系統識別號 | U0002-3007200714125400 |
---|---|
DOI | 10.6846/TKU.2007.01242 |
論文名稱(中文) | 協同過濾演算法之實作與應用 |
論文名稱(英文) | Implementation and Application of Collaborative Filtering Algorithms |
第三語言論文名稱 | |
校院名稱 | 淡江大學 |
系所名稱(中文) | 資訊工程學系碩士班 |
系所名稱(英文) | Department of Computer Science and Information Engineering |
外國學位學校名稱 | |
外國學位學院名稱 | |
外國學位研究所名稱 | |
學年度 | 95 |
學期 | 2 |
出版年 | 96 |
研究生(中文) | 林敬達 |
研究生(英文) | Chin-Ta Lin |
學號 | 694190116 |
學位類別 | 碩士 |
語言別 | 繁體中文 |
第二語言別 | |
口試日期 | 2007-06-21 |
論文頁數 | 73頁 |
口試委員 |
指導教授
-
蔣定安
委員 - 葛煥昭 委員 - 王鄭慈 |
關鍵字(中) |
推薦系統 協同過濾 |
關鍵字(英) |
Recommend system Collaborative Filtering |
第三語言關鍵字 | |
學科別分類 | |
中文摘要 |
網路人力銀行之興起,不但打破了時空的限制,並使得企業利用網路低廉的成本,讓傳統要花大筆錢刊登徵才啟示、印製DM(廣告傳單)、製作電視廣告…等的開銷,都轉移到網際網路之上。故今日最大的問題不是資訊的取得,而是資訊超載。本研究目的是建立一套「協同過濾推薦系統」,提供即將畢業的青年學子,在投入職業場所時所需的方向與建議,希望藉由此機制推薦出學生們所感興趣的工作職缺,以減少在網路人力銀行上漫無目標的瀏覽而浪費時間,進而能找到其最適合的工作。 |
英文摘要 |
The rise of the network job bank, not only broke the restriction of the timespace, and make the enterprise made use of the cheap cost of the network, let the tradition wanted spend the expense that a money publishes the hiring apocalypse and prints to make the DM(the advertisement handbill),the manufacture television advertisement … ...etc., all transfer the internet. Past biggest problem is not an information to obtain today, but the information overloads. This research purpose builds up a set of" recommend system of collaborative filtering ", providing the youth student that will soon graduate, at the devotion occupation place the direction and suggestion needed, hope by this mechanism recommend the studentses to lack the interested in work job, with decrease is planless to browse and waste time on the network job bank, then can find out its most fit work. |
第三語言摘要 | |
論文目次 |
目錄 目錄 I 圖目錄 II 表目錄 III 第一章 緒論 1 1.1、研究背景 1 1.2、研究動機 2 1.3、研究目的 4 1.4、研究架構 4 第二章 文獻探討 5 2.1、推薦系統 5 2.1.1、何謂推薦系統 5 2.1.2、推薦系統的介面呈現 7 2.2、以內容為基礎的推薦系統 9 2.3、協同過濾 12 2.3.1、何謂協同過濾 12 2.3.2、協同過濾的優缺點 14 2.3.3、協同過濾運作機制 16 2.4、評比分類方式 20 第三章 研究方法 24 3.1、研究架構 24 3.2、研究設計 27 3.2.1、系統開發 27 3.2.2、實驗程序 33 3.3、系統展示 35 3.3.1、系統開發環境與工具 35 3.3.2、系統的介面與操作 36 第四章 實驗結果與分析 39 4.1、實驗資料分析 39 4.2、整體推薦成效評估 41 4.3、分群過濾變數與干擾變數間之關係 45 第五章 結論與未來方向 49 5.1、結論 49 5.2、未來研究方向 51 參考文獻 52 附錄—英文論文 59 圖目錄 圖 2.3.3-1 協同過濾流程圖 17 圖 3.2.1-1 系統流程圖 30 圖 3.3.2-1 理想職務票選活動首頁 36 圖 3.3.2-2 理想職務票選活動畫面 37 圖 4.2-1 協同過濾機制之成效比例 43 圖 4.3-1 性別與分群過濾變數比較表 46 圖 4.3-2 年級與分群過濾變數比較 47 表目錄 表 2.2-1 以內容為基礎的推薦系統整理表 11 表 2.3.3-1 評比方式的選擇分類 19 表 2.4-1 顯性評比的實例 20 表 2.4-2 隱性評比的來源 21 表 2.4-3 顯性評比與隱性評比的比較 23 表 3.2.1-1 票選活動評比資料表 31 表 3.2.1-2 系統內部分群推薦方式 32 表 3.2.2-1 系統隨機出現的問題 34 表 3.3.2-1 參與理想職務票選活動的同學人口結構 37 表 4.1-1 職務推薦實驗人口結構 40 表 4.2-1 分群過濾變數推薦成功比例 42 表 4.2-2 同學選擇職務推薦結果滿意數統計 42 表 4.2-3 「協同過濾」與「票選排行榜推薦機制」機制之比較 44 表 4.3-1 性別與分群過濾變數匯總表 46 表 4.3-2 職業別與分群過濾變數匯總表 48 |
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