Ranking Models
Re Ranking Models Based on Small Training Data for Spoken Language Understanding
... The model used to obtain the SVM baseline for concept classification was trained using YamCHA (Kudo and Matsumoto, 2001). As re-ranking models based on structure kernels and SVMs, we used the SVM-Light-TK ...
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Ranking of DMUs by using TOPSIS and dierent ranking models in DEA
... portant ranking methods, existing in literature. As each of existing ranking methods have some major benefits that other do not have and the fact that it is not possible to gather all these ad- vantages in ...
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Extended HMM and Ranking Models for Chinese Spelling Correction
... For the context-sensitive spelling errors, there are two major kinds of processing methods: Rule-based methods and Statistics-based meth- ods. Rule-based methods use some rules generat- ed fromrelevant grammars, the ...
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Neural Ranking Models for Temporal Dependency Structure Parsing
... Bottom rows in Table 5 report the end-to-end performance of our five systems on both domains. On both labeled and unlabeled parsing, our ba- sic neural model with only lexical input performs comparable to the logistic ...
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Re Ranking Models for Spoken Language Understanding
... After an analysis of the m-best hypotheses of our SLU model, we noticed that many times the hypothesis ranked first by the SCLM is not the closest to the correct concept sequence, i.e. its er- ror rate using the ...
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Goal Oriented End to End Conversational Models with Profile Features in a Real World Setting
... response ranking models, the input to the model is a pair consisting of the conversation his- tory with customer profile features and a candidate ...
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Analysis of Multi Attribute Decision Making Problems by Using of Data Envelopment Analysis Technique
... MADM models) represented a model to identify dominant alternatives and rank ...Vickers models and performed sensitivity analysis with an applied ...DEA ranking models with some MADM ...
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Ranking all units with non-radial models in DEA
... evaluation models developed and managers need to distinguish efficient units increased, ranking models were ...for ranking, for instance the following models can be ...
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Deep Reinforcement Learning for Mention Ranking Coreference Models
... mention-ranking models for coreference evaluation metrics, obviating the need for hyperpa- rameters that must be carefully selected for each particular language, dataset, and evaluation ...
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Ranking Network-Structured Decision-Making Units and Its Application in Bank Branches
... Various models with constant return to scale have been developed for the network ...these models, efficiency is calculated based on the rele- vant units and ...DEA ranking models with a ...
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An Image reranking model based on attributes and visual features eliminating duplication
... The main motto of visual reranking is to refine the image results based on visual content rather than text based search. We propose the model that combines the visual content with the attributes which best describe the ...
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It's the economy stupid: comparison of proportional hazards models with economic and socio demographic variables for estimating the purchase of financial products
... both models, all economic variables have the expected signs so that as stock returns and the confidence index goes up the probability of purchasing goes ...both models the propensity for purchasing goes ...
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Ranking mahalanobis distance models for predictions of occupancy from presence-only data
... of models approached the top model in specificity and most were similar in structure to the top model, indicating that the comparison procedure had identified the most useful ...top models did represent a ...
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Discovery of Ranking Fraud for Mobile Apps
... submit ranking fraud. While the hugeness of thwarting ranking fraud has been comprehensively seen, there is obliged appreciation and research around ...of ranking fraud and propose a ranking ...
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Joint Learning Improves Semantic Role Labeling
... Here we describe a fast exact dynamic programming algorithm to find the most likely non-overlapping (consistent) labeling of all nodes in the parse tree, according to a product of probabilities from local models, ...
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Models for guiding and ranking well-to-well correlations of channel bodies in fluvial reservoirs
... Colombera, L, Mountney, NP, McCaffrey, WD et al. (1 more author) (2014) Models for guiding and ranking well-to-well correlations of channel bodies in fluvial reservoirs. American Association of Petroleum ...
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A Composite Weight based Multiple Attribute Decision Support System for the Selection of Automated Guided Vehicles
... their ranking scores. The user can see the ranking scores and techni- cal specifications in the same ...obtain ranking of AGVs by clicking on nine different sets of combinations of subjective and ...
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Different Ranking of NHPP Software Reliability Growth Models with Generalised Measure and Predictability
... From the need to rank SRGMs and an idea about generalised measure mentioned above, the authors apply an mathematics technique to calculate this measure based on real data sets. Base on this result, some SRGMs will be ...
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Assessing the quality of institutions’ rankings obtained through multilevel linear regression models
... In this section we illustrate the Monte Carlo simulation study we used in order to evaluate the goodness of schools’ rankings obtained with multilevel models. In particular, we aim at evaluating the consequences ...
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Mining Opinion Words and Opinion Targets – A Survey
... Then, a co-ranking process is used, which drastically reduces error propagation. The opinion targets and words and their relationships are modeled by an Opinion Relation Graph. A co-ranking algorithm based ...
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