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博碩士論文 etd-1015116-102219 詳細資訊
Title page for etd-1015116-102219
論文名稱
Title
在社群網路上以距離和移動速度為基礎的相似度排序方法
A Similarity Ranking Method based on Distance and Velocity for Social Networks
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
70
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
2016-10-06
繳交日期
Date of Submission
2016-11-15
關鍵字
Keywords
社群網路、排序、相似度、距離、移動速度
Distance, Similarity, Velocity, Ranking, Social networks
統計
Statistics
本論文已被瀏覽 5816 次,被下載 42
The thesis/dissertation has been browsed 5816 times, has been downloaded 42 times.
中文摘要
本論文提出在社群網路上以距離和移動速度為基礎的相似度(Similarity)排序方法,除了針對詢問者與朋友對於同一個物品的喜愛程度而產生的相似度排序,我們了解到如果在實際生活上將相似度應用會使相似度的準確度下降,那是因為我們無法得知朋友是否能立即到達詢問的位置且與詢問者一起做共同喜好的事情,我們在以相似度為基礎下考慮朋友和詢問者的距離以及朋友的移動速度,根據以上提到的兩項因素我們設計了MDBS (Modified Distance-based Similarity)演算法,MDBS在相似度為正時我們直接將其值由大到小排序,但是在相似度為負且詢問者與朋友的距離相同時,我們提出一個演算法來修正其排序,在此演算法中,我們將朋友分成兩種,一種為固定的移動速度,另外一種為不同的移動速度,為了驗證我們在固定移動速度以及移動速度不同下的MDBS演算法,我們分析20位朋友在不同相似度、不同距離以及不同移動速度下的排序。從數值分析的結果中,我們可以發現朋友與詢問者的距離以及朋友抵達詢問者的時間改變了詢問者與朋友的相似度排序,不同於以往只是單純以相似度為基礎的排序方法,本論文使用詢問者與朋友間的距離與不同的移動速度來作相似度的排序更能反映出現實生活中的社群網路。
Abstract
In this thesis, we propose a novel similarity ranking based on the distance and velocity. In addition to ranking similsrity between query user and friend’s perfrence for the same item.We konw that the accuaacy of similarity will reduce in reality.It is because we can not know whether a friend can immediately reach the location of the inquiry and asked to do with the common interests of things. We consider friend’s distance and velocity based on similarity. According to two factors as mentioned, we designed MDBS (Modified Distance-based Similarity) algorithm. If the similarity is positive, in MDBS, we order it from large to small directly. When the similarity is negative and friends have the same distance, we propose an algorithm to modify the original order. In the algorithm, we divide friends into two categories; fixed speed and different speeds. In order to validate the algorithm, we use 20 friends as an example. In the numerical analysis, we compute the MDBS ranking based on two different situations, i.e., fixed velocity and variable velocity. From the numerical results, we found out that the MDBS ranking can be varied significantly due to different friends’ distance and velocity. Different from the traditional similarity ranking, in this theis, we consider distance between query user and friends and different moving speed of friends,the MDBS ranking can adequately represent the real life of a social network.
目次 Table of Contents
致謝……………………. i
摘要……………………………………………………………………....ii
Abstract. iii
目錄......... iv
圖表目錄 vi
第一章 導論 1
1.1 研究動機 1
1.2 研究方法 1
1.3 章節介紹 2
第二章 社群網路上的相似度 3
2.1 相似度的定義 3
2.2 詢問者與朋友間的關係 4
2.3 相關研究 5
第三章 考慮距離與移動速度的相似度 9
3.1 系統架構 9
3.2 MDBS架構 10
3.2.1 固定移動速度的MDBS 15
3.2.2 移動速度可能不同的MDBS 29
第四章 數學分析與結果討論 32
4.1 參數的設定 32
4.2 數值分析 33
4.2.1固定移動速度的MDBS 33
4.2.2 移動速度不同的MDBS 36
4.2.3 固定速度與不同速度的MDBS比較 38
第五章 結論與未來工作 47
5.1 結論 47
5.2 遭遇的困難 47
5.3 未來的工作 47
Reference 49
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