This paper studies the problem of identifying the contagion source when partial timestamps of a contagion process are available. We formulate the source localization problem as a ranking problem on graphs, where infected nodes are ranked according to their likelihood of being the source. Two ranking algorithms, cost-based ranking (CR) and tree-based ranking (TR), are proposed in this paper. Exp...

We discuss the problem of ranking objects sampled from in general r ordered categories. A ranking model for this kind of data can be visualized as a (layered) ranking graph having a single source and sink, and the number of paths connecting source and sink is seen as a ranking-based performance measure. In this article we consider learning such a graph as a structured output in a convex optimiz...

Multi-parallel corpora provide a potentially rich resource for machine translation. This paper surveys existing methods for utilizing such resources, including hypothesis ranking and system combination techniques. We find that despite significant research into system combination, relatively little is know about how best to translate when multiple parallel source languages are available. We prov...

Source retrieval involves making use of a search engine to retrieve candidate sources of plagiarism for a given suspicious document so that more accurate comparisons can be made. We describe a strategy for source retrieval that uses a supervised method to classify and rank search engine results as potential sources of plagiarism without retrieving the documents themselves. Evaluation shows the ...

The iTrust system is a decentralized and distributed system for publication, search and retrieval of information over the Internet and the Web, that is designed to make it difficult to censor or filter information. In the distributed ranking algorithm for iTrust presented in this paper, a source node that publishes a document indexes the words in the document and produces a term-frequency table...

This paper regards the query keywords selection problem in source retrieval as learning a ranking model to choose the method of keywords extraction over suspicious document segments. Four basic methods are used in our ranking function: BM25, TFIDF, TF and EW. Then, a ranking model based on Ranking SVM is proposed to rank the query keywords group which is contributed to get the higher evaluation...

Although every terminating loop has a ranking function, not every loop has a ranking function of a restricted form, such as a lexicographic tuple of polynomials over program variables. We propose polyranking functions as a generalization of ranking functions for analyzing termination of loops. We define lexicographic polyranking functions in a general context and then specialize their synthesis...