
第5章 資訊產品生命週期之結果分析 73
5.1. 產品生命週期之分析與呈現 73
5.1.1. 單一產品生命週期圖查詢 74
5.1.2. 多種產品生命週期圖查詢 76
5.2. 產品事件偵測與分析 81
5.2.1. 行動電話之產品事件偵測與分析 81
5.2.2. 筆記型電腦之產品事件偵測與分析 87
5.3. 實務上之應用 91
第6章 結論 92
6.1. 研究成果 93
6.2. 建議與未來研究方向 94
參考文獻 96
中文參考文獻 96
英文參考文獻 96

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