Yiheng Chen

Learn More
SOM and k-means are two classical methods for text clustering. In this paper some experiments have been done to compare their performances. The sample data used is 420 articles which come from different topics. K-means method is simple and easy to implement; the structure of SOM is relatively complex, but the clustering results are more visual and easy to(More)
Product aspect recognition is a key task in fine-grained opinion mining. Current methods primarily focus on the extraction of aspects from the product reviews. However, it is also important to cluster synonymous extracted aspects into the same category. In this paper, we focus on the problem of product aspect clustering. The primary challenge is to properly(More)
Predicting the box-office revenue of a movie before its theatrical release is an important but challenging problem that requires a high level of Artificial Intelligence. Nowadays, social media has shown its predictive power in various domains, which motivates us to exploit social media content to predict box-office revenues. In this study, we employ both(More)
—This paper deals with the problem of proactive survivability of Virtual Networks (VNs) residing in a cloud data center. In all of the previous work, the protection schemes consists of augmenting the VNs with a predetermined number of backup nodes. Further, to reduce the amount of provisioned resources, various backup resource sharing schemes are(More)
  • 1