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Full-Text Articles in Engineering
Novel Natural Language Processing Models For Medical Terms And Symptoms Detection In Twitter, Farahnaz Golrooy Motlagh
Novel Natural Language Processing Models For Medical Terms And Symptoms Detection In Twitter, Farahnaz Golrooy Motlagh
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This dissertation focuses on disambiguation of language use on Twitter about drug use, consumption types of drugs, drug legalization, ontology-enhanced approaches, and prediction analysis of data-driven by developing novel NLP models. Three technical aims comprise this work: (a) leveraging pattern recognition techniques to improve the quality and quantity of crawled Twitter posts related to drug abuse; (b) using an expert-curated, domain-specific DsOn ontology model that improve knowledge extraction in the form of drug-to-symptom and drug-to-side effect relations; and (c) modeling the prediction of public perception of the drug’s legalization and the sentiment analysis of drug consumption on Twitter. We collected …
Deep Neural Ranking For Crowdsourced Geopolitical Event Forecasting, Giuseppe Nebbione, Derek Doran, Srikanth Nadella, Brandon Minnery
Deep Neural Ranking For Crowdsourced Geopolitical Event Forecasting, Giuseppe Nebbione, Derek Doran, Srikanth Nadella, Brandon Minnery
Computer Science and Engineering Faculty Publications
There are many examples of “wisdom of the crowd” effects in which the large number of participants imparts confidence in the collective judgment of the crowd. But how do we form an aggregated judgment when the size of the crowd is limited? Whose judgments do we include, and whose do we accord the most weight? This paper considers this problem in the context of geopolitical event forecasting, where volunteer analysts are queried to give their expertise, confidence, and predictions about the outcome of an event. We develop a forecast aggregation model that integrates topical information about a question, meta-data about …
Knowledge Graph Reasoning Over Unseen Rdf Data, Bhargavacharan Reddy Kaithi
Knowledge Graph Reasoning Over Unseen Rdf Data, Bhargavacharan Reddy Kaithi
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In recent years, the research in deep learning and knowledge engineering has made a wide impact on the data and knowledge representations. The research in knowledge engineering has frequently focused on modeling the high level human cognitive abilities, such as reasoning, making inferences, and validation. Semantic Web Technologies and Deep Learning have an interest in creating intelligent artifacts. Deep learning is a set of machine learning algorithms that attempt to model data representations through many layers of non-linear transformations. Deep learning is in- creasingly employed to analyze various knowledge representations mentioned in Semantic Web and provides better results for Semantic …
Deep Learning Approach For Intrusion Detection System (Ids) In The Internet Of Things (Iot) Network Using Gated Recurrent Neural Networks (Gru), Manoj Kumar Putchala
Deep Learning Approach For Intrusion Detection System (Ids) In The Internet Of Things (Iot) Network Using Gated Recurrent Neural Networks (Gru), Manoj Kumar Putchala
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The Internet of Things (IoT) is a complex paradigm where billions of devices are connected to a network. These connected devices form an intelligent system of systems that share the data without human-to-computer or human-to-human interaction. These systems extract meaningful data that can transform human lives, businesses, and the world in significant ways. However, the reality of IoT is prone to countless cyber-attacks in the extremely hostile environment like the internet. The recent hack of 2014 Jeep Cherokee, iStan pacemaker, and a German steel plant are a few notable security breaches. To secure an IoT system, the traditional high-end security …