Towards The Multilingual Semantic Web

To date, the relation between multilingualism and the Semantic Web has not yet received enough attention in the research community. One major challenge for the Semantic Web community is to develop architectures, frameworks and systems that can help in overcoming national and language barriers, facilitating equal access to information produced in different cultures and languages. As such, this volume aims at documenting the state-of-the-art with regard to the vision of a Multilingual Semantic Web, in which semantic information will be accessible in and across multiple languages. The Multilingual Semantic Web as envisioned in this volume will support the following functionalities: (1) responding to information needs in any language with regard to semantically structured data available on the Semantic Web and Linked Open Data (LOD) cloud, (2) verbalizing and accessing semantically structured data, ontologies or other conceptualizations in multiple languages, (3) harmonizing, integrating, aggregating, comparing and repurposing semantically structured data across languages and (4) aligning and reconciling ontologies or other conceptualizations across languages. The volume is divided into three main sections: Principles, Methods and Applications. The section on “Principles” discusses models, architectures and methodologies that enrich the current Semantic Web architecture with features necessary to handle multiple languages. The section on “Methods” describes algorithms and approaches for solving key issues related to the construction of the Multilingual Semantic Web. The section on “Applications” describes the use of Multilingual Semantic Web based approaches in the context of several application domains. This volume is essential reading for all academic and industrial researchers who want to embark on this new research field at the intersection of various research topics, including the Semantic Web, Linked Data, natural language processing, computational linguistics, terminology and information retrieval. It will also be of great interest to practitioners who are interested in re-examining their existing infrastructure and methodologies for handling multiple languages in Web applications or information retrieval systems.

This book contains revised and significantly extended versions of selected papers from three workshops on Uncertainty Reasoning for the Semantic Web (URSW), held at the International Semantic Web Conferences (ISWC) in 2011, 2012, and 2013. The 16 papers presented were carefully reviewed and selected from numerous submissions. The papers included in this volume are organized in topical sections on probabilistic and Dempster-Shafer models, fuzzy and possibilistic models, inductive reasoning and machine learning, and hybrid approaches.

The two-volume set LNCS 10587 + 10588 constitutes the refereed proceedings of the 16th International Semantic Web Conference, ISWC 2017, held in Vienna, Austria, in October 2017. ISWC 2017 is the premier international forum, for the Semantic Web / Linked Data Community. The total of 55 full and 21 short papers presented in this volume were carefully reviewed and selected from 300 submissions. They are organized according to the tracks that were held: Research Track; Resource Track; and In-Use Track.

This book constitutes the refereed proceedings of the 10th Extended Semantic Web Conference, ESWC 2013, held in Montpellier, France, in May 2013. The 42 revised full papers presented together with three invited talks were carefully reviewed and selected from 162 submissions. They are organized in tracks on ontologies; linked open data; semantic data management; mobile Web, sensors and semantic streams; reasoning; natural language processing and information retrieval; machine learning; social Web and Web science; cognition and semantic Web; and in-use and industrial tracks. The book also includes 17 PhD papers presented at the PhD Symposium.

This book serves as a starting point for Semantic Web (SW) students and researchers interested in discovering what Natural Language Processing (NLP) has to offer. NLP can effectively help uncover the large portions of data held as unstructured text in natural language, thus augmenting the real content of the Semantic Web in a significant and lasting way. The book covers the basics of NLP, with a focus on Natural Language Understanding (NLU), referring to semantic processing, information extraction and knowledge acquisition, which are seen as the key links between the SW and NLP communities. Major emphasis is placed on mining sentences in search of entities and relations. In the course of this “quest", challenges will be encountered for various text analysis tasks, including part-of-speech tagging, parsing, semantic disambiguation, named entity recognition and relation extraction. Standard algorithms associated with these tasks are presented to provide an understanding of the fundamental concepts. Furthermore, the importance of experimental design and result analysis is emphasized, and accordingly, most chapters include small experiments on corpus data with quantitative and qualitative analysis of the results. This book is divided into four parts. Part I “Searching for Entities in Text” is dedicated to the search for entities in textual data. Next, Part II “Working with Corpora” investigates corpora as valuable resources for NLP work. In turn, Part III “Semantic Grounding and Relatedness” focuses on the process of linking surface forms found in text to entities in resources. Finally, Part IV “Knowledge Acquisition” delves into the world of relations and relation extraction. The book also includes three appendices: “A Look into the Semantic Web” gives a brief overview of the Semantic Web and is intended to bring readers less familiar with the Semantic Web up to speed, so that they too can fully benefit from the material of this book. “NLP Tools and Platforms” provides information about NLP platforms and tools, while “Relation Lists” gathers lists of relations under different categories, showing how relations can be varied and serve different purposes. And finally, the book includes a glossary of over 200 terms commonly used in NLP. The book offers a valuable resource for graduate students specializing in SW technologies and professionals looking for new tools to improve the applicability of SW techniques in everyday life – or, in short, everyone looking to learn about NLP in order to expand his or her horizons. It provides a wealth of information for readers new to both fields, helping them understand the underlying principles and the challenges they may encounter.

The two-volume set LNCS 8218 and 8219 constitutes the refereed proceedings of the 12th International Semantic Web Conference, ISWC 2013, held in Sydney, Australia, in October 2013. The International Semantic Web Conference is the premier forum for Semantic Web research, where cutting edge scientific results and technological innovations are presented, where problems and solutions are discussed, and where the future of this vision is being developed. It brings together specialists in fields such as artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, human-computer interaction, natural language processing, and the social sciences. Part 1 (LNCS 8218) contains a total of 45 papers which were presented in the research track. They were carefully reviewed and selected from 210 submissions. Part 2 (LNCS 8219) contains 16 papers from the in-use track which were accepted from 90 submissions. In addition, it presents 10 contributions to the evaluations and experiments track and 5 papers of the doctoral consortium.

This book introduces core natural language processing (NLP) technologies to non-experts in an easily accessible way, as a series of building blocks that lead the user to understand key technologies, why they are required, and how to integrate them into Semantic Web applications. Natural language processing and Semantic Web technologies have different, but complementary roles in data management. Combining these two technologies enables structured and unstructured data to merge seamlessly. Semantic Web technologies aim to convert unstructured data to meaningful representations, which benefit enormously from the use of NLP technologies, thereby enabling applications such as connecting text to Linked Open Data, connecting texts to each other, semantic searching, information visualization, and modeling of user behavior in online networks. The first half of this book describes the basic NLP processing tools: tokenization, part-of-speech tagging, and morphological analysis, in addition to the main tools required for an information extraction system (named entity recognition and relation extraction) which build on these components. The second half of the book explains how Semantic Web and NLP technologies can enhance each other, for example via semantic annotation, ontology linking, and population. These chapters also discuss sentiment analysis, a key component in making sense of textual data, and the difficulties of performing NLP on social media, as well as some proposed solutions. The book finishes by investigating some applications of these tools, focusing on semantic search and visualization, modeling user behavior, and an outlook on the future.

This book constitutes the thoroughly refereed proceedings of the Third Iberoamerican Conference, KGSWC 2021, held in Kingsville, Texas, USA, in November 2021.* The 22 full and 2 short papers presented were carefully reviewed and selected from 85 submissions. The papers cover topics related to software and its engineering, information systems, software creation and management, World Wide Web, web data description languages, and others. *Due to the Covid-19 pandemic the conference was held virtually.