Several methods for feature selection and weighting have been implemented and tested within the similarity-based framework of classification methods. Features are excluded and ranked according to their contribution to the classification accuracy in the crossvalidation tests. Weighting factors used to compute distances are optimized using global minimization procedures or search-based methods. O...

The rapid growth of web applications increases the need to evaluate web applications objectively. In the past few years some valuable works like WebQEM tried to objectively evaluate the web applications. However, still weighting web attributes which is one step of evaluation of web applications is completely subjective, depending mostly on experts’ judgments. In this paper a two-step weighting ...

Instance-weighting has been shown to be effective in statistical machine translation (Foster et al., 2010), as well as crosslanguage adaptation of dependency parsers (Søgaard, 2011). This paper presents new methods to do instance-weighting in stateof-the-art dependency parsers. The methods are evaluated on Danish and English data with consistent improvements over unadapted baselines.

Combined with weight of samples and kernel function, fuzzy clustering method with generalized entropy is studied. Objective function for fuzzy clustering with generalized entropy based on sample weighting is obtained. Following that, fuzzy clustering algorithm with generalized entropy based on sample weighting is presented. In addition, by introducing kernel into the presented objective functio...

Instance weighting has been widely applied to phrase-based machine translation domain adaptation. However, it is challenging to be applied to Neural Machine Translation (NMT) directly, because NMT is not a linear model. In this paper, two instance weighting technologies, i.e., sentence weighting and domain weighting with a dynamic weight learning strategy, are proposed for NMT domain adaptation...