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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
11

資料挖掘應用於入口網站之顧客關係管理—以國內某網站為例 / Application of Data Mining Techniques to Portal Site's Customer Relationship Management: A Case Study of Taiwan's Portal Site

柯淑貞, Ko, Shu-Chen Unknown Date (has links)
處在變化快速的網路環境中,入口網站如何建立起專屬的會員制度,以期行銷人員能在大量的會員資料庫中找出有用的資訊,掌握會員的網路行為模式、實現個人化之服務、有效區隔市場及瞭解不同會員之網路行為模式等,進而以制定適當之行銷策略而達成結合實體行銷之目標。而資料挖掘的技術能在資料量龐大的會員交易資料庫中,利用會員的基本資料與交易資料衍生建立相關的評估指標,以評估會員的特質、需求模型、消費特徵、建立市場區隔的行銷策略等,行銷人員藉此可採用不同的宣傳方式與促銷策略,以達最佳的獲利結果。 本研究以國內某入口網站真實之會員基本資料及入口網站之商品:BBS頻道與財經頻道的資料檔,做為會員網路行為模式之資料分析的基礎。本研究利用資料挖掘的技術,找出入口網站的會員與商品之分群特徵,並發掘會員在兩頻道間的網路行為的關聯規則。另一方面,本研究利用關聯規則演算法,考量實際在發掘關聯規則分析所碰到的問題,實作出一套操作流程式較為簡便的關聯規則分析程式。本研究提供不同的關聯規則分析角度,以考量會員購買商品項目組合的關聯規則,進而支援決策者制定相關商品的促銷決策,以提高銷售量。 / In the rapid-changing network environment, how do Portal Sites establish exclusive membership mechanism in order to filter useful information out of their own database, master the network behavior models of their members, realize personalized services, and effectively segment and understand different network behavior models of all members? However, data mining can use the basic members' information and transaction data to produce the associated evaluation indicator during the high volume transaction database in order to evaluate the customers’ traits, demand models, consuming characteristics, and establish the marketing strategy of segmenting target market. As a result, we can adopt different advertising types and promotion strategies to achieve the best profitable goals. The research is based on the real data of members and the merchandise of some website in Taiwan. (i.e. using data files of BBS channel and financial channel as the fundamental analysis data of network behavior models). Per using the data mining techniques, we can not only find out the characteristics of the members of portal sites and the clustering of merchandises, but unearth the association rules of network behavior of the two kinds of channels. On the other hand, this research, according to the association-ruled calculation method, is considering the practical problems when excavating association-ruled analysis methodology and producing a much simpler association-ruled analysis program. By providing the list of best buyers, the association-ruled analysis program will consider the association rule of members’ buying component and for further step, support the decision-maker to institute the related promotion strategy in order to raise the sales volume.
12

資料採礦於資訊流通業(B2B)之應用研究—以個案公司為例

陳炳輝, Chen, Ping-Hui Unknown Date (has links)
所謂資料採礦是指『從大量資料或大型資料庫中由電腦自動選取一些重要的、潛在有用的資料類型或知識』。目前資料採礦所包含的各種技術已被廣泛的應用在許多領域上,本研究即要利用資料採礦的技術從大量的客戶交易資料中採掘出客戶與商品之間的關聯性知識,並將之應用未來客戶銷售活動。 資料採礦於流通業多為B2C之應用,本研究則嘗試將資料採礦分析應用於B2B之交易分析,並以個案公司與其客戶之實際銷售資料為本研究之資料來源,本研究利用Clementine電腦軟體為資料採礦工具,並依分析目的之不同,運用該軟體提供之各項採礦模組分別對個案公司之交易資料進行分析,如: *.使用關聯網〈web〉的方式,針對個案資料,尋找商品銷售間的強弱關係,挑出銷售關聯性較高的商品組合,並且利用C5.0決策樹演算法,尋找該交易行為的對象之特性為何。 *.使用Apriori演算法,針對BZ(商圈)、DL(經銷商)、SP(門市)等不同客戶類型在不同的資料期間,找出資料中所有商品之關聯規則。 *.利用Apriori演算法,利用前半年資料,找出IFAKMB(主機板)、IFDDLC(LCD監視器)、IFCOCP(中央處理器)等類別商品的購買規則,並分別以後半年的資料進行驗證,探究此規則之可行性。 接著針對各項資料採礦結果,就個案公司之實際狀況進行解讀,同時更重要的是探討該分析結果應用於銷售實務上之可行性,如:產品銷售規則,行銷策略、促銷戰術之擬定等。最後並以本研究之結果及經驗,對個案公司提出資訊管理系統資料補強之建議及資料採礦於未來可再延伸探討之應用方向。
13

學術研究論文推薦系統之研究 / Development of a Recommendation System for Academic Research Papers

葉博凱 Unknown Date (has links)
推薦系統為網站提升使用者滿意度、減少使用者所花費的時間並且替網站提供方提升銷售,是現在網站中不可或缺的要素,而推薦系統的研究集中在娛樂項目,學術研究論文推薦系統的研究有限。若能給予有價值的相關文獻,提供協助,無疑是加速進步的速度。 在過去的研究中,為了達到個人化目的所使用的方法,都有不可避免或未解決的缺點,2002年美國研究圖書館協會提出布達佩斯開放獲取計劃(Budapest Open Access Initiative),不要求使用者註冊帳號與支付款項就能取得研究論文全文,這樣的做法使期刊走向開放的風氣開始盛行,時至今日,開放獲取對學術期刊網站帶來重大的影響。在這樣的時空背景之下,本研究提出一個適用於學術論文之推薦機制,以FP-Growth演算法與協同過濾做為推薦方法的基礎,消弭過去研究之缺點,並具個人化推薦的優點,經實驗驗證後,證實本研究所提出的推薦架構具有良好的成效。 / Recommendation system is used in many field like movie, music, electric commerce and library. It’s not only save customers’ time but also raise organizations’ efficient. Recommended system is an essential element in a website. Some methods have been developed for recommended system, but they are primarily focused on content or collaboration-based mechanisms. For academic research, it is very important that relevant literature can be provided to researchers when they conduct literature review. Previous research indicates that there are inevitable or unsolved shortcomings in existing methods such as cold starts. Association of Research Libraries purpose “Budapest Open Access Initiative” that is advocate open access concept. Open access means that users can get full paper without register and pay fee. It’s a major impact to academic journal website. In this space-time background, we propose a hybrid recommendation mechanism that takes into consideration the nature of recommendation academic papers to mitigate the shortcomings of existing methods.
14

透過圖片標籤觀察情緒字詞與事物概念之關聯 / An analysis on association between emotion words and concept words based on image tags

彭聲揚, Peng, Sheng-Yang Unknown Date (has links)
本研究試圖從心理學出發,探究描述情緒狀態的分類方法為何, 為了進行情緒與語意的連結,我們試圖將影像當作情緒狀態的刺激 來源,針對Flickr網路社群所共建共享的內容進行抽樣與觀察,使 用心理學研究中基礎的情緒字詞與詞性變化,提取12,000張帶有字 詞標籤的照片,進行標籤字詞與情緒分類字詞共現的計算、關聯規則 計算。同時,透過語意差異量表,提出了新的偏向與強度的座標分類 方法。 透過頻率門檻的過濾、詞性加註與詞幹合併字詞的方法,從 65983個不重複的文字標籤中,最後得到272個帶有情緒偏向的事物 概念字詞,以及正負偏向的情緒關聯規則。為了透過影像驗證這些字 詞是否與影像內容帶給人們的情緒狀態有關聯,我們透過三種查詢 管道:Flickr單詞查詢、google image單詞查詢、以及我們透過照片 標籤綜合指標:情緒字詞比例、社群過濾參數來選定最後要比較的 42張照片。透過語意差異量表,測量三組照片在136位使用者的答案 中,是否能吻合先前提出的強度-偏向模型。 實驗結果發現,我們的方法和google image回傳的結果類似, 使用者問卷調查結果支持我們的方法對於正負偏向的判定,且比 google有更佳的強弱分離程度。 / This study attempts to proceed from psychology to explore the emotional state of the classification method described why, in order to be emotional and semantic links, images as we try to stimulate the emotional state of the source, the Internet community for sharing Flickr content sampling and observation, using basic psychological research in terms of mood changes with the parts of speech, with word labels extracted 12,000 photos, label and classification of words and word co-occurrence of emotional computing, computing association rules. At the same time, through the semantic differential scale, tend to put forward a new classification of the coordinates and intensity. Through the frequency threshold filter, filling part of speech combined with the terms of the method stems from the 65,983 non-duplicate text labels, the last 272 to get things with the concept of emotional bias term, and positive and negative emotions tend to association rules. In order to verify these words through images is to bring people's emotional state associated with our pipeline through the three sources: Flickr , google image , and photos through our index labels: the proportion of emotional words, the community filtering parameters to select the final 42 photos to compare. Through the semantic differential scale, measuring three photos in 136 users of answers, whether the agreement made earlier strength - bias model. Experimental results showed that our methods and google image similar to the results returned, the user survey results support our approach to determine the positive and negative bias, and the strength of better than google degree of separation.

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