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Query Processing Over Graph Structured Data On The Web
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Book Synopsis Query Processing over Graph-structured Data on the Web by : M. Acosta Deibe
Download or read book Query Processing over Graph-structured Data on the Web written by M. Acosta Deibe and published by IOS Press. This book was released on 2018-10-12 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last years, Linked Data initiatives have encouraged the publication of large graph-structured datasets using the Resource Description Framework (RDF). Due to the constant growth of RDF data on the web, more flexible data management infrastructures must be able to efficiently and effectively exploit the vast amount of knowledge accessible on the web. This book presents flexible query processing strategies over RDF graphs on the web using the SPARQL query language. In this work, we show how query engines can change plans on-the-fly with adaptive techniques to cope with unpredictable conditions and to reduce execution time. Furthermore, this work investigates the application of crowdsourcing in query processing, where engines are able to contact humans to enhance the quality of query answers. The theoretical and empirical results presented in this book indicate that flexible techniques allow for querying RDF data sources efficiently and effectively.
Book Synopsis Query Processing Over Graph-structured Data on the Web by : Maribel Acosta Deibe
Download or read book Query Processing Over Graph-structured Data on the Web written by Maribel Acosta Deibe and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Efficient Optimization and Processing of Queries Over Text-rich Graph-structured Data by : Günter Ladwig
Download or read book Efficient Optimization and Processing of Queries Over Text-rich Graph-structured Data written by Günter Ladwig and published by KIT Scientific Publishing. This book was released on 2014-05-13 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many databases today capture both, structured and unstructured data. Making use of such hybrid data has become an important topic in research and industry. The efficient evaluation of hybrid data queries is the main topic of this thesis. Novel techniques are proposed that improve the whole processing pipeline, from indexes and query optimization to run-time processing. The contributions are evaluated in extensive experiments showing that the proposed techniques improve upon the state of the art.
Download or read book The Semantic Web written by Karl Aberer and published by Springer Science & Business Media. This book was released on 2007-10-22 with total page 998 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the joint 6th International Semantic Web Conference, ISWC 2007, and the 2nd Asian Semantic Web Conference, ASWC 2007, held in Busan, Korea, in November 2007. The 50 revised full academic papers and 12 revised application papers presented together with 5 Semantic Web Challenge papers and 12 selected doctoral consortium articles were carefully reviewed and selected from a total of 257 submitted papers to the academic track and 29 to the applications track. The papers address all current issues in the field of the semantic Web, ranging from theoretical and foundational aspects to various applied topics such as management of semantic Web data, ontologies, semantic Web architecture, social semantic Web, as well as applications of the semantic Web. Short descriptions of the top five winning applications submitted to the Semantic Web Challenge competition conclude the volume.
Book Synopsis Decentralized Query Processing Over Heterogeneous Sources of Knowledge Graphs by : L. Heling
Download or read book Decentralized Query Processing Over Heterogeneous Sources of Knowledge Graphs written by L. Heling and published by IOS Press. This book was released on 2022-03-08 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge graphs are increasingly used in scientific and industrial applications. The large number and size of knowledge graphs published as Linked Data in autonomous sources has led to the development of various interfaces to query these knowledge graphs. Therefore, effective query processing approaches that enable efficient information retrieval from these knowledge graphs need to address the capabilities and limitations of different Linked Data Fragment interfaces. This book investigates novel approaches to addressing the challenges that arise in the presence of decentralized, heterogeneous sources of knowledge graphs. The effectiveness of these approaches is empirically evaluated and demonstrated using various real world and synthetic large-scale knowledge graphs throughout. First, a sample-based approach for generating fine-grained performance profiles is proposed, and it is demonstrated how the information from such profiles can be leveraged in cost model-based query planning. In addition, a sample-based data distribution profiling approach is advocated which aims to estimate the statistical profile features of large knowledge graphs and the applicability of these estimations in federated querying processing is demonstrated. The remainder of the book focuses on techniques to devise efficient query processing approaches when heterogeneous interfaces need to be queried but no fine-grained statistics are available. Robust techniques to support efficient query processing in these circumstances are investigated and results are shared to demonstrate the way in which these techniques can outperform state-of-the-art approaches. Finally, the author describes a framework for federated query processing over heterogeneous federations of Linked Data Fragments to exploit the capabilities of different sources by defining interface-aware approaches.
Book Synopsis Exploiting Semantic Web Knowledge Graphs in Data Mining by : P. Ristoski
Download or read book Exploiting Semantic Web Knowledge Graphs in Data Mining written by P. Ristoski and published by IOS Press. This book was released on 2019-06-28 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in this field are knowledge intensive and can benefit from additional knowledge from various sources, so many approaches have been proposed that combine Semantic Web data with the data mining and knowledge discovery process. This book, Exploiting Semantic Web Knowledge Graphs in Data Mining, aims to show that Semantic Web knowledge graphs are useful for generating valuable data mining features that can be used in various data mining tasks. In Part I, Mining Semantic Web Knowledge Graphs, the author evaluates unsupervised feature generation strategies from types and relations in knowledge graphs used in different data mining tasks such as classification, regression, and outlier detection. Part II, Semantic Web Knowledge Graphs Embeddings, proposes an approach that circumvents the shortcomings introduced with the approaches in Part I, developing an approach that is able to embed complete Semantic Web knowledge graphs in a low dimensional feature space where each entity and relation in the knowledge graph is represented as a numerical vector. Finally, Part III, Applications of Semantic Web Knowledge Graphs, describes a list of applications that exploit Semantic Web knowledge graphs like classification and regression, showing that the approaches developed in Part I and Part II can be used in applications in various domains. The book will be of interest to all those working in the field of data mining and KDD.
Book Synopsis Managing and Mining Graph Data by : Charu C. Aggarwal
Download or read book Managing and Mining Graph Data written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2010-02-02 with total page 623 pages. Available in PDF, EPUB and Kindle. Book excerpt: Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studies a number of domain-specific scenarios such as stream mining, web graphs, social networks, chemical and biological data. The chapters are written by well known researchers in the field, and provide a broad perspective of the area. This is the first comprehensive survey book in the emerging topic of graph data processing. Managing and Mining Graph Data is designed for a varied audience composed of professors, researchers and practitioners in industry. This volume is also suitable as a reference book for advanced-level database students in computer science and engineering.
Download or read book The Semantic Web written by Karl Aberer and published by Springer Science & Business Media. This book was released on 2007-10-27 with total page 999 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the joined 6th International Semantic Web Conference, ISWC 2007, and the 2nd Asian Semantic Web Conference, ASWC 2007. The papers address all current issues in the field of the semantic Web, ranging from theoretical and foundational aspects to various applied topics such as management of semantic Web data, ontologies, semantic Web architecture, social semantic Web, as well as applications of the semantic Web.
Book Synopsis Advanced Standard SQL Dynamic Structured Data Modeling and Hierarchical Processing by : Michael M. David
Download or read book Advanced Standard SQL Dynamic Structured Data Modeling and Hierarchical Processing written by Michael M. David and published by Artech House. This book was released on 2013 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This revised and updated edition of Advanced ANSI SQL data modeling and structure processing ..."--Pref.
Book Synopsis Geographic Knowledge Graph Summarization by : B. Yan
Download or read book Geographic Knowledge Graph Summarization written by B. Yan and published by IOS Press. This book was released on 2019-08-08 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geographic knowledge graphs can have an important role in delivering interoperability, accessibility and the demands of conceptualization in geographic information science (GIS). However, the massive amount of accompanying information and the enormous diversity of geographic knowledge graphs limits their applicability and hinders the widespread adoption of this useful structured knowledge. This book, Geographic Knowledge Graph Summarization, focuses on the ways in which geographic knowledge graphs can be digested and summarized. Such a summarization would relieve the burden of information overload for end users and reduce data storage, as well as speeding up queries and eliminating ‘noise’. The book introduces the general concept of geospatial inductive bias and explains the different ways in which this idea can be used in the summarization of geographic knowledge graphs. The book breaks up the task of summarization into separate but related components, and after an introduction and a brief overview of concepts and theories, Chapters 3, 4 and 5 explore hierarchical place type structure, multimedia leaf nodes, and general relation and entity components respectively. Chapter 6 presents a spatial knowledge map interface which illustrates the effectiveness of summarization. The book integrates top-down knowledge engineering and bottom-up knowledge learning methods, and will do much to promote awareness of this fascinating area and related issues.
Book Synopsis Managing and Consuming Completeness Information for RDF Data Sources by : F. Darari
Download or read book Managing and Consuming Completeness Information for RDF Data Sources written by F. Darari and published by IOS Press. This book was released on 2019-11-12 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasing amount of structured data available on the Web is laying the foundations for a global-scale knowledge base. But the ever increasing amount of Semantic Web data gives rise to the question – how complete is that data? Though data on the Semantic Web is generally incomplete, some may indeed be complete. In this book, the author deals with how to manage and consume completeness information about Semantic Web data. In particular, the book explores how completeness information can guarantee the completeness of query answering. Optimization techniques for completeness reasoning and the conducting of experimental evaluations are provided to show the feasibility of the approaches, as well as a technique for checking the soundness of queries with negation via reduction to query completeness checking. Other topics covered include completeness information with timestamps, and two demonstrators – CORNER and COOL-WD – are provided to show how a completeness framework can be realized. Finally, the book investigates an automated method to generate completeness statements from text on the Web. The book will be of interest to anyone whose work involves dealing with Web-data completeness.
Book Synopsis Multi-modal Data Fusion based on Embeddings by : S. Thoma
Download or read book Multi-modal Data Fusion based on Embeddings written by S. Thoma and published by IOS Press. This book was released on 2019-11-06 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges by : I. Tiddi
Download or read book Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges written by I. Tiddi and published by IOS Press. This book was released on 2020-05-06 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: The latest advances in Artificial Intelligence and (deep) Machine Learning in particular revealed a major drawback of modern intelligent systems, namely the inability to explain their decisions in a way that humans can easily understand. While eXplainable AI rapidly became an active area of research in response to this need for improved understandability and trustworthiness, the field of Knowledge Representation and Reasoning (KRR) has on the other hand a long-standing tradition in managing information in a symbolic, human-understandable form. This book provides the first comprehensive collection of research contributions on the role of knowledge graphs for eXplainable AI (KG4XAI), and the papers included here present academic and industrial research focused on the theory, methods and implementations of AI systems that use structured knowledge to generate reliable explanations. Introductory material on knowledge graphs is included for those readers with only a minimal background in the field, as well as specific chapters devoted to advanced methods, applications and case-studies that use knowledge graphs as a part of knowledge-based, explainable systems (KBX-systems). The final chapters explore current challenges and future research directions in the area of knowledge graphs for eXplainable AI. The book not only provides a scholarly, state-of-the-art overview of research in this subject area, but also fosters the hybrid combination of symbolic and subsymbolic AI methods, and will be of interest to all those working in the field.
Book Synopsis Strategies and Techniques for Federated Semantic Knowledge Integration and Retrieval by : D. Collarana
Download or read book Strategies and Techniques for Federated Semantic Knowledge Integration and Retrieval written by D. Collarana and published by IOS Press. This book was released on 2020-01-24 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Identity of Long-tail Entities in Text by : F. Ilievski
Download or read book Identity of Long-tail Entities in Text written by F. Ilievski and published by IOS Press. This book was released on 2019-11-29 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: The digital era has generated a huge amount of data on the identities (profiles) of people, organizations and other entities in a digital format, largely consisting of textual documents such as news articles, encyclopedias, personal websites, books, and social media. Identity has thus been transformed from a philosophical to a societal issue, one requiring robust computational tools to determine entity identity in text. Computational systems developed to establish identity in text often struggle with long-tail cases. This book investigates how Natural Language Processing (NLP) techniques for establishing the identity of long-tail entities – which are all infrequent in communication, hardly represented in knowledge bases, and potentially very ambiguous – can be improved through the use of background knowledge. Topics covered include: distinguishing tail entities from head entities; assessing whether current evaluation datasets and metrics are representative for long-tail cases; improving evaluation of long-tail cases; accessing and enriching knowledge on long-tail entities in the Linked Open Data cloud; and investigating the added value of background knowledge (“profiling”) models for establishing the identity of NIL entities. Providing novel insights into an under-explored and difficult NLP challenge, the book will be of interest to all those working in the field of entity identification in text.
Book Synopsis Study on Data Placement Strategies in Distributed RDF Stores by : D.D. Janke
Download or read book Study on Data Placement Strategies in Distributed RDF Stores written by D.D. Janke and published by IOS Press. This book was released on 2020-03-18 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Neural Generation of Textual Summaries from Knowledge Base Triples by : P. Vougiouklis
Download or read book Neural Generation of Textual Summaries from Knowledge Base Triples written by P. Vougiouklis and published by IOS Press. This book was released on 2020-04-07 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most people need textual or visual interfaces to help them make sense of Semantic Web data. In this book, the author investigates the problems associated with generating natural language summaries for structured data encoded as triples using deep neural networks. An end-to-end trainable architecture is proposed, which encodes the information from a set of knowledge graph triples into a vector of fixed dimensionality, and generates a textual summary by conditioning the output on this encoded vector. Different methodologies for building the required data-to-text corpora are explored to train and evaluate the performance of the approach. Attention is first focused on generating biographies, and the author demonstrates that the technique is capable of scaling to domains with larger and more challenging vocabularies. The applicability of the technique for the generation of open-domain Wikipedia summaries in Arabic and Esperanto – two under-resourced languages – is then discussed, and a set of community studies, devised to measure the usability of the automatically generated content by Wikipedia readers and editors, is described. Finally, the book explains an extension of the original model with a pointer mechanism that enables it to learn to verbalise in a different number of ways the content from the triples while retaining the capacity to generate words from a fixed target vocabulary. The evaluation of performance using a dataset encompassing all of English Wikipedia is described, with results from both automatic and human evaluation both of which highlight the superiority of the latter approach as compared to the original architecture.
