Titlebook: Data Science – Analytics and Applications; Proceedings of the 2 Peter Haber,Thomas Lampoltshammer,Manfred Mayr Conference proceedings 2019

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Combining Lexical and Semantic Similarity Methods for News Article Matchingthough, there are studies about finding duplicate or near-duplicate documents in several domains, none focus on grouping news texts based on their events or sources. A particular event can be narrated from very different perspectives with different words, concepts, and sentiment due to the different

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The Effectiveness of the Max Entropy Classifier for Feature Selection feature selection is often achieved by removing common stop words. In order to more drastically reduce the number of input features, actual feature selection methods such as Mutual Information or Chi-Squared are used on a count-based input representation. We suggest a task-oriented approach to sele

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脊椎动物

A Data-Driven Approach for Detecting Autism Spectrum Disorderscted and repetitive behaviors. Current ASD detection mechanisms are either subjective (survey-based) or focus only on responses to a single stimulus. In this work, we develop machine learning methods for predicting ASD based on electrocardiogram (ECG) and skin conductance (SC) data collected during

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A Spatial Data Analysis Approach for Public Policy Simulation in Thermal Energy Transition Scenariosaper discusses the underlying methodologies of calculating Heating Energy demand of buildings and the rationale for potential zones for thermal energy systems. In order to simulate the effects of public policies on communities the authors developed a spatial Agentbased Model, where the buildings are

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Facilitating Public Access to Legal Informationignificant ramifications for European society, whose various constituent actors require regular access to accurate and timely legal information, and often struggle with basic comprehension of legalese. The project focused on within this paper proposes to develop a suite of usercentric services that

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Neural Machine Translation from Natural Language into SQL with state-of-the-art Deep Learning methodbut training a computer to perform these tasks is a challenge. Recent advances in deep learning make it possible to interpret text effectively and achieve high performance results across natural language tasks. Interacting with relational databases trough natural language enables users of any backgr