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Audio data contains several sounds and is an important source for multimedia applications. One of them is unstructured Environmental Sounds (also referred to as audio events) that have noise-like characteristics with flat spectrums. Therefore, in general, recognition methods applied for music and speech data are not appropriate for the Environmental Sounds. In this paper, we propose an MFCC-SVM based...
A challenge in the research of Social Networks is the large scale analysis of graphs. One of the most valuable metrics in the evaluation of graphs is betweenness-centrality. In this paper, we define an approximation of betweenness-centrality for the purpose of building a predictive model of Social Networks. The methodology presented describes a bounded distance approximation of betweenness-centrality...
In today's cloud service market, different providers have very different low-level mechanisms to accommodate various types of policies from their users. Enforcement of policies over multiple cloud provider domains is an intrinsically complex problem for both sides. In reality, cloud providers have to either manually update enforcement mechanisms or negotiate adjusted policies with their users for...
The Linked Data (LD) Cloud consists of LD sources covering a wide variety of topics. These data sources use formal vocabularies to represent their data and in many cases, they use heterogeneous vocabularies to represent data about the same topics. This data heterogeneity must be overcome to effectively integrate and consume data from the LD Cloud. Mappings overcome this data heterogeneity by transforming...
T.R.A.F.F.I.C is an acronym representing Transit Response Analysis for Facilitating Informed Commuters. T.R.A.F.F.I.C. is a web service hosted in the cloud which uses real-time Big Data from TRANSCOM, a non-profit firm. We are mining for potential congested traffic patterns which may impair one's timely commute during rush hour. T.R.A.F.F.I.C is based on the service-oriented architecture (SOA) web...
The development of modern health care and clinical practice increase the need of nutritional and medical data extraction and integration across heterogeneous data sources. It can be useful for researchers and patients if there is a way to extract relevant information and organize it as easily shared and machine-processable linked data. In this paper, we describe an automatic approach that extracts...
Bioenergy is a renewable energy generated from biomass, while biofuel is a hydrocarbon fuel that is produced from biomass. Recently, bioenergy and biofuel projects are encouraged and supported by many governments and organizations in various ways such as providing incentives, technical supports, information, and decision support tools. Economic model is one of the decision support tools, which helps...
Automatic question generation from text has been used and adapted to online and self-directed learning platforms. We incorporate methods into the automatic question generation process that are designed to improve question quality by aligning them to the specified pedagogical goals and to a learner's model. This is achieved by extracting, ranking and filtering relevant sentences in the given learning...
Word prediction generally relies on n-grams occurrence statistics, which may have huge data storage requirements and does not take into account the general meaning of the text. We propose an alternative methodology, based on Latent Semantic Analysis, to address these issues. An asymmetric Word-Word frequency matrix is employed to achieve higher scalability with large training datasets than the classic...
Information privacy and security plays a major role in domains where sensitive information is handled, such as case studies of rare diseases. Currently, security for accessing any sensitive information is provided by various mechanisms at the user/system level by employing access control models such as Role Based Access Control. However, these approaches leave security at the knowledge level unattended,...
Mining opinions and analyzing sentiments from social network data help in various fields such as even prediction, analyzing overall mood of public on a particular social issue and so on. This paper involves analyzing the mood of the society on a particular news from Twitter posts. The key idea of the paper is to increase the accuracy of classification by including Natural Language Processing Techniques...
We present the design and application of a generic approach for semantic extraction of professional interests from social media using a hierarchical knowledge-base and spreading activation theory. By this, we can assess to which extend a user's social media life reflects his or her professional life. Detecting named entities related to professional interests is conducted by a taxonomy of terms in...
The increasing popularity of smartphones has significantly changed the way we live. Today's powerful mobile systems provide us with all kinds of convenient services. Thanks to the wide variety of available apps, it has never been so easy for people to shop, to navigate, and to communicate with others. However, for some tasks we can further improve the user experience by employing newly developed algorithms...
The research on ‘Pedagogical potentials of IEEE 802.11 WLAN to Nigerian based University’ is an in depth study to evaluate the potentials of its implementation to the entire teaching and tutoring vertical in Nigerian universities. While conducting this research study, the campus did not have the facility of Wireless internet service. Researchers are to provide the WLAN-Wireless local area network...
Home insurance is a critical issue in the state of Florida, considering that residential properties are exposed to hurricane risk each year. To assess hurricane risk and project insured losses, the Florida Public Hurricane Loss Model (FPHLM) funded by the states insurance regulatory agency was developed. The FPHLM is an open and public model that offers an integrated complex computing framework that...
There are so many web data hidden behind so-called deep web and can only be accessed through query interfaces, and the data volume is increasing. We often need to fill forms over alternative interfaces in the same domain to select the best product or service, such as buying a book across various online book websites to choose the most affordable one. Integrating these web interfaces in the same domain...
Semantic parsing is still a challenging problem for open domain question answering. In semantic parsing, questions are mapped with their meaning representations. These representations are matched with feasible answers in knowledge bases. In Knowledge bases (e.g. Freebase), knowledge is stored in the form of Topics. For a successful answer extraction from Freebase, it is required to correctly identify...
This work proposes a system for the analysis and the comparison of users profiles in social networks. Posts are extracted and analyzed in order to detect similar contents, like topics, sentiments and writing styles. A case study regarding the analysis of the authenticity of profiles of the Italian prime minister in different social networks is illustrated.
In this paper, we address the problem of processing semantic data streams. The semantic annotation of sensor data is one of the solutions to the heterogeneous nature of sensor data streams. Existing systems for publishing semantic streaming data collect stream data and transmit the semantic streaming data to query engines regardless of the queries registered in the query engines. As a large number...
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