Chunyang Wu

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Social networks have become more and more popular in recent years. This popularity creates a need for personalization services to recommend tweets, posts (information) and celebrities organizations (information sources) to users according to their potential interest. Tencent Weibo (microblog) data in KDD Cup 2012 brings one such challenge to the researchers(More)
We in this paper present the model for our participation (BCMI) in the CoNLL-2012 Shared Task. Following the work of (Lee et al., 2011), we extend their English deterministic corefer-ence resolution model to Chinese. This paper describes a pure rule-based method, which assembles different filters in a proper order. Different filters handle different(More)
Given the size of modern cities in the urbanising age, it is beyond the perceptual capacity of most people to develop a good knowledge about the beauty and ugliness of the city at every street corner. Correspondingly, for planners, it is also difficult to accurately answer questions like 'where are the worst-looking places in the city that regeneration(More)
Rapid adaptation of deep neural networks (DNNs) with limited un-supervised data remains a significant challenge. This paper investigates the combination of two schemes that have been proposed to address this problem: i-vector representations and multi-basis adap-tive neural networks (MBANNs). Two approaches for combining these schemes together are(More)
Due to the limitation of radio spectrum resource and fast deployment of wireless devices, careful channel allocation is of great importance for mitigating the performance degradation caused by interference among different users in wireless networks. Most of existing work focused on fixed-width channel allocation. However, latest researches have demonstrated(More)
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