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Cloud SLAs are contractually binding agreements between cloud service providers and cloud consumers. For cloud service providers, it is essential to prevent SLA violations as much as possible to enhance customer satisfaction and avoid penalty payments. Therefore, it is desirable for providers to predict possible violations before they happen. We propose an approach for predicting SLA violations, which...
In this paper, we propose a novel pipeline for automated scribal attribution based on the Quill feature: 1) We compensate the Quill feature histogram for pen changes and page warping. 2) We add curvature as a third dimension in the feature histogram, to better separate characteristics like loops and lines. 3) We also investigate the use of several dissimilarity measures between the feature histograms...
Author name disambiguation has been one of the hardest problems faced by digital libraries since their early days. Historically, supervised solutions have empirically outperformed those based on heuristics, but with the burden of having to rely on manually labelled training sets for the learning process. Moreover, most supervised solutions just apply some type of generic machine learning solution...
In this paper we proposed a static analysis framework to classify the android malware. The three different feature likely (a) opcode (b) method and (c) permissions are extracted from the each android .apk file. The dominant attributes are aggregated by modifying two different ranked feature methods such as ANOVA to Extended ANOVA (X-ANOVA) and Wann-Whiteney U-test to Extended U-Test (X-U-Test). These...
An important factor of a corpus is its domain, usually the quality of a SMT system trained on an in-domain corpus increases by adding out-of-domain sentences to its training corpus. In this paper we have shown out-of-domain corpora may also contains sentences which are proper for improving the quality of in-domain corpus. These sentences have words and phrases that occur in indomain corpora so, their...
Many of the phrase pairs extracted in the phrase-based machine translation systems have low quality and are not relevant. So their existence in the phrase table not only enlarges it, but also could reduce the translation quality. There are many methods presented to prune these noisy phrase pairs, using the statistics derived from the phrase table. In this paper we proposed a new pruning method that...
Satire exposes humanity's vices and foibles through the use of irony, wit, and sometimes sarcasm too. It is also frequently used in online communities. Recognition of satire can help in many NLP applications like dialogue system and review summarization. In this paper we filter online news articles as satirical or true news documents using SVM (Support Vector Machine) classification method combined...
Emotional Polarity Classification is an important task in Sentiment Analysis area. It is applied in many real problems such as reviews of consumer products and services, financial markets, and forensic analysis. The scientists from the areas of text mining and nature language processing have studied how to solve emotional polarity classification problem. They used a variety of methods, from simple...
Personality research on social media is a hot topic recently due to the rapid development of social media as well as the central importance of personality study in psychology, but most studies are conducted on inadequate label samples. Our research aims to explore the usage of unlabeled samples to improve the prediction accuracy. By conducting n user study with 1792 users, we adopt local linear semi-supervised...
Given multiple classifiers, one prevalent approach in classifier ensemble is to diversely combine classifier components (diversity-based ensemble), and a lot of previous works show that this approach can improve accuracy in classification. However, how to measure diversity and perform diversity-based learning are still challenges in the literature. Moreover, the learning procedure highly depends upon...
This paper presents a multi-joint lower limbs rehabilitation robot with three degrees of freedom. The robot includes seat, left mechanical leg, right mechanical leg and electric control box, and each mechanical leg includes the hip joint, knee joint and ankle joint which correspond to the hip joint, knee joint and ankle joint of human. The mechanical structure of the rehabilitation robot is described...
Text mining is a discovery of interesting knowledge in text documents. Exact and accurate knowledge in the text documents needed for the user to find what they require. Many data mining methods are used to mine useful patterns from text documents. However, using and updating these discovered patterns is still an open research issue. Many term based methods are suggested, but a disadvantage with these...
In the Prognostics and Health Management domain, estimating the remaining useful life (RUL) of critical machinery is a challenging task. Various research topics as data acquisition and processing, fusion, diagnostics, prognostivs and decision are involved in this domain. This paper presents an approach for estimating the Remaining Useful Life (RUL) of equipments based on shapelet extraction and characterization...
The timely detection of abnormal energy usage is one of the major ad-hoc techniques to optimize energy efficiency. Typically an alarm is triggered either by a significant drift from the baseline consumption level or by a period of large variations. In this paper we propose a statistical predictive method for detecting anomalies both in mean and in variation. The criterion behind is based on the prediction...
Finding out an effective way to score Chinese written essays automatically remains challenging for researchers. Several methods have been proposed and developed but limited in the character and word usage levels. As one of the scoring standards, however, content or topic perspective is also an important and necessary indicator to assess an essay. Therefore, in this paper, we propose a novel perspective...
In this paper, we show how to improve the Radial Basis Function Neural Networks effectiveness by using the Optimum-Path Forest clustering algorithm, since it computes the number of clusters on-the-fly, which can be very interesting for finding the Gaussians that cover the feature space. Some commonly used approaches for this task, such as the well-known fc-means, require the number of classes/clusters...
In this paper, we propose a Multilayer Markovian model for change detection in registered aerial image pairs with large time differences. A Three Layer Markov Random Field takes into account information from two different sets of features namely the Modified HOG (Histogram of Oriented Gradients) difference and the Gray-Level (GL) Difference. The third layer is the resultant combination of the two...
Along with the information explosion in the Internet era, the traditional classification methods, such as KNN (k-nearest neighbor), Naive Bayes (NB), encounter bottlenecks due to the endless stream of new words. In this paper, through comparing with the Rocchio and Bayesian algorithms, it has been found that centroid-based algorithms are insufficient for text classification. Therefore, a novel feature...
In many classification problems, there exists additional information which is available during training but not available during testing. In this paper we denote such information as hidden information, and study how to incorporate it to improve the learning performance. Despite its importance, learning with hidden information has not attracted enough attention from the field and existing work in this...
In this paper we present a novel approach to integrate feature similarity and spatial consistency of local features to achieve the goal of localizing an object of interest in an image. The goal is to achieve coherent and accurate labeling of feature points in a simple and effective way. We introduced our Spatial-Visual Label Propagation algorithm to infer the labels of local features in a test image...
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