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https://nccur.lib.nccu.edu.tw/handle/140.119/32706
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Title: | 由全球資訊網探勘學術研究領域的本體論資訊 |
Authors: | 周大鈞 Chou, Ta-Chun |
Contributors: | 沈錳坤 Shan, Man-Kwan 周大鈞 Chou, Ta-Chun |
Keywords: | 本體論 學術研究 全球資訊網 資料探勘 Ontology Academic research WWW Data mining |
Date: | 2004 |
Issue Date: | 2009-09-17 14:06:05 (UTC+8) |
Abstract: | 對學者而言,其研究主題的本體論資訊,包括有影響力的論文、有影響力的會議、有影響力的期刊和有影響力的研究者等資料,是學術研究的重要資訊。利用研究主題的本體論資訊,就能對該領域有大致的瞭解。因此本研究的目的,就是針對特定研究主題,自動的從WWW中,探勘出此主題的本體論資訊,包含此主題中有影響力的論文、作者、會議和期刊。 我們先從WWW上透過CiteSeer取得與主題相關的學術論文,再透過引用關係去擴充論文集合。由這些論文中利用資訊萃取的技術,找出論文出處和作者。接著分別根據引用關係分析論文、會議、期刊和作者的影響力指標,我們也考慮論文、會議、期刊和作者之間的mutual reinforcing relation,修改Webpage Ranking Algorithms,來幫助計算由論文引用關係所得的影響力指標。 我們實做出系統,提供使用者查詢特定研究主題的本體論資訊,並且找出相關學者、期刊、論文的網站。我們請具有該研究主題專長的學者,評估系統的效果,得出將近60%的準確率。 Ontological information of research topic, that includes influential papers, conferences, journals, and authors, is the important information of academic research for researchers. Ontological information gives an overview of specific research topic for researchers. Our research is to discover the ontological information of specific research topic from WWW. Firstly, we collect papers that related to specific research topic. These papers are collected by querying CiteSeer. The dataset of papers is extended by citation information further. Then, the metadata of these papers is extracted by Information Extraction technique. After analyzing the influence of papers, conferences, journals, and authors individually based on citation analysis, the influence between them will be considered mutually. We modify the Webpage Ranking Algorithms to be adapted in our research for mutual reinforcing relation analysis. We implemented a system that offers users the ontological information of specific research topic after querying from this system. And discover the website of related authors, conferences, and journals. The results evaluated by experts in specific topic are near sixty percent correct. |
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Description: | 碩士 國立政治大學 資訊科學學系 91753003 93 |
Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0917530031 |
Data Type: | thesis |
Appears in Collections: | [資訊科學系] 學位論文
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