Rapid expansion and the novel phenomenon of deep learning have manifested a variety proposals concerns in area video description, particularly recent past. Automatic event localization textual alternatives generation for complex diverse visual data supplied can be articulated as bridging two leading realms computer vision natural language processing. Several sequence-to-sequence algorithms are ...

To validate the credibility of diversity evaluation metrics, a number of methods that “evaluate evaluation metrics” are adopted in diversified search evaluation studies, such as Kendall’s τ , Discriminative Power, and the Intuitiveness Test. These methods have been widely adopted and have aided us in gaining much insight into the effectiveness of evaluation metrics. However, they also follow ce...

Evaluating Optical Music Recognition (OMR) is notoriously difficult and automated end-to-end OMR evaluation metrics are not available to guide development. In “Towards a Standard Testbed for Optical Music Recognition: Definitions, Metrics, and Page Images”, Byrd and Simonsen recently stress that a benchmarking standard is needed in the OMR community, both with regards to data and evaluation met...

This paper describes the UPC submissions to the WMT14 Metrics Shared Task: UPCIPA and UPC-STOUT. These metrics use a collection of evaluation measures integrated in ASIYA, a toolkit for machine translation evaluation. In addition to some standard metrics, the two submissions take advantage of novel metrics that consider linguistic structures, lexical relationships, and semantics to compare both...

Coupling is an internal software attribute that can be used to indicate the degree of system interdependence among the components of a software. Coupling is thought to be a desirable goal in software construction, leading to better values for maintainability, reusability and reliability. Although several coupling frameworks and coupling metrics have been proposed for aspect-oriented software, t...

Classifier evaluation has historically been conducted by estimating predictive accuracy via cross-validation tests or similar methods. More recently, ROC analysis has been shown to be a good alternative. However, the characteristics vary greatly between problem domains and it has been shown that some evaluation metrics are more appropriate than others in certain cases. We argue that different p...

Recommender Systems (RSs) can be found in many modern applications and that expose the user to a huge collections of items and helps user to decide on appropriate items, and ease the task of finding preferred items in the collection. Recently Recommender systems are gaining popularity in both commercial and research community, where many algorithms have been used for providing recommendations. ...

Experimental studies confirmed that only a small portion of software modules cause faults in software systems. Therefore, the majority of software modules are represented with non-faulty labels and the rest are marked with faulty labels during the modeling phase. These kinds of datasets are called imbalanced, and different performance metrics exist to evaluate the performance of proposed fault ...

This paper describes a feasibility study of n-gram-based evaluation metrics for automatic keyphrase extraction. To account for near-misses currently ignored by standard evaluation metrics, we adapt various evaluation metrics developed for machine translation and summarization, and also the R-precision evaluation metric from keyphrase evaluation. In evaluation, the R-precision metric is found to...