Proceedings of the 24th International Conference on World Wide Web PDF Download

Author: Aldo Gangemi
Publisher:
ISBN: 9781450334730
Category : Computer science
Languages : en
Pages : 1562

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Author: S. Sadagopan
Publisher:
ISBN:
Category :
Languages : en
Pages : 524

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Author: Paul Jones
Publisher:
ISBN: 9781605587998
Category : Internet
Languages : en
Pages : 1365

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Book Description
WWW '10: The 19th International World Wide Web Conference Apr 26, 2010-Apr 30, 2010 Raleigh, USA. You can view more information about this proceeding and all of ACMs other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.

Author: K. Selçuk Candan
Publisher: Springer Nature
ISBN: 3030852512
Category : Computers
Languages : en
Pages : 487

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Book Description
This book constitutes the refereed proceedings of the 12th International Conference of the CLEF Association, CLEF 2021, held virtually in September 2021. The conference has a clear focus on experimental information retrieval with special attention to the challenges of multimodality, multilinguality, and interactive search ranging from unstructured to semi structures and structured data. The 11 full papers presented in this volume were carefully reviewed and selected from 21 submissions. This year, the contributions addressed the following challenges: application of neural methods for entity recognition as well as misinformation detection in the health area, skills extraction in job-match databases, stock market prediction using financial news, and extraction of audio features for podcast retrieval. In addition to this, the volume presents 5 “best of the labs” papers which were reviewed as full paper submissions with the same review criteria. 12 lab overview papers were accepted and represent scientific challenges based on new data sets and real world problems in multimodal and multilingual information access.

Author: G. De Giacomo
Publisher: IOS Press
ISBN: 164368101X
Category : Computers
Languages : en
Pages : 3122

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Book Description
This book presents the proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), held in Santiago de Compostela, Spain, from 29 August to 8 September 2020. The conference was postponed from June, and much of it conducted online due to the COVID-19 restrictions. The conference is one of the principal occasions for researchers and practitioners of AI to meet and discuss the latest trends and challenges in all fields of AI and to demonstrate innovative applications and uses of advanced AI technology. The book also includes the proceedings of the 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020) held at the same time. A record number of more than 1,700 submissions was received for ECAI 2020, of which 1,443 were reviewed. Of these, 361 full-papers and 36 highlight papers were accepted (an acceptance rate of 25% for full-papers and 45% for highlight papers). The book is divided into three sections: ECAI full papers; ECAI highlight papers; and PAIS papers. The topics of these papers cover all aspects of AI, including Agent-based and Multi-agent Systems; Computational Intelligence; Constraints and Satisfiability; Games and Virtual Environments; Heuristic Search; Human Aspects in AI; Information Retrieval and Filtering; Knowledge Representation and Reasoning; Machine Learning; Multidisciplinary Topics and Applications; Natural Language Processing; Planning and Scheduling; Robotics; Safe, Explainable, and Trustworthy AI; Semantic Technologies; Uncertainty in AI; and Vision. The book will be of interest to all those whose work involves the use of AI technology.

Author: Svetlana S. Bodrunova
Publisher: Springer
ISBN: 9783030014360
Category : Computers
Languages : en
Pages : 313

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Book Description
This book constitutes the proceedings of the 5th International Conference on Internet Science held in St. Petersburg, Russia, in October 2018. The 23 papers presented were carefully reviewed and selected for inclusion in this volume. They were organized in topical sections named: risks on the Internet: detecting harmful content and discussing regulation; methodologies for studies of online audiences; and online media and public issues.

Author: Shaoxu Song
Publisher: Springer
ISBN: 3319697811
Category : Computers
Languages : en
Pages : 274

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Book Description
This book constitutes the thoroughly refereed post-conference proceedings of the First APWeb-WAIM 2017 Workshops, held jointly with the First International Joint Conference APWeb-WAIM 2017, held in Beijing, China, in July 2017. The 25 full papers presented were carefully reviewed and selected from 40 submissions. The papers originating from six workshops present cutting-edge ideas, results, experiences, techniques, and tools from all aspects of web data management with the focus on mobile web data analytics; big spatial data and urban computing; graph data management and analytics; mobility analytics from spatial and social data.

Author: Pavel Braslavski
Publisher: Springer
ISBN: 3319417185
Category : Computers
Languages : en
Pages : 202

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Book Description
This book constitutes the thoroughly refereed proceedings of the 9th Russian Summer School on Information Retrieval, RuSSIR 2015, held in Saint Petersburg, Russia, in August 2015. The volume includes 5 tutorial papers, summarizing lectures given at the event, and 6 revised papers from the school participants. The papers focus on various aspects of information retrieval.

Author: Chuan Shi
Publisher: Springer Nature
ISBN: 9811661669
Category : Computers
Languages : en
Pages : 329

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Book Description
Representation learning in heterogeneous graphs (HG) is intended to provide a meaningful vector representation for each node so as to facilitate downstream applications such as link prediction, personalized recommendation, node classification, etc. This task, however, is challenging not only because of the need to incorporate heterogeneous structural (graph) information consisting of multiple types of node and edge, but also the need to consider heterogeneous attributes or types of content (e.g. text or image) associated with each node. Although considerable advances have been made in homogeneous (and heterogeneous) graph embedding, attributed graph embedding and graph neural networks, few are capable of simultaneously and effectively taking into account heterogeneous structural (graph) information as well as the heterogeneous content information of each node. In this book, we provide a comprehensive survey of current developments in HG representation learning. More importantly, we present the state-of-the-art in this field, including theoretical models and real applications that have been showcased at the top conferences and journals, such as TKDE, KDD, WWW, IJCAI and AAAI. The book has two major objectives: (1) to provide researchers with an understanding of the fundamental issues and a good point of departure for working in this rapidly expanding field, and (2) to present the latest research on applying heterogeneous graphs to model real systems and learning structural features of interaction systems. To the best of our knowledge, it is the first book to summarize the latest developments and present cutting-edge research on heterogeneous graph representation learning. To gain the most from it, readers should have a basic grasp of computer science, data mining and machine learning.

Author: Stan Matwin
Publisher: Springer Nature
ISBN: 3031336178
Category : Mathematics
Languages : en
Pages : 92

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Book Description
This book provides a broad overview of the state of the art of the research in generative methods for the analysis of social media data. It especially includes two important aspects that currently gain importance in mining and modelling social media: dynamics and networks. The book is divided into five chapters and provides an extensive bibliography consisting of more than 250 papers. After a quick introduction and survey of the book in the first chapter, chapter 2 is devoted to the discussion of data models and ontologies for social network analysis. Next, chapter 3 deals with text generation and generative text models and the dangers they pose to social media and society at large. Chapter 4 then focuses on topic modelling and sentiment analysis in the context of social networks. Finally, Chapter 5 presents graph theory tools and approaches to mine and model social networks. Throughout the book, open problems, highlighting potential future directions, are clearly identified. The book aims at researchers and graduate students in social media analysis, information retrieval, and machine learning applications.