This is the first monograph on the emerging area of linguistic linked data. Presenting a combination of background information on linguistic linked data and concrete implementation advice, it introduces and discusses the main benefits of applying linked data (LD) principles to the representation and publication of linguistic resources, arguing that LD does not look at a single resource in isolation but seeks to create a large network of resources that can be used together and uniformly, and so making more of the single resource. The book describes how the LD principles can be applied to modelling language resources. The first part provides the foundation for understanding the remainder of the book, introducing the data models, ontology and query languages used as the basis of the Semantic Web and LD and offering a more detailed overview of the Linguistic Linked Data Cloud. The second part of the book focuses on modelling language resources using LD principles, describing how to model lexical resources using Ontolex-lemon, the lexicon model for ontologies, and how to annotate and address elements of text represented in RDF. It also demonstrates how to model annotations, and how to capture the metadata of language resources. Further, it includes a chapter on representing linguistic categories. In the third part of the book, the authors describe how language resources can be transformed into LD and how links can be inferred and added to the data to increase connectivity and linking between different datasets. They also discuss using LD resources for natural language processing. The last part describes concrete applications of the technologies: representing and linking multilingual wordnets, applications in digital humanities and the discovery of language resources. Given its scope, the book is relevant for researchers and graduate students interested in topics at the crossroads of natural language processing / computational linguistics and the Semantic Web / linked data. It appeals to Semantic Web experts who are not proficient in applying the Semantic Web and LD principles to linguistic data, as well as to computational linguists who are used to working with lexical and linguistic resources wanting to learn about a new paradigm for modelling, publishing and exploiting linguistic resources.

In the last decade, ontologies have received much attention within computer science and related disciplines, most often as the semantic web. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications discusses ontologies for the semantic web, as well as knowledge management, information retrieval, text clustering and classification, as well as natural language processing.

Ontology Learning and Population from Text: Algorithms, Evaluation and Applications is structured for research scientists and practitioners in industry. This book is also suitable for graduate-level students in computer science.

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 is the first monograph on the emerging area of linguistic linked data. Presenting a combination of background information on linguistic linked data and concrete implementation advice, it introduces and discusses the main benefits of applying linked data (LD) principles to the representation and publication of linguistic resources, arguing that LD does not look at a single resource in isolation but seeks to create a large network of resources that can be used together and uniformly, and so making more of the single resource. The book describes how the LD principles can be applied to modelling language resources. The first part provides the foundation for understanding the remainder of the book, introducing the data models, ontology and query languages used as the basis of the Semantic Web and LD and offering a more detailed overview of the Linguistic Linked Data Cloud. The second part of the book focuses on modelling language resources using LD principles, describing how to model lexical resources using Ontolex-lemon, the lexicon model for ontologies, and how to annotate and address elements of text represented in RDF. It also demonstrates how to model annotations, and how to capture the metadata of language resources. Further, it includes a chapter on representing linguistic categories. In the third part of the book, the authors describe how language resources can be transformed into LD and how links can be inferred and added to the data to increase connectivity and linking between different datasets. They also discuss using LD resources for natural language processing. The last part describes concrete applications of the technologies: representing and linking multilingual wordnets, applications in digital humanities and the discovery of language resources. Given its scope, the book is relevant for researchers and graduate students interested in topics at the crossroads of natural language processing / computational linguistics and the Semantic Web / linked data. It appeals to Semantic Web experts who are not proficient in applying the Semantic Web and LD principles to linguistic data, as well as to computational linguists who are used to working with lexical and linguistic resources wanting to learn about a new paradigm for modelling, publishing and exploiting linguistic resources.

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.

For humans, understanding a natural language sentence or discourse is so effortless that we hardly ever think about it. For machines, however, the task of interpreting natural language, especially grasping meaning beyond the literal content, has proven extremely difficult and requires a large amount of background knowledge. This book focuses on the interpretation of natural language with respect to specific domain knowledge captured in ontologies. The main contribution is an approach that puts ontologies at the center of the interpretation process. This means that ontologies not only provide a formalization of domain knowledge necessary for interpretation but also support and guide the construction of meaning representations. We start with an introduction to ontologies and demonstrate how linguistic information can be attached to them by means of the ontology lexicon model lemon. These lexica then serve as basis for the automatic generation of grammars, which we use to compositionally construct meaning representations that conform with the vocabulary of an underlying ontology. As a result, the level of representational granularity is not driven by language but by the semantic distinctions made in the underlying ontology and thus by distinctions that are relevant in the context of a particular domain. We highlight some of the challenges involved in the construction of ontology-based meaning representations, and show how ontologies can be exploited for ambiguity resolution and the interpretation of temporal expressions. Finally, we present a question answering system that combines all tools and techniques introduced throughout the book in a real-world application, and sketch how the presented approach can scale to larger, multi-domain scenarios in the context of the Semantic Web. Table of Contents: List of Figures / Preface / Acknowledgments / Introduction / Ontologies / Linguistic Formalisms / Ontology Lexica / Grammar Generation / Putting Everything Together / Ontological Reasoning for Ambiguity Resolution / Temporal Interpretation / Ontology-Based Interpretation for Question Answering / Conclusion / Bibliography / Authors' Biographies

This book constitutes the thoroughly refereed post-proceedings of the satellite events of the10th International Conference on the Semantic Web, ESWC 2013, held in Montpellier, France, in May 2013. The volume contains 44 papers describing the posters and demonstrations, 10 best workshop papers selected from various submissions and four papers of the AI Mashup Challenge. The papers cover various aspects on the Semantic Web.

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 constitutes the refereed proceedings of the 9th Extended Semantic Web Conference, ESWC 2012, held in Heraklion, Crete, Greece, in May 2012. The 53 revised full papers presented were carefully reviewed and selected from 212 submissions. They are organized in tracks on linked open data, machine learning, natural language processing and information retrieval, ontologies, reasoning, semantic data management, services, processes, and cloud computing, social Web and Web science, in-use and industrial, digital libraries and cultural heritage, and e-government. The book also includes 13 PhD papers presented at the PhD Symposium.

In the last decade, ontologies have received much attention within computer science and related disciplines, most often as the semantic web. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications discusses ontologies for the semantic web, as well as knowledge management, information retrieval, text clustering and classification, as well as natural language processing.

Ontology Learning and Population from Text: Algorithms, Evaluation and Applications is structured for research scientists and practitioners in industry. This book is also suitable for graduate-level students in computer science.

This volume contains papers from the technical program of the 6th European Semantic Web Conference (ESWC 2009), held from May 31 to June 4, 2009, in Heraklion, Greece. ESWC 2009 presented the latest results in research and applications of Semantic Web technologies. In addition to the technical research track, ESWC 2009 featured a tutorial program, a PhD symposium, a system demo track, a poster track, a number of collocated workshops, and for the ?rst time in the series a Semantic Web in-use track exploring the bene?ts of applying Semantic Web technology in real-life applications and contexts. Thetechnical researchpaper trackreceivedover250submissions.The review process was organized using a two-tiered system, where each submission was reviewed by at least three members of the Program Committee. Vice Program CommitteeChairsorganizedadiscussionbetweenreviewers,collectedadditional reviews when necessary and provided a metareview for each submission. During a physical Program Committee meeting, the Vice Program Committee Chairs together with the Program Chairs selected 45 research papers to be presented at the conference.

This book constitutes the refereed proceedings of the 25th International Conference on Applications of Natural Language to Information Systems, NLDB 2020, held in Saarbrucken, Germany, in June 2020.* The 15 full papers and 10 short papers were carefully reviewed and selected from 68 submissions. The papers are organized in the following topical sections: semantic analysis; question answering and answer generation; classification; sentiment analysis; personality, affect and emotion; retrieval, conversational agents and multimodal analysis. *The conference was held virtually due to the COVID-19 pandemic.

This book constitutes the refereed proceedings of the 15th International Conference on Web Engineering, ICWE 2015, held in Rotterdam, The Netherlands, in June 2015. The 26 full research papers, 11 short papers, 7 industry papers, 11 demonstrations, 6 posters and 4 contributions to the PhD symposium presented were carefully reviewed and selected from 100 submissions. Moreover 2 tutorials are presented. The papers focus on eight tracks, namely Web application modeling and engineering; mobile Web applications; social Web applications; semantic Web applications; quality and accessibility aspects of Web applications; Web applications composition and mashups; Web user interfaces; security and privacy in Web applications.