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Tensors for Data Mining and Data Fusion: Models, Applications, and Scalable Algorithms
Evangelos E. Papalexakis, Christos Faloutsos, Nicholas D. Sidiropoulos
Article No.: 16
Tensors and tensor decompositions are very powerful and versatile tools that can model a wide variety of heterogeneous, multiaspect data. As a result, tensor decompositions, which extract useful latent information out of multiaspect data tensors,...
Introduction to Intelligent Music Systems and Applications
Markus Schedl, Yi-Hsuan Yang, Perfecto Herrera-Boyer
Article No.: 17
Intelligent technologies have become an essential part of music systems and applications. This is evidenced by today's omnipresence of digital online music stores and streaming services, which rely on music recommenders, automatic playlist...
Most works in automatic music generation have addressed so far specific tasks. Such a reductionist approach has been extremely successful and some of these tasks have been solved once and for all. However, few works have addressed the issue...
Getting Closer to the Essence of Music: The Con Espressione Manifesto
Article No.: 19
This text offers a personal and very subjective view on the current situation of Music Information Research (MIR). Motivated by the desire to build systems with a somewhat deeper understanding of music than the ones we currently have, I try to...
Harnessing Music-Related Visual Stereotypes for Music Information Retrieval
Alexander Schindler, Andreas Rauber
Article No.: 20
Over decades, music labels have shaped easily identifiable genres to improve recognition value and subsequently market sales of new music acts. Referring to print magazines and later to music television as important distribution channels, the...
The Web has moved, slowly but steadily, from a collection of documents towards a collection of structured data. Knowledge graphs have then emerged as a way of representing the knowledge encoded in such data as well as a tool to reason on them in...
Tempo Driven Audio-to-Score Alignment Using Spectral Decomposition and Online Dynamic Time Warping
Francisco Jose Rodriguez-Serrano, Julio Jose Carabias-Orti, Pedro Vera-Candeas, Damian Martinez-Munoz
Article No.: 22
In this article, we present an online score following framework designed to deal with automatic accompaniment. The proposed framework is based on spectral factorization and online Dynamic Time Warping (DTW) and has two separated stages:...
Towards Music Structural Segmentation across Genres: Features, Structural Hypotheses, and Annotation Principles
Mi Tian, Mark B. Sandler
Article No.: 23
This article faces the problem of how different audio features and segmentation methods work with different music genres. A new annotated corpus of Chinese traditional Jingju music is presented. We incorporate this dataset with two existing music...
Learning Contextualized Music Semantics from Tags Via a Siamese Neural Network
Ubai Sandouk, Ke Chen
Article No.: 24
Music information retrieval faces a challenge in modeling contextualized musical concepts formulated by a set of co-occurring tags. In this article, we investigate the suitability of our recently proposed approach based on a Siamese neural network...
Intelligent Process Adaptation in the SmartPM System
Andrea Marrella, Massimo Mecella, Sebastian Sardina
Article No.: 25
The increasing application of process-oriented approaches in new challenging dynamic domains beyond business computing (e.g., healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of...
SMARTS: Scalable Microscopic Adaptive Road Traffic Simulator
Kotagiri Ramamohanarao, Hairuo Xie, Lars Kulik, Shanika Karunasekera, Egemen Tanin, Rui Zhang, Eman Bin Khunayn
Article No.: 26
Microscopic traffic simulators are important tools for studying transportation systems as they describe the evolution of traffic to the highest level of detail. A major challenge to microscopic simulators is the slow simulation speed due to the...
Differential Flattening: A Novel Framework for Community Detection in Multi-Layer Graphs
Jungeun Kim, Jae-Gil Lee, Sungsu Lim
Article No.: 27
A multi-layer graph consists of multiple layers of weighted graphs, where the multiple layers represent the different aspects of relationships. Considering multiple aspects (i.e., layers) together is essential to achieve a comprehensive and...
Joint Structured Sparsity Regularized Multiview Dimension Reduction for Video-Based Facial Expression Recognition
Liping Xie, Dacheng Tao, Haikun Wei
Article No.: 28
Video-based facial expression recognition (FER) has recently received increased attention as a result of its widespread application. Using only one type of feature to describe facial expression in video sequences is often inadequate, because the...
Prediction and Simulation of Human Mobility Following Natural Disasters
Xuan Song, Quanshi Zhang, Yoshihide Sekimoto, Ryosuke Shibasaki, Nicholas Jing Yuan, Xing Xie
Article No.: 29
In recent decades, the frequency and intensity of natural disasters has increased significantly, and this trend is expected to continue. Therefore, understanding and predicting human behavior and mobility during a disaster will play a vital role...
A Supervised Learning Model for High-Dimensional and Large-Scale Data
Chong Peng, Jie Cheng, Qiang Cheng
Article No.: 30
We introduce a new supervised learning model using a discriminative regression approach. This new model estimates a regression vector to represent the similarity between a test example and training examples while seamlessly integrating the class...
Implicit Visual Learning: Image Recognition via Dissipative Learning Model
Yan Liu, Yang Liu, Shenghua Zhong, Songtao Wu
Article No.: 31
According to consciousness involvement, human’s learning can be roughly classified into explicit learning and implicit learning. Contrasting strongly to explicit learning with clear targets and rules, such as our school study of mathematics,...
Efficient Methods for Influence-Based Network-Oblivious Community Detection
Nicola Barbieri, Francesco Bonchi, Giuseppe Manco
Article No.: 32
We study the problem of detecting social communities when the social graph is not available but instead we have access to a log of user activity, that is, a dataset of tuples (u, i, t) recording the fact that user u...