本文選題：多證據融合 + 視頻排序��； 參考：《電子學報》2010年01期

【摘要】：在視頻檢索中,通過對用戶行為特性的分析發(fā)現(xiàn),用戶通常只關注排在最前面的返回結果,而很少有耐心將所有的返回結果瀏覽一遍.因此,對于一個搜索引擎來說,能否將最相關的結果排在最前面是至關重要的.為了實現(xiàn)這一目標,本文提出了一種基于多證據融合的視頻排序方法.該方法利用Dempster-Shafer證據推理理論來協(xié)同地融合多方證據,進而推斷出最相關的視頻鏡頭.如果多方證據一致,則證明某個視頻鏡頭是相關的,此鏡頭被認為是最相關的鏡頭,并被排在返回列表的最前列.相反,如果多方證據產生沖突,那么此鏡頭就將被排在后面.實驗結果表明,利用建議的多證據融合排序算法,搜索引擎的搜索質量,特別是排在前列的搜索結果的準確性,有了明顯的改善.
[Abstract]:In video retrieval, by analyzing the behavior of users, it is found that users usually focus on the first result, and rarely have the patience to browse all the returned results once. Therefore, for a search engine, whether the most relevant results at the top is crucial. In order to achieve this goal, a video sorting method based on multi-evidence fusion is proposed. The method uses Dempster-Shafer evidence reasoning theory to fuse multi-party evidence and then infer the most relevant video shot. If the evidence is consistent, it proves that a video shot is relevant, which is considered the most relevant shot and is at the top of the return list. On the contrary, if multiple sources of evidence conflict, then this scene will be placed in the back. The experimental results show that the search quality of search engines, especially the accuracy of the first search results, has been improved obviously by using the proposed multi-evidence fusion sorting algorithm.
【作者單位】： 北京交通大學信息科學研究所;
【基金】：國家自然科學基金(No.60602030,60776794) 國家863高技術研究發(fā)展計劃(No.2007AA01Z175) 國家重點基礎研究發(fā)展計劃(No.2006CB303104) 教育部長江學者和創(chuàng)新團隊發(fā)展計劃(No.IRT707) 模式識別國家重點實驗室開放基金
【分類號】：TP391.41
，

本文編號：1915700