專利先前技術檢索主要用來辨別一個專利的先前技術，其應用在協助判斷專利的新穎性及侵權檢索。專利為擴大其權利範圍所造就的特殊文體結構是過去檢索研究常面臨的困難之一。在本研究中，我們致力於採用引證的關聯做為專利檢索中查詢擴展的特徵值以增進檢索的效能。我們假設一群具有相同引證的專利，他們在技術領域上是較具關聯的。因此針對欲查詢專利文件，我們先檢索出一些內文相似的專利集合，經過專利集合的引證分析，選出數個專利文件反饋給原查詢專利。我們從USPTO中搜集14,928篇專利並設計一系列的實驗來對全文探勘技術、傳統查詢擴展技術及我們所提出來技術進行比較。經實驗結果顯示我們所提的方法能得到更佳的檢索結果。

Prior art retrieval refers to the process of identifying relevant prior arts for a given patent (or patent application). Prior art retrieval task is mainly used to support patent validity search or patentability search. Patent applicants often use peculiar or abstract terms to enlarge the legal monopoly scope of patents, which make the prior art retrieval a difficult task. However, existing techniques for prior art retrieval encounter some limitations. In response, we propose the citation-relatedness-based relevance feedback prior art retrieval (CRF-PAR) technique, which incorporates citation information of patents as knowledge source for performing relevance feedback. A hybrid similarity measure which combines text-based and citation-based similarities between patents is proposed to select top-ranked patents for expanding the original query patent. The expanded query patent is then applied to perform prior art retrieval. For empirical evaluation purpose, we collect 14,928 patents documents from the United States Patent and Trademark Office (USPTO) website and conduct a series of experiments using a traditional text-based prior art retrieval and a traditional relevance-feedback-based prior art retrieval as the performance benchmarks. Our evaluation results suggest that our proposed technique outperforms its benchmark techniques, measured by the top-m recall rate.

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