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博碩士論文 etd-0818110-113700 詳細資訊
Title page for etd-0818110-113700
論文名稱
Title
利用使用者和產品區隔進行信任為主的推薦之研究
Using Trust for Recommendation by Differentiating Users and Products
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
47
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2010-06-29
繳交日期
Date of Submission
2010-08-18
關鍵字
Keywords
使用者偏見、電子商務、產品爭議性、信任網路、推薦系統
User bias, Product Controversy, Trust Network, Recommender System, E-commerce
統計
Statistics
本論文已被瀏覽 5919 次,被下載 1406
The thesis/dissertation has been browsed 5919 times, has been downloaded 1406 times.
中文摘要
身處於資訊爆炸的時代,如何快速從網站中有效率地找到所需要的資訊是一件非常困難的事情。對使用者而言,瀏覽、搜尋並決定是否從網路商店中購買產品都是一件費時的工作。因此,許多電子商務網站開始引進推薦機制系統,企圖提供使用者從多樣化的產品與服務中,達到個人客制化的推薦。雖然許許多多的推薦機制方法已經被提出,但是仍然存在許多的問題需要去克服,像是資料稀疏性和新使用者…等相關問題。除此之外,有些學者也發現使用者存在著偏見性、產品存在著可爭議性。我們推測,這些來自於有偏見的使用者、或是對於爭議性的產品所下的評分,可能會對於推薦系統的評估正確性與否造成影響。在這篇論文中,我們將檢驗使用者偏見性和產品爭議性的指標,並提出以信任為基準的推薦機制為做實驗的考量。我們從Epinions.com網站收集信任以及評分資訊作為我
們實驗的資料。研究結果顯示出,適當調整一些變數,整合使用者偏見性做為調整信任基礎推薦機制的架構後,將達到比較高的推薦正確性。
Abstract
Living in the information-overloading age, it is difficult to find the right information and
identify the resources they need on the websites. As to a user, it is time-consuming in browsing,
searching, and making a decision to buy products on online stores. Therefore, many
E-commerce websites have implemented recommender systems that intend to provide users
with professional recommendation for various types of products and services. Although many
recommendation methods have been proposed, there are still some problems like the sparsity
and the cold start problems. In addition, some researchers observe there exist users who are
biased and products that are controversial. We conjecture that ratings given by biased users or
given to controversial products may have impact on estimation accuracy of recommendation. In
this thesis, we will examine the measures for user bias and product controversy and propose
trust-based-recommendation techniques that take them into account. We evaluate the proposed
techniques using the web of trust and rating data collected from the Epinions.com website. It is
found that properly setting some parameters, the proposed trust network-based method that
incorporates user bias achieve higher recommendation accuracy.
目次 Table of Contents
CHAPTER 1 - Introduction.............................................................................. 9
1.1 Background .....................................................................................................................9
1.2 Motivation ..................................................................................................................... 10
CHAPTER 2 - Literature Review .................................................................. 12
Recommender Systems ....................................................................................................... 12
2.1.1 Content-based Methods .............................................................................................. 12
2.1.2 Collaborative Methods ................................................................................................ 14
2.2 Social Network Analysis ............................................................................................... 16
2.2.1 The Elements of Social Network ............................................................................. 16
2.2.2 The Structural Properties of Social Network ........................................................... 17
2.3 The Trust-Aware Recommendation ............................................................................... 17
2.3.1 Measuring Trust ...................................................................................................... 18
2.3.2 Adjusting Trust ....................................................................................................... 18
2.3.3 Trust Propagation.................................................................................................... 18
2.3.4 Making Recommendation ....................................................................................... 20
2.4 Differentiating Users and Products ................................................................................ 20
2.5 Malicious Users Attack .................................................................................................. 23
CHAPTER 3 - Recommendations Approaches Based on Trust Network.... 24
3.1 Problem definition ......................................................................................................... 24
3.2 The Trust Network Propagation ..................................................................................... 25
3.3 Differentiating Users and Products ................................................................................ 26
3.4 Making Recommendation .............................................................................................. 26
CHAPTER 4 - Experiments............................................................................ 28
4.1 Data Collection .............................................................................................................. 28
4.2 Data Set Generation ....................................................................................................... 28
4.3 Preliminary Experiments ............................................................................................... 29
4.4 Distribution of User Bias and Product Controversy ........................................................ 34
4.5 Extend Experiments ....................................................................................................... 37
4.6 Coverage of Different Thresholds .................................................................................. 40
4.7 Experiment Using Constant Decline of Bias Users ......................................................... 40
4.8 Evaluation of Adjusting Collaborative Filtering Method ................................................ 41
CHAPTER 5 - Conclusion .............................................................................. 43
References ........................................................................................................ 44
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