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    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/56502
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/56502


    Title: 應用資料探勘技術於食譜分享社群網站進行內容分群之研究
    A user-based content clustering system using data mining techniques on a recipe sharing website
    Authors: 林宜儒
    Contributors: 楊建民
    林宜儒
    Keywords: 文字探勘
    資料分群
    text mining
    data clustering
    Date: 2012
    Issue Date: 2013-01-02 13:21:51 (UTC+8)
    Abstract: 本研究以一個食譜分享社群網站為研究對象,針對網站上所提供的食譜建立了運用 kNN 分群演算法的自動分群機制,並利用該網站上使用者的使用行為進行分群後群集的特徵描述參考。
    本研究以三個階段建立了一針對食譜領域進行自動分群的資訊系統。第一階段為資料處理,在取得食譜網站上所提供的食譜資料後,雖然已經有相對結構化的格式可直接進行分群運算,然而由使用者所輸入的內容,仍有錯別字、贅詞、與食譜本身直接關連性不高等情形,因此必須進行處理。第二階段為資料分群,利用文字探勘進行內容特徵值的萃取,接著再以資料探勘的技術進行分群,分群的結果將會依群內的特徵、群間的相似度作為分群品質的主要指標。第三階段則為群集特徵分析,利用網站上使用者收藏食譜並加以分類的行為,運用統計的方式找出該群集的可能分類名稱。
    本研究實際以 500 篇食譜進行分群實驗,在最佳的一次分群結果中,可得到 10 個食譜群集、平均群內相似度為 0.4482,每個群集可觀察出明顯的相似特徵,並且可藉由網站上使用者的收藏行為,標註出其群集特徵,例如湯品、甜點、麵包、中式料理等類別。
    由於網站依照schema.org 所提供的食譜格式標準,針對網站上每一篇食譜內容進行了內容欄位的標記,本研究所實作之食譜分群機制,未來亦可運用在其他同樣採用 schema.org 所提供標準之同類型網站。
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    Description: 碩士
    國立政治大學
    資訊管理研究所
    97356002
    101
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0097356002
    Data Type: thesis
    Appears in Collections:[資訊管理學系] 學位論文

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