Abstract. Today, bibliographic digital libraries play an important role in helping members of academic community search for novel research. In particular, author disambiguation for citations is a major problem during the data integration and cleaning process, since author names are usually very ambiguous. For solving this problem, we proposed two kinds of correlations between citations, namely, Topic Correlation and Web Correlation, to exploit relationships between citations, in order to identify whether two citations with the same author name refer to the same individual. The topic correlation measures the similarity between research topics of two citations; while the Web correlation measures the number of co-occurrence in web pages. We employ a pair-wise grouping algorithm to group citations into clusters. The results of experiments show that the disambiguation accuracy has great improvement when using topic correlation and Web correlation, and Web correlation provides stronger evidences about the authors of citations.

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Predicting prices and risk measures of assets and derivatives and rating of financial products have been studied and widely used by financial institutions and individual investors. In contrast to the centralized and oligopoly nature of the existing financial information services, in this paper, we advocate the notion of a FinancialCloud, i.e., an open distributed framework based cloud computing architecture to host modularize financial services such that these modularized financial services may easily be integrated flexibly and dynamically to meet users' needs on demand. This new cloudbased architecture of modularized financial services provides several advantages. We may have different types of service providers in the ecosystem on top of the framework. For example, market data resellers may collect and sell long-term historical market data. Statistical analyses of macroeconomic indices, interest rates, and correlation of a set of assets may also be purchased online. Some agencies might be interested in providing services based on rating or pricing values of financial products. Traders may use the statistically estimated parameters to fine-tune their trading algorithm to maximize the profit of their clients. Providers of each service module may focus on effectiveness, performance, robustness, and security of their innovative products. On the other hand, a user pays for exactly what one uses to optimally manage their assets. A user may also acquire services through an online agent who is an expert in assessing the structural model and quality of existing products and thus assembles service modules matching users risk taking behavior. In this paper, we will also present a survey of related existing technologies and a prototype we developed so far.

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