The previous work has justified the assumption that document ranking can be improved by further considering the coarse-grained relations in various linguistic levels (e.g., lexical, syntactical and semantic). To the best of our knowledge, little work is reported to incorporate the fine-grained ontological relations (e.g., ) in document ranking. Two contributions are wo...

super eciency data envelopment analysis(dea) model can be used in ranking the performanceof ecient decision making units(dmus). in dea, non-extreme ecient unitshave a super eciency score one and the existing super eciency dea models do notprovide a complete ranking about these units. in this paper, we will propose a methodfor ranking the performance of the extreme and non-extreme ecient u...

in many applications, ranking of decision making units (dmus) is a problematic technical task procedure to decision makers in data envelopment analysis (dea), especially when there are extremely efficient dmus. in such cases, many dea models may usually get the same efficiency score for different dmus. hence, there is a growing interest in ranking techniques yet. the purpose of this paper is ra...

We propose a new item-ranking method that is reliable and can efficiently identify high-quality items from among a set of items in a given category using their review-scores which were rated and posted by users. Typical ranking methods rely only on either the number of reviews or the average review score. Some of them discount outdated ratings by using a temporal-decay function to make a fair c...

Automatic evaluation of machine translation (MT) systems is an important research topic for the advancement of MT technology. Most automatic evaluation methods proposed to date are score-based: they compute scores that represent translation quality, and MT systems are compared on the basis of these scores. We advocate an alternative perspective of automatic MT evaluation based on ranking. Inste...

We present the notion of Ranking for evaluation of two-class classifiers. Ranking is based on using the ordering information contained in the output of a scoring model, rather than just setting a classification threshold. Using this ordering information, we can evaluate the model's performance with regard to complex goal functions, such as the cor rect identification of the k most likely and/or...

Super eciency data envelopment analysis(DEA) model can be used in ranking the performanceof ecient decision making units(DMUs). In DEA, non-extreme ecient unitshave a super eciency score one and the existing super eciency DEA models do notprovide a complete ranking about these units. In this paper, we will propose a methodfor ranking the performance of the extreme and non-extreme ecient units.

We develop a multi-period theoretical model to characterize the relationship between a publication that ranks universities and prospective attendees – high school students – who might view the ranking and use it to help decide which university to attend. We assert that published rankings not only offer information about the objective quality of universities, but also have an effect on the prest...