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Increasingly large numbers of customers are choosing online shopping because of its convenience, reliability, and cost. As the number of products being sold online increases, it is becoming increasingly difficult for customers to make purchasing decisions based on only pictures and short product descriptions. On the other hand, customer reviews,(More)
Social Media is becoming major and popular technological platform that allows users discussing and sharing information. Information is generated and managed through either computer or mobile devices by one person and consumed by many other persons. Most of these user generated content are textual information, as Social Networks(Face book, Linked In),(More)
As online shopping becomes increasingly more popular, many shopping web sites encourage existing customers to add reviews of products purchased. These reviews make an impact on the purchasing decisions of potential customers. At Amazon.com for instance, some products receive hundreds of reviews. It is overwhelming and time restrictive for most customers to(More)
The aim of the present study was to investigate the cytotoxic activity of cytokine-induced killer (CIK) cells targeted by an epidermal growth factor receptor (EGFR)/CD3 bispecific antibody (BsAb) to the gastric cancer cell line SGC7901. A BsAb was constructed by chemically cross-linking a monoclonal antibody (McAb) against human CD3 with another McAb(More)
The rapid evolution of modern social networks motivates the design of networks based on users' interests. Using popular social media such as Facebook and Twitter, we show that this new perspective can generate more meaningful information about the networks. In this paper, we model user-interest based networks by deducing intent from social media activities(More)
In the post-genome era, huge numbers of protein structures accumulate, but little is known about their function. It is time consuming and labour intensive to investigate them, e.g., enzyme catalytic properties, through in vivo or in vitro work. So in silico predictions could be a promising strategy to greatly shrink the list of potential targets. This work(More)
We investigate a class of emerging online marketing challenges in social networks; macro behavioral targeting (MBT) is introduced as non-personalized broadcasting efforts to massive populations. We propose a new probabilistic graph-ical model for MBT. Further, a linear-time approximation method is proposed to circumvent an intractable paramet-ric(More)
Most of the existing active learning algorithms assume all the category labels as independent or consider them in a "flat" structure. However, in reality, there are many applications in which the set of possible labels are often organized in a hierarchical structure. In this paper, we consider the problem of active learning when the categories are(More)
Clustering similar items for web text has become increasingly important in many Web and Information Retrieval applications. For several kinds of web text data, it is much easier to obtain some external information other than textual features which can be utilized to improve the performance of clustering analysis. This external information, called prior(More)
The exponential rise of online content in the form of blogs, microblogs, forums, and multimedia sharing sites has raised an urgent demand for efficient and high-quality text clustering algorithms for fast navigation and browsing of users based on better document organization. For several kinds of these user-generated content, it is much easier to obtain the(More)