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    政大典藏 > College of Commerce > Department of MIS > Theses >  Item 140.119/153155


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/153155


    Title: 結合人格特質與動態信任之團體推薦系統
    Influence based Group Recommendation System in Personality and Dynamic Trust
    Authors: 黃誠恩
    Huang, Cheng-En
    Contributors: 林怡伶
    Lin, Yi-Ling
    黃誠恩
    Huang, Cheng-En
    Keywords: 團體推薦
    信任
    人格特質
    團體決策
    Group Recommendation
    Trust
    Personality traits
    Group decision-making
    Date: 2024
    Issue Date: 2024-09-04 14:04:43 (UTC+8)
    Abstract: 在日常生活中，團體活動頻繁進行，向用戶推薦內容成為一項重要任務。在異質團體中，成員偏好不一致可能導致衝突的產生。動態團體的挑戰在於調和其成員多樣化偏好，以達成所有成員滿意的團體決策。然而人格特質和關係等社會因子在促進團體決策中有關鍵作用，本研究採用了TKI性格特徵，這在緩解決策過程中的衝突表現良好。此外，我們開發了一種創新的動態信任機制，能夠更精準的捕捉團體內彼此變動的信任值，並將其整合到我們改良的團體推薦演算法中。為了達成研究目標，我們進行了一項為期兩週的實證研究，我們部署了一個響應式網頁。實驗中用戶會針對每個群組的兩個推薦清單進行評分，包含傳統聚合型和矩陣式演算法。通過本實驗，我們能夠更好地捕捉團體決策中社會因子的變動性，以達到更高的準確度和滿意度，並為團體餐廳推薦領域奠定里程碑。
    Given the frequent engagement in group activities within daily life, recommending content to a group of users becomes an important task. In heterogeneous groups, a conflict situation may arise more easily if the preferences of group members are incompatible. The challenge with dynamic groups lies in reconciling the diverse preferences of its members to reach a collective decision that satisfies everyone. While social dynamics such as personality traits, and mutual influence play a pivotal role in shaping group decision-making, this study employs the TKI personality traits, which have demonstrated efficacy in mitigating conflicts during group decision processes. Besides, we have developed a novel dynamic trust mechanism that adeptly captures the evolving trust values within a group integrated into our refined group recommendation algorithms. In order to achieve our research objectives, we executed a two-week empirical study by deploying a responsive web application tailored for our group recommendation system. Users in the experiment interacted with two distinct algorithms: traditional influence-based aggregation and the influence matrix algorithm at random. Through the experiment, we are able to better capture the variability of social factors in group decision-making, achieving higher accuracy and satisfaction as well as laying the foundation for a milestone in group recommendation within the restaurant domain.
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    Description: 碩士
    國立政治大學
    資訊管理學系
    111356030
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0111356030
    Data Type: thesis
    Appears in Collections:[Department of MIS] Theses

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