每一項學術研究進行，其理論基礎都必需要建立於過去已完成的研究之上，因此文獻尋找與探討是進行研究過程非常重要的一個步驟。在數位時代與網際網路的加乘效益之下，改變了過去研究者必需為參考文獻東奔西跑的文獻資料尋找方式，但是卻會造成研究者被許多數位文獻淹沒。借用自網頁分析技術而設計的Google學術搜尋網路工具，能透過已經計算好的文獻權重PaperRank排序使用者所尋找的文獻集合，讓使用者能在數位文獻之中依單篇文獻被引用次數為原則而理出頭緒，但其順序式的排列仍然不能夠揭露出搜尋到的文獻集合裡彼此之間的關聯，其中包括了文獻所使用的關鍵字、作者與參考文獻。為了處理了解文獻中多維度的複雜資料關聯，最好的方式還是依賴人類的視覺化資訊處理能力，特別是當資料量大並且需要在短時間內決策時。 此外使用在文獻分析研究中，學者們使用共同引用(co-citation)、共同作者(co-work)、共同作者引用(co-author)等分析方式，配合延伸自社會網路分析理論中的社會密度(social distance)、關聯層級(social degree)、群(clique)等參數概念，試將複雜的文獻資料有脈絡地按排供參考。僅管此是工作難以機械化且消耗時間的(Börner, Chen , Boyack, 2003)，但是卻能將某一特定領域的發展直覺地呈現出來，如此若能將這些分析方式配合視覺化的呈現，則研究學者便能更進一步了進行大量文獻資料視覺化的分析、探索。 本研究試提出一個新的協助文獻探索平台系統架構，將傳統的文字搜尋轉變為視覺化的資料探索。使用者能透過三種不同的層級的資料：知識本體與關鍵字層、引文網路層及人員網路層，並與呈現的資料互動進一步了解資料間的關聯方式。最後實作視覺化雛型平台，並使用在國家圖書館所提供的博、碩士論文網所提供的論文資料，提供給研究人員探索特定知識領域中新研究方向的探索工具，並能協助研究者能在尚未完瞭解的專業領域之前，能快速地瞭解在該其領域重要文獻的導引平台。 / Paper survey is the most important task for building earnest theories, while researchers conducting academic researches. One must touches the fundamental detail of each theory and track down the develop-path of what achievement have been established by previous researches. Benefit from synergy of information age and document digitalized, it not only reduces the cost of finding reference documents, but also makes researchers suffer from information overwhelming after click single “search it” bottom. Stand in for traditional paper web search methods, new academic paper search technology borrowing from the idea of web search engine calculates the importance of each paper by cited number, and recommends users the most important papers by serial listing. However, serial listing does never spell the relationships of suggesting papers out, but only those results match some specific criteria. Those relationships of papers can be classified into 3 different types: the relations of keywords and references that author used and social relationship of authors like co-author and author co-citation which have been developed to explain the complex citation network structures. Those multi-dimensional relationships are extremely abundant and complex, so there is no better way to deal with but depending on visual data processing within human nature. In this paper, we try to propose a new platform to transform paper search in serial listing, into a visualized explore platform by demonstrating 3 different types of relationship: ontology-keywords, papers-references and personnel-references. End users can fallow the relationships between each difference nodes to explore considerable references, as well as change into different view and interact with existing information by using interactive mechanizes. In order to bring this idea to practical application usage, we build a proto-type platform to show our idea by using data from ETDS (electronic theses and dissertations system) of Ministry of education. We hope sincerely by using this proto-type platform, users can catch the major ideas of specific knowledge domain and researchers can explore acceptable references and even conduct new search topic.