Resource Space Model (RSM) is a semantic data model for specifying, organizing, and retrieving resources based on classification of resources. An efficient index mechanism is critical for its implementation. However, ...
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How to reduce the amount of relevance judgments is an important issue in retrieval evaluation. In this paper, we propose a novel method using global statistics to rank retrieval systems without relevance judgments. In...
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A group of decision-makers may differ in their choice of alternatives while taking a decision. So, in any decision-making problem concerning decisions made by a group, the question arises how best we can aggregate ind...
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Fast stereoscopic video encoding becomes a highly desired technique because the stereoscopic video has been realizable for applications like TV broadcasting and consumer electronics. The stereoscopic video has high in...
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As the Web continues to grow, the pornographic texts in varied forms run rampant on Internet, despite repeated prohibitionsm. It severely does harms to the development of people's mental health and the stability o...
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This paper tries to fill the gap between Traditional Chinese Pulse Diagnosis (TCPD) and Doppler diagnosis by applying digital signal analysis and pattern classification techniques to wrist radial arterial Doppler bloo...
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Minimum Error Rate Training (MERT) as an effective parameters learning algorithm is widely applied in machine translation and system combination area. However, there exists an ambiguity problem in respect to the train...
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Traditional 1-best translation pipelines suffer a major drawback: the errors of 1- best outputs, inevitably introduced by each module, will propagate and accumulate along the pipeline. In order to alleviate this probl...
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Traditional 1-best translation pipelines suffer a major drawback: the errors of 1- best outputs, inevitably introduced by each module, will propagate and accumulate along the pipeline. In order to alleviate this problem, we use compact structures, lattice and forest, in each module instead of 1-best results. We integrate both lattice and forest into a single tree-to-string system, and explore the algorithms of lattice parsing, lattice-forest-based rule extraction and decoding. More importantly, our model takes into account all the probabilities of different steps, such as segmentation, parsing, and translation. The main advantage of our model is that we can make global decision to search for the best segmentation, parse-tree and translation in one step. Medium-scale experiments show an improvement of +0.9 BLEU points over a state-of-the-art forest-based baseline.
Parsing plays an important role in semantic role labeling (SRL) because most SRL systems infer semantic relations from I-best parses. Therefore, parsing errors inevitably lead to labeling mistakes. To alleviate this p...
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