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Author: Gerardo I. Simari
Publisher: Springer
ISBN: 331965229X
Category : Computers
Languages : en
Pages : 77
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Book Description
This SpringerBrief reviews the knowledge engineering problem of engineering objectivity in top-k query answering; essentially, answers must be computed taking into account the user’s preferences and a collection of (subjective) reports provided by other users. Most assume each report can be seen as a set of scores for a list of features, its author’s preferences among the features, as well as other information is discussed in this brief. These pieces of information for every report are then combined, along with the querying user’s preferences and their trust in each report, to rank the query results. Everyday examples of this setup are the online reviews that can be found in sites like Amazon, Trip Advisor, and Yelp, among many others. Throughout this knowledge engineering effort the authors adopt the Datalog+/– family of ontology languages as the underlying knowledge representation and reasoning formalism, and investigate several alternative ways in which rankings can b e derived, along with algorithms for top-k (atomic) query answering under these rankings. This SpringerBrief also investigate assumptions under which our algorithms run in polynomial time in the data complexity. Since this SpringerBrief contains a gentle introduction to the main building blocks (OBDA, Datalog+/-, and reasoning with preferences), it should be of value to students, researchers, and practitioners who are interested in the general problem of incorporating user preferences into related formalisms and tools. Practitioners also interested in using Ontology-based Data Access to leverage information contained in reviews of products and services for a better customer experience will be interested in this brief and researchers working in the areas of Ontological Languages, Semantic Web, Data Provenance, and Reasoning with Preferences.
Author: Gerardo I. Simari
Publisher: Springer
ISBN: 331965229X
Category : Computers
Languages : en
Pages : 77
Get Book
Book Description
This SpringerBrief reviews the knowledge engineering problem of engineering objectivity in top-k query answering; essentially, answers must be computed taking into account the user’s preferences and a collection of (subjective) reports provided by other users. Most assume each report can be seen as a set of scores for a list of features, its author’s preferences among the features, as well as other information is discussed in this brief. These pieces of information for every report are then combined, along with the querying user’s preferences and their trust in each report, to rank the query results. Everyday examples of this setup are the online reviews that can be found in sites like Amazon, Trip Advisor, and Yelp, among many others. Throughout this knowledge engineering effort the authors adopt the Datalog+/– family of ontology languages as the underlying knowledge representation and reasoning formalism, and investigate several alternative ways in which rankings can b e derived, along with algorithms for top-k (atomic) query answering under these rankings. This SpringerBrief also investigate assumptions under which our algorithms run in polynomial time in the data complexity. Since this SpringerBrief contains a gentle introduction to the main building blocks (OBDA, Datalog+/-, and reasoning with preferences), it should be of value to students, researchers, and practitioners who are interested in the general problem of incorporating user preferences into related formalisms and tools. Practitioners also interested in using Ontology-based Data Access to leverage information contained in reviews of products and services for a better customer experience will be interested in this brief and researchers working in the areas of Ontological Languages, Semantic Web, Data Provenance, and Reasoning with Preferences.
Author:
Publisher:
ISBN: 9783319652306
Category : Data mining
Languages : en
Pages :
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Book Description
This SpringerBrief reviews the knowledge engineering problem of engineering objectivity in top-k query answering; essentially, answers must be computed taking into account the user's preferences and a collection of (subjective) reports provided by other users. Most assume each report can be seen as a set of scores for a list of features, its author's preferences among the features, as well as other information is discussed in this brief. These pieces of information for every report are then combined, along with the querying user's preferences and their trust in each report, to rank the query results. Everyday examples of this setup are the online reviews that can be found in sites like Amazon, Trip Advisor, and Yelp, among many others. Throughout this knowledge engineering effort the authors adopt the Datalog+/- family of ontology languages as the underlying knowledge representation and reasoning formalism, and investigate several alternative ways in which rankings can b e derived, along with algorithms for top-k (atomic) query answering under these rankings. This SpringerBrief also investigate assumptions under which our algorithms run in polynomial time in the data complexity. Since this SpringerBrief contains a gentle introduction to the main building blocks (OBDA, Datalog+/-, and reasoning with preferences), it should be of value to students, researchers, and practitioners who are interested in the general problem of incorporating user preferences into related formalisms and tools. Practitioners also interested in using Ontology-based Data Access to leverage information contained in reviews of products and services for a better customer experience will be interested in this brief and researchers working in the areas of Ontological Languages, Semantic Web, Data Provenance, and Reasoning with Preferences.
Author: Markus Krötzsch
Publisher: Springer Nature
ISBN: 3030314235
Category : Computers
Languages : en
Pages : 294
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Book Description
This volume contains lecture notes of the 15th Reasoning Web Summer School (RW 2019), held in Bolzano, Italy, in September 2019. The research areas of Semantic Web, Linked Data, and Knowledge Graphs have recently received a lot of attention in academia and industry. Since its inception in 2001, the Semantic Web has aimed at enriching the existing Web with meta-data and processing methods, so as to provide Web-based systems with intelligent capabilities such as context awareness and decision support. The Semantic Web vision has been driving many community efforts which have invested a lot of resources in developing vocabularies and ontologies for annotating their resources semantically. Besides ontologies, rules have long been a central part of the Semantic Web framework and are available as one of its fundamental representation tools, with logic serving as a unifying foundation. Linked Data is a related research area which studies how one can make RDF data available on the Web and interconnect it with other data with the aim of increasing its value for everybody. Knowledge Graphs have been shown useful not only for Web search (as demonstrated by Google, Bing, etc.) but also in many application domains.
Author: Umberto Straccia
Publisher: Springer
ISBN: 3319115081
Category : Computers
Languages : en
Pages : 329
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Book Description
This book constitutes the refereed proceedings of the 8th International Conference on Scalable Uncertainty Management, SUM 2014, held in Oxford, UK, in September 2014. The 20 revised full papers and 6 revised short papers were carefully reviewed and selected from 47 submissions. The papers cover topics in all areas of managing and reasoning with substantial and complex kinds of uncertain, incomplete or inconsistent information including applications in decision support systems, machine learning, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, data and text mining, and the consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.
Author: A. Ławrynowicz
Publisher: IOS Press
ISBN: 1614997462
Category : Computers
Languages : en
Pages : 210
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Book Description
Ontologies are now increasingly used to integrate, and organize data and knowledge, particularly in data and knowledge-intensive applications in both research and industry. The book is devoted to semantic data mining – a data mining approach where domain ontologies are used as background knowledge, and where the new challenge is to mine knowledge encoded in domain ontologies and knowledge graphs, rather than only purely empirical data. The introductory chapters of the book provide theoretical foundations of both data mining and ontology representation. Taking a unified perspective, the book then covers several methods for semantic data mining, addressing tasks such as pattern mining, classification and similarity-based approaches. It attempts to provide state-of-the-art answers to specific challenges and peculiarities of data mining with use of ontologies, in particular: How to deal with incompleteness of knowledge and the so-called Open World Assumption? What is a truly “semantic” similarity measure? The book contains several chapters with examples of applications of semantic data mining. The examples start from a scenario with moderate use of lightweight ontologies for knowledge graph enrichment and end with a full-fledged scenario of an intelligent knowledge discovery assistant using complex domain ontologies for meta-mining, i.e., an ontology-based meta-learning approach to full data mining processes. The book is intended for researchers in the fields of semantic technologies, knowledge engineering, data science, and data mining, and developers of knowledge-based systems and applications.
Author: Anol Bhattacherjee
Publisher: CreateSpace
ISBN: 9781475146127
Category : Science
Languages : en
Pages : 156
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Book Description
This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309142393
Category : Law
Languages : en
Pages : 348
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Book Description
Scores of talented and dedicated people serve the forensic science community, performing vitally important work. However, they are often constrained by lack of adequate resources, sound policies, and national support. It is clear that change and advancements, both systematic and scientific, are needed in a number of forensic science disciplines to ensure the reliability of work, establish enforceable standards, and promote best practices with consistent application. Strengthening Forensic Science in the United States: A Path Forward provides a detailed plan for addressing these needs and suggests the creation of a new government entity, the National Institute of Forensic Science, to establish and enforce standards within the forensic science community. The benefits of improving and regulating the forensic science disciplines are clear: assisting law enforcement officials, enhancing homeland security, and reducing the risk of wrongful conviction and exoneration. Strengthening Forensic Science in the United States gives a full account of what is needed to advance the forensic science disciplines, including upgrading of systems and organizational structures, better training, widespread adoption of uniform and enforceable best practices, and mandatory certification and accreditation programs. While this book provides an essential call-to-action for congress and policy makers, it also serves as a vital tool for law enforcement agencies, criminal prosecutors and attorneys, and forensic science educators.
Author: Martin Horsch
Publisher:
ISBN: 9783030685980
Category : Electronic books
Languages : en
Pages :
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Book Description
This open access book discusses advances in semantic interoperability for materials modelling, aiming at integrating data obtained from different methods and sources into common frameworks, and facilitating the development of platforms where simulation services in computational molecular engineering can be provided as well as coupled and linked to each other in a standardized and reliable way. The Virtual Materials Marketplace (VIMMP), which is open to all service providers and clients, provides a framework for offering and accessing such services, assisting the uptake of novel modelling and simulation approaches by SMEs, consultants, and industrial R&D end users. Semantic assets presented include the EngMeta metadata schema for research data infrastructures in simulation-based engineering and the collection of ontologies from VIMMP, including the ontology for simulation, modelling, and optimization (OSMO) and the VIMMP software ontology (VISO).
Author: Marie-Francine Moens
Publisher: Springer Science & Business Media
ISBN: 1402049935
Category : Language Arts & Disciplines
Languages : en
Pages : 255
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Book Description
This book covers content recognition in text, elaborating on past and current most successful algorithms and their application in a variety of settings: news filtering, mining of biomedical text, intelligence gathering, competitive intelligence, legal information searching, and processing of informal text. Today, there is considerable interest in integrating the results of information extraction in retrieval systems, because of the demand for search engines that return precise answers to flexible information queries.
Author: Aijun An
Publisher: Springer
ISBN: 354068123X
Category : Computers
Languages : en
Pages : 667
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Book Description
This volume contains the papers selected for presentation at the 17th Inter- tional Symposium on Methodologies for Intelligent Systems (ISMIS 2008), held in York University, Toronto, Canada, May 21–23, 2008. ISMIS is a conference series started in 1986. Held twice every three years, ISMIS provides an inter- tional forum for exchanging scienti?c research and technological achievements in building intelligent systems. Its goal is to achieve a vibrant interchange - tween researchers and practitioners on fundamental and advanced issues related to intelligent systems. ISMIS 2008featureda selectionof latestresearchworkandapplicationsfrom the following areas related to intelligent systems: active media human–computer interaction, autonomic and evolutionary computation, digital libraries, intel- gent agent technology, intelligent information retrieval, intelligent information systems, intelligent language processing, knowledge representation and integ- tion, knowledge discovery and data mining, knowledge visualization, logic for arti?cial intelligence, soft computing, Web intelligence, and Web services. - searchers and developers from 29 countries submitted more than 100 full - pers to the conference. Each paper was rigorously reviewed by three committee members and external reviewers. Out of these submissions, 40% were selected as regular papers and 22% as short papers. ISMIS 2008 also featured three plenary talks given by John Mylopoulos, Jiawei Han and Michael Lowry. They spoke on their recent research in age- oriented software engineering, information network mining, and intelligent so- ware engineering tools, respectively.
