The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Short text clustering is a challenging problem due to its sparseness of text representation. Here we propose a flexible Self-Taught Convolutional neural network framework for Short Text Clustering (dubbed STC2), which can flexibly and successfully incorporate more useful semantic features and learn non-biased deep text representation in an unsupervised manner. In our framework, the original raw text...
Feature selection is an important topic in pattern recognition research, which is supposed to find the most informative subset of features and remove the redundant features as well. By doing this, feature selection not only reduces the size of data, but also improves the performance of pattern recognition algorithms. However, previous feature selection methods focus on identifying the most important...
Text classification can help users to effectively handle and exploit useful information hidden in large-scale documents. However, the sparsity of data and the semantic sensitivity to context often hinder the classification performance of short texts. In order to overcome the weakness, we propose a unified framework to expand short texts based on word embedding clustering and convolutional neural network...
Emotion entrainment accounts for the rhythmic convergence of human emotions through social interactions. This phenomenon abounds in various disciplines, i.e. effervescency in soccer games, anger proliferation in violence incidents, or anxiety diffusion in disasters. Although emotion entrainment is highly relevant to the quality of human daily life, the principles underpinning this phenomenon is still...
The rapid proliferation of online social networks has greatly boosted the dissemination and evolution of online memes, which can be free text, trending catchphrase, or micro media. However, this information abundance is exceeding the capability of the public to consume it, especially in unusual situations such as emergency management, intelligence acquisition, and crime analysis. Thus, there calls...
Sentiment analysis has now become a popular research problem to tackle in NLP field. However, there are very few researches conducted on sentiment analysis for Chinese. Progress is held back due to lack of large and labelled corpus and powerful models. To remedy this deficiency, we build a Chinese Sentiment Treebank over social data. It concludes 13550 labeled sentences which are from movie reviews...
In this paper, we propose a general simulation platform integrated with a general failure model framework. Based on our simulation platform, we investigate the implications of system failures on virtualization platform. Meanwhile, we investigate the capability of virtualization platform's recovery mechanism, both reactive and proactive ones. In fact, we find that proactive recovery, in terms of both...
Service availability and QoS, in terms of customer affecting performance metrics, is crucial for service systems. However, the increasing complexity in distributed service systems introduce hidden space for software faults, which undermine system availability, leading to fault or even down time. In this paper, we introduce a composition technique, Coordinated Selective Rejuvenation, to automate the...
As a novel computing paradigm, e.g., cloud computing, become popular, researchers proposed various resource sharing techniques and resource provision techniques. However, very limited literatures pay attentions to the reliability of dynamically provided resources. In this paper, we propose a failure rules aware node resource provision policy for heterogeneous services consolidated in cloud computing...
Locating and diagnosing performance faults in distributed systems is crucial but challenging. Distributed systems are increasingly complex, full of various correlation and dependency, and exhibit dramatic dynamics. All these made traditional approaches prone to high false alarms. In this paper, we propose a novel system modeling technique, which encodes component's dynamic dependencies and behavior...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.