Search (94 results, page 1 of 5)

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Abstract

The successes of information retrieval (IR) in recent decades were built upon bag-of-words representations. Effective as it is, bag-of-words is only a shallow text understanding; there is a limited amount of information for document ranking in the word space. This dissertation goes beyond words and builds knowledge based text representations, which embed the external and carefully curated information from knowledge bases, and provide richer and structured evidence for more advanced information retrieval systems. This thesis research first builds query representations with entities associated with the query. Entities' descriptions are used by query expansion techniques that enrich the query with explanation terms. Then we present a general framework that represents a query with entities that appear in the query, are retrieved by the query, or frequently show up in the top retrieved documents. A latent space model is developed to jointly learn the connections from query to entities and the ranking of documents, modeling the external evidence from knowledge bases and internal ranking features cooperatively. To further improve the quality of relevant entities, a defining factor of our query representations, we introduce learning to rank to entity search and retrieve better entities from knowledge bases. In the document representation part, this thesis research also moves one step forward with a bag-of-entities model, in which documents are represented by their automatic entity annotations, and the ranking is performed in the entity space.

Content

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.

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Abstract

A method to develop a prototype domain ontology has been described. The domain selected for the study is Accelerator Driven Systems. This is a multidisciplinary and interdisciplinary subject comprising Nuclear Physics, Nuclear and Reactor Engineering, Reactor Fuels and Radioactive Waste Management. Since Accelerator Driven Systems is a vast topic, select areas in it were singled out for the study. Both qualitative and quantitative methods such as Content analysis, Facet analysis and Clustering were used, to develop the web-based model.

Date

22. 7.2010 19:41:16

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Content

Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.

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Abstract

Considering the characteristics of hypertext systems and problems such as cognitive overload and the disorientation of users, this project studies subject hypertext documents that have undergone conceptual structuring using facets for content representation and improvement of information retrieval during navigation. The main objective was to assess the possibility of the application of topic map technology for automating the compatibilization process of these structures. For this purpose, two dissertations from the UFMG Information Science Post-Graduation Program were adopted as samples. Both dissertations had been duly analyzed and structured on the MHTX (Hypertextual Map) prototype database. The faceted structures of both dissertations, which had been represented in conceptual maps, were then converted into topic maps. It was then possible to use the merge property of the topic maps to promote the semantic interrelationship between the maps and, consequently, between the hypertextual information resources proper. The merge results were then analyzed in the light of theories dealing with the compatibilization of languages developed within the realm of information technology and librarianship from the 1960s on. The main goals accomplished were: (a) the detailed conceptualization of the merge process of the topic maps, considering the possible compatibilization levels and the applicability of this technology in the integration of faceted structures; and (b) the production of a detailed sequence of steps that may be used in the implementation of topic maps based on faceted structures.

Date

22. 2.2013 11:39:23

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Abstract

Major efforts have been conducted on ontology learning, that is, semiautomatic processes for the construction of domain ontologies from diverse sources of information. In the past few years, a research trend has focused on the construction of educational ontologies, that is, ontologies to be used for educational purposes. The identification of the terminology is crucial to build ontologies. Term extraction techniques allow the identification of the domain-related terms from electronic resources. This paper presents LiTeWi, a novel method that combines current unsupervised term extraction approaches for creating educational ontologies for technology supported learning systems from electronic textbooks. LiTeWi uses Wikipedia as an additional information source. Wikipedia contains more than 30 million articles covering the terminology of nearly every domain in 288 languages, which makes it an appropriate generic corpus for term extraction. Furthermore, given that its content is available in several languages, it promotes both domain and language independence. LiTeWi is aimed at being used by teachers, who usually develop their didactic material from textbooks. To evaluate its performance, LiTeWi was tuned up using a textbook on object oriented programming and then tested with two textbooks of different domains-astronomy and molecular biology.

Date

22. 1.2016 12:38:14

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Abstract

The development of complex projects in the aerospace industry is based on the collaboration of geographically distributed teams and companies. In this context, the need of sharing different types of data and information is a key factor to assure the successful execution of the projects. In the case of European projects, the ECSS standards provide a normative framework that specifies, among other requirements, the different document types, information items and artifacts that need to be generated. The specification of the characteristics of these information items are usually incorporated as annex to the different ECSS standards, and they provide the intended purpose, scope, and structure of the documents and information items. In these standards, documents or deliverables should not be considered as independent items, but as the results of packaging different information artifacts for their delivery between the involved parties. Successful information integration and knowledge exchange cannot be based exclusively on the conceptual definition of information types. It also requires the definition of methods and techniques for serializing and exchanging these documents and artifacts. This area is not covered by ECSS standards, and the definition of these data schemas would improve the opportunity for improving collaboration processes among companies. This paper describes the development of an OWL-based ontology to manage the different artifacts and information items requested in the European Space Agency (ESA) ECSS standards for SW development. The ECSS set of standards is the main reference in aerospace projects in Europe, and in addition to engineering and managerial requirements they provide a set of DRD (Document Requirements Documents) with the structure of the different documents and records necessary to manage projects and describe intermediate information products and final deliverables. Information integration is a must-have in aerospace projects, where different players need to collaborate and share data during the life cycle of the products about requirements, design elements, problems, etc. The proposed ontology provides the basis for building advanced information systems where the information coming from different companies and institutions can be integrated into a coherent set of related data. It also provides a conceptual framework to enable the development of interfaces and gateways between the different tools and information systems used by the different players in aerospace projects.

Source

Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik

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Abstract

Purpose - The purpose of this paper is to improve the conceptual-based search by incorporating structural ontological information such as concepts and relations. Generally, Semantic-based information retrieval aims to identify relevant information based on the meanings of the query terms or on the context of the terms and the performance of semantic information retrieval is carried out through standard measures-precision and recall. Higher precision leads to the (meaningful) relevant documents obtained and lower recall leads to the less coverage of the concepts. Design/methodology/approach - In this paper, the authors enhance the existing ontology-based indexing proposed by Kohler et al., by incorporating sibling information to the index. The index designed by Kohler et al., contains only super and sub-concepts from the ontology. In addition, in our approach, we focus on two tasks; query expansion and ranking of the expanded queries, to improve the efficiency of the ontology-based search. The aforementioned tasks make use of ontological concepts, and relations existing between those concepts so as to obtain semantically more relevant search results for a given query. Findings - The proposed ontology-based indexing technique is investigated by analysing the coverage of concepts that are being populated in the index. Here, we introduce a new measure called index enhancement measure, to estimate the coverage of ontological concepts being indexed. We have evaluated the ontology-based search for the tourism domain with the tourism documents and tourism-specific ontology. The comparison of search results based on the use of ontology "with and without query expansion" is examined to estimate the efficiency of the proposed query expansion task. The ranking is compared with the ORank system to evaluate the performance of our ontology-based search. From these analyses, the ontology-based search results shows better recall when compared to the other concept-based search systems. The mean average precision of the ontology-based search is found to be 0.79 and the recall is found to be 0.65, the ORank system has the mean average precision of 0.62 and the recall is found to be 0.51, while the concept-based search has the mean average precision of 0.56 and the recall is found to be 0.42. Practical implications - When the concept is not present in the domain-specific ontology, the concept cannot be indexed. When the given query term is not available in the ontology then the term-based results are retrieved. Originality/value - In addition to super and sub-concepts, we incorporate the concepts present in same level (siblings) to the ontological index. The structural information from the ontology is determined for the query expansion. The ranking of the documents depends on the type of the query (single concept query, multiple concept queries and concept with relation queries) and the ontological relations that exists in the query and the documents. With this ontological structural information, the search results showed us better coverage of concepts with respect to the query.

Date

20. 1.2015 18:30:22

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LCSH

Information storage and retrieval systems
Information systems

Subject

Information storage and retrieval systems
Information systems

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Abstract

Knowledge organization systems have been studied in several fields and for different and complementary aspects. Among the aspects that concentrate common interests, in this article we highlight those related to the terminological and conceptual relationships among the components of any knowledge organization system. This research aims to contribute to the critical analysis of knowledge organization systems, especially ontologies, thesauri, and classification systems, by the comprehension of its similarities and differences when dealing with concepts and their ways of relating to each other as well as to the conceptual design that is adopted.

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Abstract

This paper presents a new approach to understanding how indexing strategies, models for interoperability and retrieval paradigms interact in information systems and how this can be used to support the design and implementation of components of a semantic navigation for information retrieval systems.

Source

Paradigms and conceptual systems in knowledge organization: Proceedings of the Eleventh International ISKO Conference, 23-26 February 2010 Rome, Italy. Edited by Claudio Gnoli and Fulvio Mazzocchi

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Abstract

The originality of this book, which deals with such a new subject matter, lies in the application of methods and concepts never used before - such as Ontologies and Taxonomies, as well as Thesauri - to the ordering of knowledge based on primary information. Chapters in the book also examine the study of Ontologies, Taxonomies and Thesauri from the perspective of Systematics and General Systems Theory. "Ontologies, Taxonomy and Thesauri in Information Organisation and Retrieval" will be extremely useful to those operating within the network of related fields, which includes Documentation and Information Science.

Content

Inhalt: 1. From classifications to ontologies Knowledge - A new concept of knowledge - Knowledge and information - Knowledge organisation - Knowledge organisation and representation - Cognitive sciences - Talent management - Learning systematisation - Historical evolution - From classification to knowledge organisation - Why ontologies exist - Ontologies - The structure of ontologies 2. Taxonomies and thesauri From ordering to taxonomy - The origins of taxonomy - Hierarchical and horizontal order - Correlation with classifications - Taxonomy in computer science - Computing taxonomy - Definitions - Virtual taxonomy, cybernetic taxonomy - Taxonomy in Information Science - Similarities between taxonomies and thesauri - ifferences between taxonomies and thesauri 3. Thesauri Terminology in classification systems - Terminological languages - Thesauri - Thesauri definitions - Conditions that a thesaurus must fulfil - Historical evolution - Classes of thesauri 4. Thesauri in (cladist) systematics Systematics - Systematics as a noun - Definitions and historic evolution over time - Differences between taxonomy and systematics - Systematics in thesaurus construction theory - Classic, numerical and cladist systematics - Classic systematics in information science - Numerical systematics in information science - Thesauri in cladist systematics - Systematics in information technology - Some examples 5. Thesauri in systems theory Historical evolution - Approach to systems - Systems theory applied to the construction of thesauri - Components - Classes of system - Peculiarities of these systems - Working methods - Systems theory applied to ontologies and taxonomies

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Content

Introduction.- Ontology Development.- Compliance using Metadata.- Variety Management for Big Data.- Text Mining in Economics.- Generation of Natural Language Texts.- Sentiment Analysis.- Building Concise Text Corpora from Web Contents.- Ontology-Based Modelling of Web Content.- Personalized Clinical Decision Support for Cancer Care.- Applications of Temporal Conceptual Semantic Systems.- Context-Aware Documentation in the Smart Factory.- Knowledge-Based Production Planning for Industry 4.0.- Information Exchange in Jurisdiction.- Supporting Automated License Clearing.- Managing cultural assets: Implementing typical cultural heritage archive's usage scenarios via Semantic Web technologies.- Semantic Applications for Process Management.- Domain-Specific Semantic Search Applications.

LCSH

Management information systems
Information Systems Applications (incl. Internet)
Management of Computing and Information Systems

Subject

Management information systems
Information Systems Applications (incl. Internet)
Management of Computing and Information Systems

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Date

13.12.2017 14:17:22

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Source

Spektrum der Wissenschaft. 2018, H.1, S.22-27

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Abstract

Content Management Systems (CMSs) are used in almost every industry by millions of end-user organizations. In contrast to the 90s, they are no longer used as isolated applications in one organization but they support critical core operations in business ecosystems. Content management today is more interactive and more integrative: interactive because end-users are increasingly content creators themselves and integrative because content elements can be embedded into various other applications. The authors of this book investigate how Semantic Technologies can increase interactivity and integration capabilities of CMSs and discuss their business value to millions of end-user organizations. This book has therefore the objective, to reflect existing applications as well as to discuss and present new applications for CMSs that use Semantic Technologies. An evaluation of 27 CMSs concludes this book and provides a basis for IT executives that plan to adopt or replace a CMS in the near future.

Content

On the Changing Market for Content Management Systems: Status and Outlook - Wolfgang Maass Empowering the Distributed Editorial Workforce - Steve McNally The Rise of Semantic-aware Applications - Stéphane Croisier Simplified Semantic Enhancement of JCR-based Content Applications -Bertrand Delacretaz and Michael Marth Dynamic Semantic Publishing - Jem Rayfield Semantics in the Domain of eGovernment - Luis Alvarez Sabucedo and Luis Anido Rifón The Interactive Knowledge Stack (IKS): A Vision for the Future of CMS - Wernher Behrendt Essential Requirements for Semantic CMS - Valentina Presutti Evaluation of Content Management Systems - Tobias Kowatsch and Wolfgang Maass CMS with No Particular Industry Focus (versch. Beiträge)

LCSH

Information storage and retrieval systems
Information Systems
Management information systems

Subject

Information storage and retrieval systems
Information Systems
Management information systems

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Abstract

The formal structure of the information on the Semantic Web lends itself to faceted browsing, an information retrieval method where users can filter results based on the values of properties ("facets"). Numerous faceted browsers have been created to browse RDF and Linked Data, but these systems use their own ontologies for defining how data is queried to populate their facets. Since the source data is the same format across these systems (specifically, RDF), we can unify the different methods of describing how to quer the underlying data, to enable compatibility across systems, and provide an extensible base ontology for future systems. To this end, we present FacetOntology, an ontology that defines how to query data to form a faceted browser, and a number of transformations and filters that can be applied to data before it is shown to users. FacetOntology overcomes limitations in the expressivity of existing work, by enabling the full expressivity of SPARQL when selecting data for facets. By applying a FacetOntology definition to data, a set of facets are specified, each with queries and filters to source RDF data, which enables faceted browsing systems to be created using that RDF data.

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Date

22. 1.2017 16:54:03
22. 1.2017 17:10:56

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Abstract

The purpose of this paper is to determine semantic types for tags in social tagging systems. In social tagging systems, the determination of the semantic type of tags plays an important role in tag classification, increasing the semantic information of tags and establishing mapping relations between tagged resources and a normed ontology. The research reported in this paper constructs the semantic type library that is needed based on the Unified Medical Language System (UMLS) and FrameNet and determines the semantic type of selected tags that have been pretreated via direct matching using the Semantic Navigator tool, the Semantic Type Word Sense Disambiguation (STWSD) tools in UMLS, and artificial matching. And finally, we verify the feasibility of the determination of semantic type for tags by empirical analysis.

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LCSH

Multimedia systems
Information storage and retrieval systems

Subject

Multimedia systems
Information storage and retrieval systems

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Abstract

There are quite a few success stories illustrating philosophy's relevance to information science. One can cite, for example, Leibniz's work on a characteristica universalis and a corresponding calculus ratiocinator through which he aspired to reduce reasoning to calculating. It goes without saying that formal logic initiated research on decidability and computational complexity. But even beyond the realm of formal logic, philosophy has served as a source of inspiration for developments in information and computer science. At the end of the twentieth century, formal ontology emerged from a quest for a semantic foundation of information systems having a higher reusability than systems being available at the time. A success story that is less well documented is the advent of frame systems in computer science. Minsky is credited with having laid out the foundational ideas of such systems. There, the logic programming approach to knowledge representation is criticized by arguing that one should be more careful about the way human beings recognize objects and situations. Notably, the paper draws heavily on the writings of Kuhn and the Gestalt-theorists. It is not our intent, however, to document the traces of the frame idea in the works of philosophers. What follows is, rather, an exposition of a methodology for representing scientific knowledge that is essentially frame-like. This methodology is labelled as structuralist theory of science or, in short, as structuralism. The frame-like character of its basic meta-theoretical concepts makes structuralism likely to be useful in knowledge representation.