Multi Modal Data Fusion Based On Embeddings
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Multi Modal Data Fusion Based On Embeddings
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Author : S. Thoma
language : en
Publisher: IOS Press
Release Date : 2019-11-06
Multi Modal Data Fusion Based On Embeddings written by S. Thoma and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-06 with Computers categories.
Many web pages include structured data in the form of semantic markup, which can be transferred to the Resource Description Framework (RDF) or provide an interface to retrieve RDF data directly. This RDF data enables machines to automatically process and use the data. When applications need data from more than one source the data has to be integrated, and the automation of this can be challenging. Usually, vocabularies are used to concisely describe the data, but because of the decentralized nature of the web, multiple data sources can provide similar information with different vocabularies, making integration more difficult. This book, Multi-modal Data Fusion based on Embeddings, describes how similar statements about entities can be identified across sources, independent of the vocabulary and data modeling choices. Previous approaches have relied on clean and extensively modeled ontologies for the alignment of statements, but the often noisy data in a web context does not necessarily adhere to these prerequisites. In this book, the use of RDF label information of entities is proposed to tackle this problem. In combination with embeddings, the use of label information allows for a better integration of noisy data, something that has been empirically confirmed by experiment. The book presents two main scientific contributions: the vocabulary and modeling agnostic fusion approach on the purely textual label information, and the combination of three different modalities into one multi-modal embedding space for a more human-like notion of similarity. The book will be of interest to all those faced with the problem of processing data from multiple web-based sources.
Multi Modal Data Fusion Based On Embeddings
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Author : Steffen Thoma
language : en
Publisher:
Release Date : 2018
Multi Modal Data Fusion Based On Embeddings written by Steffen Thoma and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Data Science And Emerging Technologies
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Author : Yap Bee Wah
language : en
Publisher: Springer Nature
Release Date :
Data Science And Emerging Technologies written by Yap Bee Wah and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Advanced Concepts For Intelligent Vision Systems
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Author : Jaques Blanc-Talon
language : en
Publisher: Springer Nature
Release Date : 2023-12-15
Advanced Concepts For Intelligent Vision Systems written by Jaques Blanc-Talon and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-15 with Computers categories.
This book constitutes the proceedings of the 21st International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2023, held in Kumamoto, Japan, during August 2023. The 31 papers presented in this volume were carefully reviewed and selected from a total of 48 submissions. They were organized in topical sections named: Computer Vision, Affective Computing and Human Interactions, Managing the Biodiversity, Robotics and Drones, Machine Learning.
Multimodal Scene Understanding
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Author : Michael Yang
language : en
Publisher: Academic Press
Release Date : 2019-07-16
Multimodal Scene Understanding written by Michael Yang and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-16 with Computers categories.
Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections – for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful. Contains state-of-the-art developments on multi-modal computing Shines a focus on algorithms and applications Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning
Health Information Science
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Author : Siuly Siuly
language : en
Publisher: Springer Nature
Release Date : 2021-11-09
Health Information Science written by Siuly Siuly and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-09 with Medical categories.
This book constitutes the proceedings of the 10th International Conference on Health Information Science, HIS 2021, which took place in Melbourne, Australia, in October 2021. The 16 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 56 submissions. They are organized in topical sections named: COVID-19, EEG data processing, Medical Data Analysis, Medical Record Mining (I), Medical Data Mining (II), Medical Data Processing.
Data Mining
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Author : Yue Xu
language : en
Publisher: Springer Nature
Release Date : 2021-12-08
Data Mining written by Yue Xu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-08 with Computers categories.
This book constitutes the refereed proceedings of the 19th Australasian Conference on Data Mining, AusDM 2021, held in Brisbane, Queensland, Australia, in December 2021.* The 16 revised full papers presented were carefully reviewed and selected from 32 submissions. The papers are organized in sections on research track and application track. *Due to the COVID-19 pandemic the conference was held online.
Strategies And Techniques For Federated Semantic Knowledge Integration And Retrieval
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Author : D. Collarana
language : en
Publisher: IOS Press
Release Date : 2020-01-24
Strategies And Techniques For Federated Semantic Knowledge Integration And Retrieval written by D. Collarana and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-24 with Computers categories.
The vast amount of data available on the web has led to the need for effective retrieval techniques to transform that data into usable machine knowledge. But the creation of integrated knowledge, especially knowledge about the same entity from different web data sources, is a challenging task requiring the solving of interoperability problems. This book addresses the problem of knowledge retrieval and integration from heterogeneous web sources, and proposes a holistic semantic knowledge retrieval and integration approach to creating knowledge graphs on-demand from diverse web sources. Semantic Web Technologies have evolved as a novel approach to tackle the problem of knowledge integration from heterogeneous data, but because of the Extraction-Transformation-Load approach that dominates the process, knowledge retrieval and integration from web data sources is either expensive, or full physical integration of the data is impeded by restricted access. Focusing on the representation of data from web sources as pieces of knowledge belonging to the same entity which can then be synthesized as a knowledge graph helps to solve interoperability conflicts and allow for a more cost-effective integration approach, providing a method that enables the creation of valuable insights from heterogeneous web data. Empirical evaluations to assess the effectiveness of this holistic approach provide evidence that the methodology and techniques proposed in this book help to effectively integrate the disparate knowledge spread over heterogeneous web data sources, and the book also demonstrates how three domain applications of law enforcement, job market analysis, and manufacturing, have been developed and managed using the approach.
Study On Data Placement Strategies In Distributed Rdf Stores
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Author : D.D. Janke
language : en
Publisher: IOS Press
Release Date : 2020-03-18
Study On Data Placement Strategies In Distributed Rdf Stores written by D.D. Janke and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-18 with Computers categories.
The distributed setting of RDF stores in the cloud poses many challenges, including how to optimize data placement on the compute nodes to improve query performance. In this book, a novel benchmarking methodology is developed for data placement strategies; one that overcomes these limitations by using a data-placement-strategy-independent distributed RDF store to analyze the effect of the data placement strategies on query performance. Frequently used data placement strategies have been evaluated, and this evaluation challenges the commonly held belief that data placement strategies which emphasize local computation lead to faster query executions. Indeed, results indicate that queries with a high workload can be executed faster on hash-based data placement strategies than on, for example, minimal edge-cut covers. The analysis of additional measurements indicates that vertical parallelization (i.e., a well-distributed workload) may be more important than horizontal containment (i.e., minimal data transport) for efficient query processing. Two such data placement strategies are proposed: the first, found in the literature, is entitled overpartitioned minimal edge-cut cover, and the second is the newly developed molecule hash cover. Evaluation revealed a balanced query workload and a high horizontal containment, which lead to a high vertical parallelization. As a result, these strategies demonstrated better query performance than other frequently used data placement strategies. The book also tests the hypothesis that collocating small connected triple sets on the same compute node while balancing the amount of triples stored on the different compute nodes leads to a high vertical parallelization.
Neural Information Processing
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Author : Biao Luo
language : en
Publisher: Springer Nature
Release Date : 2023-11-26
Neural Information Processing written by Biao Luo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-26 with Computers categories.
The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.