歷年獲獎名單

2016人民網獎學金獲獎名單：

徐安民、唐翯?
2016人民網優秀技術課題獲獎者名單：
一等獎：賴澤祺、戴檸薇、王吉磊
二等獎：王竹凡、賈許亞、郭澤華、吳振未、
　　　　周琳鈞
三等獎：吳鬆芮

優秀技術課題一等獎（2）

VR技術及其新聞應用前景研究: 本文首先介紹VR技術及其在新聞、出版行業的應用前景，並提出當今VR技術面臨的三大重要挑戰。為了讓VR應用獲得更好的用戶體驗，本文提出QuickView，一套運行於當今智能終端上的渲染遷移框架。QuickView將復雜而高功耗的渲染任務通過網絡傳遞到強大的雲端，由雲端完成高計算量的圖像渲染工作，最終返回終端並回顯給用戶。為了克服無線網絡下高延遲，帶寬有限的挑戰，QuickView採用了兩項新技術：基於網絡狀態的用戶行為預測和低延遲帶寬的渲染遷移網絡協議。我們實現了QuickView原型系統，並且將QuickView和傳統的本地渲染的VR應用進行對比。實驗証明，QuickView可以提升大約59%的幀刷新率，降低68%的用戶感知時延，降低90%的平均功耗。我們相信，未來QuickView渲染遷移框架將會為更多的新聞、出版類VR應用提升更加便攜的使用，更優質的視頻服務質量，以及保証更長時間的續航。; 詳細 >>

Learning Chinese-Japanese Bilingual Word Embedding by Using Common Characters: Abstract. Bilingual word embedding, which maps word embedding of two languages into one vector space, has been widely applied in the domain of machine translation, word sense disambiguation and so on. However, no model has been universally accepted for learning bilingual word embedding. In this work, we propose a novel model named CJ- BOC to learn Chinese-Japanese word embeddings. Given Chinese and Japanese share a large portion of common characters, we exploit them in our training process. We demonstrated the effectiveness of such exploitation through theoretical and also experimental study. To evaluate the performance of CJ-BOC, we conducted a comprehensive experiment, which reveals its speed advantage, and high quality of acquired word embeddings as well.; 詳細 >>

基於在線自適應多重外觀模型的長期視頻跟蹤模型: 如何構建被跟蹤目標的外觀描述是進行長期魯棒的目標跟蹤的基本挑戰。在最近的研究中，許多跟蹤方法更注重更新跟蹤目標的當前外觀，通過採用特殊的視覺特征和學習方法來構建一個在線外觀模型。然而，單個外觀模型總是不足以描述歷史出現信息，且無法應對照明變化和目標被切割的情況，對於長期跟蹤任務這些情況會出現的更多。在本文中，我們提出在線自適應多重模型以提高目標跟蹤性能。通過構建基於Dirichlet過程混合模型（DPMM）的外觀模型集合，其可以動態地且以無監督的方式將跟蹤目標的不同外觀進行分組。盡管DPMM具有如上有點，但DPMM依賴於吉布斯取樣器這個計算密集的推斷過程。由於目標跟蹤對逐幀處理的效率要求較高，吉布斯取樣器因為時間成本高不適合跟蹤。所以在原有的DPMM模型基礎上，我們提出了一種在線貝葉斯學習算法，通過以流的方式通過順序逼近從頭開始可靠和有效地學習DPMM以適應新的跟蹤目標。在多個具有挑戰性的基准公共數據集上進行的實驗証明了所提出的跟蹤算法優於現有技術。; 詳細 >>

Reducing and Balancing Flow Table Entries in Software-Defined Networks: Software-Defined Networking (SDN) allows flexible and efficient management of networks. However, the limited capacity of flow tables in SDN switches hinders the deployment of SDN. In this paper, we propose a novel routing scheme to improve the efficiency of flow tables in SDNs. To efficiently use the routing scheme, we formulate an optimization problem with the objective to maximize the number of flows in the network, constrained by the limited flow table space in SDN switches.The problem is NP-hard, and we propose the K Similar Greedy Tree (KSGT) algorithm to solve it. We evaluate the performance of KSGT against ``traditional" SDN solutions with real-world topologies and traffic. The results show that, compared to the existing solutions, KSGT can reduce about 60% of flow entries when processing the same amount of flows, and improve about 25% of the successful installation and forwarding flows under the same flow table space..; 詳細 >>

跨平台的音樂推薦算法: 傳統的音樂推薦算法往往是根據用戶的聽歌記錄來對其進行推薦，但是對於一個新用戶傳統的推薦算法就無能為力了。在本文中，我們使用機器學習中典型關聯分析（CCA）技術期望能夠通過加入用戶的社會屬性（微博）來改進原始的推薦算法，從而更加精准的推薦給用戶他們喜歡聽的音樂，另外，相較於其他推薦算法，我們能夠實現推薦的冷啟動。即使用戶之前沒有聽過任何音樂，我們也能夠從他的微博數據中挖掘出他喜歡聽的音樂類型。; 詳細 >>

Incremental Switch Deployment for Hybrid Software-Defined Networks: Software-Defined Networking (SDN) brings excellent opportunities to improve network performance by flexible flow control with a centralized network view. However, due to budget constraints and technique limitations, ISPs can upgrade only a limited number of conventional switches in real backbone networks to SDN devices at one time. In this paper, we propose one heuristic scheme to increase the deployment of SDN switches in hybrid SDNs, which are composed of conventional and SDN switches. Our scheme works for two different cases: (1) maximizing the network control ability with a given upgrading budget constraint, and (2) minimizing the upgrading cost to achieve the best network control ability. The results show that our scheme can achieve 95\% of the number of flows controlled with only 10% upgrading cost. We evaluate our scheme in two topologies, the ISP 1755 and the ISP 3967 from the real network..; 詳細 >>

基於密文的數據范圍搜索算法設計與實現: 隨著大數據的發展，大規模的數據越來越多的以密文的形式存儲在雲服務器中。本文重點討論了在雲服務器中，如何對已加密的數據進行快速的范圍搜索。當可信任的數據持有者將加密的數據上傳到雲服務器后，雲服務器支持大量的用戶搜索數據，並在不可解密數據及查找范圍的前提下，對數據搜索進行精確的匹配。本文提出了通過建立安全索引的方式對一維、二維數據進行范圍查詢的模型，並用百萬的數據驗証了方法的可行性與正確性。; 詳細 >>