We propose Maximum Ranking Correlation (MRC) as an objective function in discriminative tuning of parameters in a linear model of Statistical Machine Translation (SMT). We try to maximize the ranking correlation between sentence level BLEU (SBLEU) scores and model scores of the N-best list, while the MERT paradigm focuses on the potential 1best candidates of the N-best list. After we optimize t...

Information searching is the most popular activity in Internet. Usually the search engine provides the search results ranked by the relevance. However, for a certain purpose that concerns with information credibility, particularly citing information for scientific works, another approach of ranking the search engine results is required. This paper presents a study on developing a new ranking me...

Despite a variety of theoretical-sound techniques have been proposed for biometric template protection, there is rarely practical solution that guarantees non-invertibility, cancellability, non-linkability and performance simultaneously. In this paper, a ranking-based representational transformation is proposed for fingerprint templates. The proposed method transforms a real-valued feature vect...

We propose a novel framework and an algorithm for mining gradual dependencies between attributes in a data set. Our approach is based on the use of fuzzy rank correlation for measuring the strength of a dependency. It can be seen as a unification of previous approaches to evaluating gradual dependencies and captures both, qualitative and quantitative measures of association as special cases.