The rapidly growing volume of available digital documents of various formats and the possibility to access these through Internet-based technologies, have led to the necessity to develop solid methods to properly organize and structure documents in large digital libraries and repositories. Due to the extremely large volumes of documents and to their unstructured form, most of the research efforts in this direction are dedicated to automatically infer structure and schemas that can help to better organize huge collections of documents and data. This book covers the latest advances in structure inference in heterogeneous collections of documents and data. The book brings a comprehensive view of the state-of-the-art in the area, presents some lessons learned and identifies new research issues, challenges and opportunities for further research agenda and developments. The selected chapters cover a broad range of research issues, from theoretical approaches to case studies and best practices in the field. Researcher, software developers, practitioners and students interested in the field of learning structure and schemas from documents will find the comprehensive coverage of this book useful for their research, academic, development and practice activity.
A growing body of work is addressing the problem of recognizing structure and schemas in documents of various types. ... learning to exploit attributes of documents and relationships among different documents to infer structures in ...
Author: Marenglen Biba
Category: Technology & Engineering
This book covers the latest advances in structure inference in heterogeneous collections of documents and data, offering a comprehensive view of the state of the art, and identifying challenges and opportunities for further research agenda and developments.
Researcher, software developers, practitioners and students interested in the field of learning structure and schemas from documents will find the comprehensive coverage of this book useful for their research, academic, development and ...
Author: Marenglen Biba
Researchers in many disciplines have been concerned with modeling textual data in order to account for texts as the primary information unit of written communication. The book “Modelling, Learning and Processing of Text-Technological Data Structures” deals with this challenging information unit. It focuses on theoretical foundations of representing natural language texts as well as on concrete operations of automatic text processing. Following this integrated approach, the present volume includes contributions to a wide range of topics in the context of processing of textual data. This relates to the learning of ontologies from natural language texts, the annotation and automatic parsing of texts as well as the detection and tracking of topics in texts and hypertexts. In this way, the book brings together a wide range of approaches to procedural aspects of text technology as an emerging scientific discipline.
Schema-based models: they transform schemas and ignore the document content [18, 8,2]. ... sources of evidence in the documents (tag names, schema description, data types, local structure, etc), using a regression function learned from ...
Author: Alexander Mehler
Publisher: Springer Science & Business Media
The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and few-shot learning; learning algorithms and applications. Part II: Generative models; algorithms and learning theory; graphs and networks; interpretation, explainability, transparency, safety. Part III: Generative models; search and optimization; supervised learning; text mining and natural language processing; image processing, computer vision and visual analytics. Applied Data Science Track: Part IV: Anomaly detection and malware; spatio-temporal data; e-commerce and finance; healthcare and medical applications (including Covid); mobility and transportation. Part V: Automating machine learning, optimization, and feature engineering; machine learning based simulations and knowledge discovery; recommender systems and behavior modeling; natural language processing; remote sensing, image and video processing; social media.
We consider the problem of annotating such semi-structured documents using a knowledge graph schema that specifies entity types and binary relation types between these entity types. The structure of real schemas can be complex.
Author: Nuria Oliver
Publisher: Springer Nature
This book constitutes the refereed proceedings of the 4th CCF Conference, NLPCC 2015, held in Nanchang, China, in October 2015. The 35 revised full papers presented together with 22 short papers were carefully reviewed and selected from 238 submissions. The papers are organized in topical sections on fundamentals on language computing; applications on language computing; NLP for search technology and ads; web mining; knowledge acquisition and information extraction.
4 Conclusions The algorithm of logical structure reconstruction has great significance for document understanding. However, because of many factors are ... Learning Structure and Schemas from Documents. SCI, vol. 375, pp. 51–71.
Author: Juanzi Li
This book constitutes the thoroughly refereed proceedings of the 8th Italian Research Conference on Digital Libraries, held in Bari, Italy, in February 2012. The 22 full papers, included together with 4 panel papers, were selected from extended versions of the presentations given at the conference, following an additional round of reviewing and revision after the event. The topics covered are as follows: legacy documents and cultural heritage; systems interoperability and data integration; formal and methodological foundations of digital libraries; semantic web and linked data for digital libraries; multilingual information access; digital library infrastructures; metadata creation and management; search engines for digital library systems; evaluation and log data; handling audio/visual and non-traditional objects; user interfaces and visualization; digital library quality; policies and copyright issues in digital libraries; scientific data curation, citation and scholarly publication, user behavior and modeling; and preservation and curation.
Baird, H.S., Casey, M.R.: Towards Versatile Document Analysis Systems. ... Ceci, M., Loglisci, C., Malerba, D.: Transductive Learning of Logical Structures from Document Images. ... Learning Structure and Schemas from Documents.
Author: Maristella Agosti
This volume constitutes the refereed proceedings of the international workshops, Confederated International Workshops: OTM Academy, OTM Industry Case Studies Program, ACM, EI2N, ISDE, META4eS, ORM, SeDeS, SINCOM, SMS and SOMOCO 2013, held as part of OTM 2013 in Graz, Austria, in September 2013. The 75 revised full papers presented together with 12 posters and 5 keynotes were carefully reviewed and selected from a total of 131 submissions. The papers are organized in topical sections on: On The Move Academy; Industry Case Studies Program; Adaptive Case Management and other non-workflow approaches to BPM; Enterprise Integration, Interoperability and Networking; Information Systems in Distributed Environment; Methods, Evaluation, Tools and Applications for the Creation and Consumption of Structured Data for the e-Society; Fact-Oriented Modeling; Semantics and Decision Making; Social Media Semantics; Social and Mobile Computing for collaborative environments; cooperative information systems; Ontologies, Data Bases and Applications of Semantics.
Learning Structure and Schemas from Documents. SCI, vol. 375, pp. 51–71. Springer, Heidelberg (2011) Alippi, C., Pessina, F., Roveri, M.: An adaptive system for automatic invoicedocuments classification.
Author: Yan Tang Demey
Version 5.0 of the Java 2 Standard Edition SDK is the most important upgrade since Java first appeared a decade ago. With Java 5.0, you'll not only find substantial changes in the platform, but to the language itself-something that developers of Java took five years to complete. The main goal of Java 5.0 is to make it easier for you to develop safe, powerful code, but none of these improvements makes Java any easier to learn, even if you've programmed with Java for years. And that means our bestselling hands-on tutorial takes on even greater significance. Learning Java is the most widely sought introduction to the programming language that's changed the way we think about computing. Our updated third edition takes an objective, no-nonsense approach to the new features in Java 5.0, some of which are drastically different from the way things were done in any previous versions. The most essential change is the addition of "generics", a feature that allows developers to write, test, and deploy code once, and then reuse the code again and again for different data types. The beauty of generics is that more problems will be caught during development, and Learning Java will show you exactly how it's done. Java 5.0 also adds more than 1,000 new classes to the Java library. That means 1,000 new things you can do without having to program it in yourself. That's a huge change. With our book's practical examples, you'll come up to speed quickly on this and other new features such as loops and threads. The new edition also includes an introduction to Eclipse, the open source IDE that is growing in popularity. Learning Java, 3rd Edition addresses all of the important uses of Java, such as web applications, servlets, and XML that are increasingly driving enterprise applications.
With XML Schema, you can describe the data content of the document as well as the structure. XML Schemas are written in terms of primitives, such as numbers, dates, and simple regular expressions, and also allow the user to define ...
Author: Patrick Niemeyer
Publisher: "O'Reilly Media, Inc."
As modern technologies continue to develop and evolve, the ability of users to interface with new systems becomes a paramount concern. Research into new ways for humans to make use of advanced computers and other such technologies is necessary to fully realize the potential of 21st century tools. Human-Computer Interaction: Concepts, Methodologies, Tools, and Applications gathers research on user interfaces for advanced technologies and how these interfaces can facilitate new developments in the fields of robotics, assistive technologies, and computational intelligence. This four-volume reference contains cutting-edge research for computer scientists; faculty and students of robotics, digital science, and networked communications; and clinicians invested in assistive technologies. This seminal reference work includes chapters on topics pertaining to system usability, interactive design, mobile interfaces, virtual worlds, and more.
Automatic document layout analysis through relational machine learning. Learning Structure and Schemas from Documents. Springer Berlin Heidelberg. Ishitani, Y. (2003) Document transformation system from papers to XML DataBased on pivot ...
Author: Management Association, Information Resources
Publisher: IGI Global
The prevalence of digital documentation presents some pressing concerns for efficient information retrieval in the modern age. Readers want to be able to access the information they desire without having to search through a mountain of unrelated data, so algorithms and methods for effectively seeking out pertinent information are of critical importance. Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding evaluates some of the existing approaches to information retrieval and summarization of digital documents, as well as current research and future developments. This book serves as a sounding board for students, educators, researchers, and practitioners of information technology, advancing the ongoing discussion of communication in the digital age.
In Learning Structure and Schemas from Documents, Studies in Computational Intelligence (pp. 315–341). Springer. doi:10.1007/978-3-642- 22913-8_15 Locoro, A., Mascardi, V., & Briola, D. Martelli M. Ancona M., Deufemia V., ...
Author: Fiori, Alessandro
Publisher: IGI Global