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博碩士論文 etd-0726107-140903 詳細資訊
Title page for etd-0726107-140903
論文名稱
Title
採用引用分析尋找關鍵文獻之專家系統
Key Paper Expert System Using Citation Analysis
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
79
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
2007-07-11
繳交日期
Date of Submission
2007-07-26
關鍵字
Keywords
引用分析、關鍵文獻、資料探勘、專家系統
Expert System, Data Mining, Citation Analysis, Key Paper
統計
Statistics
本論文已被瀏覽 5823 次,被下載 2219
The thesis/dissertation has been browsed 5823 times, has been downloaded 2219 times.
中文摘要
近年來由於網際網路的蓬勃發展,許多學術文獻資料庫也跟隨著快速增長,然而由於文獻資料庫的量不只龐大且繁雜,使用者很容易迷失在大量的搜尋結果之中,並且受到資料庫及期刊收錄範圍的限制。近年來引用分析(Citation Analysis)已經被廣泛的應用在許多領域,因此本研究利用引用分析建立專家系統來針對文獻資料庫中的文章進行分析,進一步找出重要程度與影響力較高,足以代表此一領域的「關鍵文獻」。此外由於引用分析又可分為直接引用和間接引用,過去研究大多採直接引用,並未整合間接引用,有學者指出間接引用具有其價值存在,因此本研究提出了完整引用的計算公式,整合直接引用及間接引用來建立尋找關鍵文獻之專家系統,除了協助使用者找出更正確的關鍵文獻外,並且以視覺化的方式呈現文獻與文獻之間的關係給使用者參考。最後本研究利用資管領域的六大期刊共7579篇文章進行分析,從中萃取出了129114篇文獻引用資料評估此系統的正確性,研究結果發現,本研究間接引用會造成些微影響,但是直接引用和完整引用都能判斷出正確的關鍵文獻,並且能發現資料範圍外的關鍵文獻,甚至包含了相關重要書籍,而在找尋關鍵文獻時,只需針對該領域前三大期刊進行分析,不必將所有的資料範圍收錄。
Abstract
Recently, Internet has been used widely. Many scholar digital libraries have also followed this trend and grown up quickly. However, information in these digital libraries is complex and huge. Users are difficult to discover papers they need; instead, they often get lost in the information. When they search these digital libraries, they are also limited to the documents which are embodied in these digital libraries, and can not locate important papers in other journals. Citation Analysis has been used in many areas and it is used in this research to build an expert system. Further, we will discover important papers which can represent these research areas. We called these papers as “Key Papers”. A citation can be classified by its relation as “Direct Citation” and “Indirect Citation”. Many researchers showed that indirect citations held influence, but in the past they just used direct citations to calculate importance and neglected indirect citations. This research combined direct and indirect relations into one index, and used this index to build the expert system. In addition, we provided a visualization of papers’ citation relations, and helped users to find key papers in their research areas. In order to test our system, we collected the top six journals in MIS, totally 7579 papers, and extracted 129114 citations from these papers. The result showed no differences between direct and indirect citations. However, key papers that didn’t belong to these journals could be discovered, and using top three journals could obtain the same result as found in using top six journals.
目次 Table of Contents
致謝 I
摘要 II
Abstract III
目錄 IV
表目錄 VI
圖目錄 VIII
第一章、 緒論 1
第一節、 研究背景與動機 1
第二節、 研究目的 3
第三節、 研究範圍 4
第四節、 論文架構 4
第二章、 文獻探討 6
第一節、 專家系統 6
第二節、 引用分析 11
第三章、 研究方法 15
第一節、 研究方法 15
第二節、 研究流程 18
第四章、 系統建置 21
第一節、 系統架構 21
第二節、 資料描述 35
第三節、 系統畫面 35
第五章、 研究結果 40
第一節、 系統評估 40
第二節、 視覺化呈現 56
第六章、 結論 60
第一節、 研究成果 61
第二節、 研究貢獻 62
第三節、 研究限制 63
第四節、 未來研究方向 63
參考文獻 65
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