Search (186 results, page 1 of 10)

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Abstract

By the explosion of possibilities for a ubiquitous content production, the information overload problem reaches the level of complexity which cannot be managed by traditional modelling approaches anymore. Due to their pure syntactical nature traditional information retrieval approaches did not succeed in treating content itself (i.e. its meaning, and not its representation). This leads to a very low usefulness of the results of a retrieval process for a user's task at hand. In the last ten years ontologies have been emerged from an interesting conceptualisation paradigm to a very promising (semantic) modelling technology, especially in the context of the Semantic Web. From the information retrieval point of view, ontologies enable a machine-understandable form of content description, such that the retrieval process can be driven by the meaning of the content. However, the very ambiguous nature of the retrieval process in which a user, due to the unfamiliarity with the underlying repository and/or query syntax, just approximates his information need in a query, implies a necessity to include the user in the retrieval process more actively in order to close the gap between the meaning of the content and the meaning of a user's query (i.e. his information need). This thesis lays foundation for such an ontology-based interactive retrieval process, in which the retrieval system interacts with a user in order to conceptually interpret the meaning of his query, whereas the underlying domain ontology drives the conceptualisation process. In that way the retrieval process evolves from a query evaluation process into a highly interactive cooperation between a user and the retrieval system, in which the system tries to anticipate the user's information need and to deliver the relevant content proactively. Moreover, the notion of content relevance for a user's query evolves from a content dependent artefact to the multidimensional context-dependent structure, strongly influenced by the user's preferences. This cooperation process is realized as the so-called Librarian Agent Query Refinement Process. In order to clarify the impact of an ontology on the retrieval process (regarding its complexity and quality), a set of methods and tools for different levels of content and query formalisation is developed, ranging from pure ontology-based inferencing to keyword-based querying in which semantics automatically emerges from the results. Our evaluation studies have shown that the possibilities to conceptualize a user's information need in the right manner and to interpret the retrieval results accordingly are key issues for realizing much more meaningful information retrieval systems.

Content

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Abstract

Ontologies improve IR systems regarding its retrieval and presentation of information, which make the task of finding information more effective, efficient, and interactive. In this paper we argue that ontologies also greatly improve the engineering of such systems. We created a framework that uses ontology to drive the process of engineering an IR system. We developed a prototype that shows how a domain specialist without knowledge in the IR field can build an IR system with interactive components. The resulting system provides support for users not only to find their information needs but also to extend their state of knowledge. This way, our approach to ontology-enabled information retrieval addresses both the engineering aspect described here and also the usability aspect described elsewhere.

Date

28.11.2016 12:43:22

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Abstract

This paper presents an abstract formalization of the notion of "facets". Facets are relational structures of units, relations and other facets selected for a certain purpose. Facets can be used to structure large knowledge representation systems into a hierarchical arrangement of consistent and independent subsystems (facets) that facilitate flexibility and combinations of different viewpoints or aspects. This paper describes the basic notions, facet characteristics and construction mechanisms. It then explicates the theory in an example of a faceted information retrieval system (FaIR)

Date

22. 1.2016 17:47:06

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Abstract

In the proposed article a new, ontology-based approach to information retrieval (IR) is presented. The system is based on a domain knowledge representation schema in form of ontology. New resources registered within the system are linked to concepts from this ontology. In such a way resources may be retrieved based on the associations and not only based on partial or exact term matching as the use of vector model presumes In order to evaluate the quality of this retrieval mechanism, experiments to measure retrieval efficiency have been performed with well-known Cystic Fibrosis collection of medical scientific papers. The ontology-based retrieval mechanism has been compared with traditional full text search based on vector IR model as well as with the Latent Semantic Indexing method.

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Abstract

Contemporary retrieval systems, which search across collections, usually ignore collection-level metadata. Alternative approaches, exploiting collection-level information, will require an understanding of the various kinds of relationships that can obtain between collection-level and item-level metadata. This paper outlines the problem and describes a project that is developing a logic-based framework for classifying collection/item metadata relationships. This framework will support (i) metadata specification developers defining metadata elements, (ii) metadata creators describing objects, and (iii) system designers implementing systems that take advantage of collection-level metadata. We present three examples of collection/item metadata relationship categories, attribute/value-propagation, value-propagation, and value-constraint and show that even in these simple cases a precise formulation requires modal notions in addition to first-order logic. These formulations are related to recent work in information retrieval and ontology evaluation.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Abstract

As information becomes richer and more complex, alternative information-organization methods are needed to more effectively and efficiently retrieve information from various systems, including the Web. The objective of this study is to explore how a Topic Maps-based ontology approach affects users' searching performance. Forty participants participated in a task-based evaluation where two dependent variables, recall and search time, were measured. The results of this study indicate that a Topic Maps-based ontology information retrieval (TOIR) system has a significant and positive effect on both recall and search time, compared to a thesaurus-based information retrieval (TIR) system. These results suggest that the inclusion of a Topic Maps-based ontology is a beneficial approach to take when designing information retrieval systems.

Source

Journal of the American Society for Information Science and Technology. 59(2008) no.12, S.1898-1911

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Abstract

Das Werk behandelt die aktuellen Entwicklungen zur inhaltlichen Erschließung von Informationsquellen im Internet. Topic Maps, semantische Modelle vernetzter Informationsressourcen unter Verwendung von XML bzw. HyTime, bieten alle notwendigen Modellierungskonstrukte, um Dokumente im Internet zu klassifizieren und ein assoziatives, semantisches Netzwerk über diese zu legen. Neben Einführungen in XML, XLink, XPointer sowie HyTime wird anhand von Einsatzszenarien gezeigt, wie diese neuartige Technologie für Content Management und Information Retrieval im Internet funktioniert. Der Entwurf einer Abfragesprache wird ebenso skizziert wie der Prototyp einer intelligenten Suchmaschine. Das Buch zeigt, wie Topic Maps den Weg zu semantisch gesteuerten Suchprozessen im Internet weisen.

Content

Topic Maps - Einführung in den ISO Standard (Topics, Associations, Scopes, Facets, Topic Maps).- Grundlagen von XML (Aufbau, Bestandteile, Element- und Attributdefinitionen, DTD, XLink, XPointer).- Wie entsteht ein Heringsschmaus? Konkretes Beispiel einer Topic Map.Topic Maps - Meta DTD. Die formale Beschreibung des Standards.- HyTime als zugrunde liegender Formalismus (Bounded Object Sets, Location Addressing, Hyperlinks in HyTime).- Prototyp eines Topic Map Repositories (Entwicklungsprozess für Topic Maps, Prototyp Spezifikation, technische Realisierung des Prototyps).- Semantisches Datenmodell zur Speicherung von Topic Maps.- Prototypische Abfragesprache für Topic Maps.- Erweiterungsvorschläge für den ISO Standard.

RSWK

Internet / Information Retrieval / Semantisches Netz / HyTime
Internet / Information Retrieval / Semantisches Netz / XML

Subject

Internet / Information Retrieval / Semantisches Netz / HyTime
Internet / Information Retrieval / Semantisches Netz / XML

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Abstract

An increasing number of recent information retrieval systems make use of ontologies to help the users clarify their information needs and come up with semantic representations of documents. A particular concern here is the integration of these semantic approaches with traditional search technology. The research presented in this paper examines how ontologies can be efficiently applied to large-scale search systems for the web. We describe how these systems can be enriched with adapted ontologies to provide both an in-depth understanding of the user's needs as well as an easy integration with standard vector-space retrieval systems. The ontology concepts are adapted to the domain terminology by computing a feature vector for each concept. Later, the feature vectors are used to enrich a provided query. The whole retrieval system is under development as part of a larger Semantic Web standardization project for the Norwegian oil & gas sector.

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Abstract

This paper presents a novel hybrid approach for visual information retrieval (VIR) that combines shape analysis of objects in image with their indexing by textual descriptions. The principal goal of presented technique is applying Two Segments Turning Function (2STF) proposed by authors for efficient invariant to spatial variations shape processing and implementation of semantic Web approaches for ontology-based user-oriented annotations of multimedia information. In the proposed approach the user's textual queries are converted to image features, which are used for images searching, indexing, interpretation, and retrieval. A decision about similarity between retrieved image and user's query is taken computing the shape convergence to 2STF combining it with matching the ontological annotations of objects in image and providing in this way automatic definition of the machine-understandable semantics. In order to evaluate the proposed approach the Image Retrieval by Ontological Description of Shapes system has been designed and tested using some standard image domains.

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Abstract

Semantic search has been one of the motivations of the Semantic Web since it was envisioned. We propose a model for the exploitation of ontologybased KBs to improve search over large document repositories. Our approach includes an ontology-based scheme for the semi-automatic annotation of documents, and a retrieval system. The retrieval model is based on an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. Semantic search is combined with keyword-based search to achieve tolerance to KB incompleteness. Our proposal is illustrated with sample experiments showing improvements with respect to keyword-based search, and providing ground for further research and discussion.

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

Unternehmen sehen sich heutzutage regelmäßig der Herausforderung gegenübergestellt, aus umfangreichen Mengen an Dokumenten schnell relevante Informationen zu identifizieren. Dabei zeigt sich jedoch, dass Suchverfahren, die lediglich syntaktische Abgleiche von Informationsbedarfen mit potenziell relevanten Dokumenten durchführen, häufig nicht die an sie gestellten Erwartungen erfüllen. Viel versprechendes Potenzial bietet hier der Einsatz von Ontologien für das Information Retrieval. Beim ontologiebasierten Information Retrieval werden Ontologien eingesetzt, um Wissen in einer Form abzubilden, die durch Informationssysteme verarbeitet werden kann. Eine Berücksichtigung des so explizierten Wissens durch Suchalgorithmen führt dann zu einer optimierten Deckung von Informationsbedarfen. Jan Hermans stellt in seinem Buch ein adaptives Referenzmodell für die Entwicklung von ontologiebasierten Information Retrieval-Systemen vor. Zentrales Element seines Modells ist die einsatzkontextspezifische Adaption des Retrievalprozesses durch bewährte Techniken, die ausgewählte Aspekte des ontologiebasierten Information Retrievals bereits effektiv und effizient unterstützen. Die Anwendung des Referenzmodells wird anhand eines Fallbeispiels illustriert, bei dem ein Information Retrieval-System für die Suche nach Open Source-Komponenten entwickelt wird. Das Buch richtet sich gleichermaßen an Dozenten und Studierende der Wirtschaftsinformatik, Informatik und Betriebswirtschaftslehre sowie an Praktiker, die die Informationssuche im Unternehmen verbessern möchten. Jan Hermans, Jahrgang 1978, studierte Wirtschaftsinformatik an der Westfälischen Wilhelms-Universität in Münster. Seit 2003 war er als Wissenschaftlicher Mitarbeiter am European Research Center for Information Systems der WWU Münster tätig. Seine Forschungsschwerpunkte lagen in den Bereichen Wissensmanagement und Information Retrieval. Im Mai 2008 erfolgte seine Promotion zum Doktor der Wirtschaftswissenschaften.

RSWK

Information Retrieval / Ontologie <Wissensverarbeitung> / Wissensmanagement

Series

Advances in information systems and management science; 39

Subject

Information Retrieval / Ontologie <Wissensverarbeitung> / Wissensmanagement

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Abstract

This paper presents an approach to designing and implementing extensible computational models for perceiving systems based on a knowledge-driven joint inference approach. These models can integrate different sources of information both horizontally (multi-modal and temporal fusion) and vertically (bottom-up, top-down) by incorporating prior hierarchical knowledge expressed as an extensible ontology.Two implementations of this approach are presented. The first consists of a content-based image retrieval system that allows users to search image databases using an ontological query language. Queries are parsed using a probabilistic grammar and Bayesian networks to map high-level concepts onto low-level image descriptors, thereby bridging the 'semantic gap' between users and the retrieval system. The second application extends the notion of ontological languages to video event detection. It is shown how effective high-level state and event recognition mechanisms can be learned from a set of annotated training sequences by incorporating syntactic and semantic constraints represented by an ontology.

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Abstract

The Semantic Web realization depends on the availability of a critical mass of metadata for the web content, associated with the respective formal knowledge about the world. We claim that the Semantic Web, at its current stage of development, is in a state of a critical need of metadata generation and usage schemata that are specific, well-defined and easy to understand. This paper introduces our vision for a holistic architecture for semantic annotation, indexing, and retrieval of documents with regard to extensive semantic repositories. A system (called KIM), implementing this concept, is presented in brief and it is used for the purposes of evaluation and demonstration. A particular schema for semantic annotation with respect to real-world entities is proposed. The underlying philosophy is that a practical semantic annotation is impossible without some particular knowledge modelling commitments. Our understanding is that a system for such semantic annotation should be based upon a simple model of real-world entity classes, complemented with extensive instance knowledge. To ensure the efficiency, ease of sharing, and reusability of the metadata, we introduce an upper-level ontology (of about 250 classes and 100 properties), which starts with some basic philosophical distinctions and then goes down to the most common entity types (people, companies, cities, etc.). Thus it encodes many of the domain-independent commonsense concepts and allows straightforward domain-specific extensions. On the basis of the ontology, a large-scale knowledge base of entity descriptions is bootstrapped, and further extended and maintained. Currently, the knowledge bases usually scales between 105 and 106 descriptions. Finally, this paper presents a semantically enhanced information extraction system, which provides automatic semantic annotation with references to classes in the ontology and to instances. The system has been running over a continuously growing document collection (currently about 0.5 million news articles), so it has been under constant testing and evaluation for some time now. On the basis of these semantic annotations, we perform semantic based indexing and retrieval where users can mix traditional information retrieval (IR) queries and ontology-based ones. We argue that such large-scale, fully automatic methods are essential for the transformation of the current largely textual web into a Semantic Web.

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Abstract

The retrieval problem is one of the main reasoning tasks for knowledge base systems. Given a knowledge base K and a concept C, the retrieval problem consists of finding all individuals a for which K logically entails C(a). We present an approach to answer retrieval queries over (a restriction of) OWL ontologies. Our solution is based on reducing the retrieval problem to a problem of evaluating an SQL query over a database constructed from the original knowledge base. We provide complete answers to retrieval problems. Still, our system performs very well as is shown by a standard benchmark.

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Abstract

Interpretation of semantic propositions in free-text documents such as MEDLINE citations would provide valuable support for biomedical applications, and several approaches to semantic interpretation are being pursued in the biomedical informatics community. In this paper, we describe a methodology for interpreting linguistic structures that encode hypernymic propositions, in which a more specific concept is in a taxonomic relationship with a more general concept. In order to effectively process these constructions, we exploit underspecified syntactic analysis and structured domain knowledge from the Unified Medical Language System (UMLS). After introducing the syntactic processing on which our system depends, we focus on the UMLS knowledge that supports interpretation of hypernymic propositions. We first use semantic groups from the Semantic Network to ensure that the two concepts involved are compatible; hierarchical information in the Metathesaurus then determines which concept is more general and which more specific. A preliminary evaluation of a sample based on the semantic group Chemicals and Drugs provides 83% precision. An error analysis was conducted and potential solutions to the problems encountered are presented. The research discussed here serves as a paradigm for investigating the interaction between domain knowledge and linguistic structure in natural language processing, and could also make a contribution to research on automatic processing of discourse structure. Additional implications of the system we present include its integration in advanced semantic interpretation processors for biomedical text and its use for information extraction in specific domains. The approach has the potential to support a range of applications, including information retrieval and ontology engineering.

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Abstract

The Functional Requirements for Subject Authority Records (FRSAR) Working Group was formed in 2005 as the third IFLA working group of the FRBR family to address subject authority data issues and to investigate the direct and indirect uses of subject authority data by a wide range of users. This paper introduces the Functional Requirements for Subject Authority Data (FRSAD), the model developed by the FRSAR Working Group, and discusses it in the context of other related conceptual models defined in the specifications during recent years, including the British Standard BS8723-5: Structured vocabularies for information retrieval - Guide Part 5: Exchange formats and protocols for interoperability, W3C's SKOS Simple Knowledge Organization System Reference, and OWL Web Ontology Language Reference. These models enable the consideration of the functions of subject authority data and concept schemes at a higher level that is independent of any implementation, system, or specific context, while allowing us to focus on the semantics, structures, and interoperability of subject authority data.

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Date

11. 2.2011 18:22:25

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

This publication shows how the gap between the HTML based internet and the RDF based vision of the semantic web might be bridged, by linking words in texts to concepts of ontologies. Most current search engines use indexes that are built at the syntactical level and return hits based on simple string comparisons. However, the indexes do not contain synonyms, cannot differentiate between homonyms ('mouse' as a pointing vs. 'mouse' as an animal) and users receive different search results when they use different conjugation forms of the same word. In this publication, we present a system that uses ontologies and Natural Language Processing techniques to index texts, and thus supports word sense disambiguation and the retrieval of texts that contain equivalent words, by indexing them to concepts of ontologies. For this purpose, we developed fully automated methods for mapping equivalent concepts of imported RDF ontologies (for this prototype WordNet, SUMO and OpenCyc). These methods will thus allow the seamless integration of domain specific ontologies for concept based information retrieval in different domains. To demonstrate the practical workability of this approach, a set of web pages that contain synonyms and homonyms were indexed and can be queried via a search engine like query frontend. However, the ontology based indexing approach can also be used for other data mining applications such text clustering, relation mining and for searching free text fields in biological databases. The ontology alignment methods and some of the text mining principles described in this publication are now incorporated into the ONDEX system http://ondex.sourceforge.net/.

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Abstract

Grounded on a strong belief that ontologies enhance the performance of information retrieval systems, there has been an upsurge of interest in ontologies. Its importance is identified in diverse research fields such as knowledge engineering, knowledge representation, qualitative modeling, language engineering, database design, information integration, object-oriented analysis, information retrieval and extraction, knowledge management and agent-based systems design (Guarino, 1998). While the role-played by ontologies, automatically lends a place of legitimacy for these tools, research in this area gains greater significance in the wake of various challenges faced in the contemporary digital environment. With the objective of overcoming various pitfalls associated with current search mechanisms, ontologies are increasingly used for developing efficient information retrieval systems. An indicator of research interest in the area of ontology is the Swoogle, a search engine for Semantic Web documents, terms and data found on the Web (Ding, Li et al, 2004). Given the complex nature of the digital content archived in digital libraries, ontologies can be employed for designing efficient forms of information retrieval in digital libraries. Knowledge representation assumes greater significance due to its crucial role in ontology development. These systems aid in developing intelligent information systems, wherein the notion of intelligence implies the ability of the system to find implicit consequences of its explicitly represented knowledge (Baader and Nutt, 2003). Knowledge representation formalisms such as 'Description Logics' are used to obtain explicit knowledge representation of the subject domain. These representations are developed into ontologies, which are used for developing intelligent information systems. Against this backdrop, the paper examines the use of Description Logics for conceptually modeling a chosen domain, which would be utilized for developing domain ontologies. The knowledge representation languages identified for this purpose are Web Ontology Language (OWL) and KArlsruhe ONtology (KAON) language. Drawing upon the various technical constructs in developing ontology-based information systems, the paper explains the working of the prototypes and also presents a comparative study of the two prototypes.

Theme

Information Gateway

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Abstract

An information system like the Web is a continuously evolving system consisting of multiple heterogeneous information sources, covering a wide domain of discourse, and a huge number of users (human or software) with diverse characteristics and needs, that produce and consume information. The challenge nowadays is to build a scalable information infrastructure enabling the effective, accurate, content based retrieval of information, in a way that adapts to the characteristics and interests of the users. The aim of this work is to propose formally sound methods for building such an information network based on ontologies which are widely used and are easy to grasp by ordinary Web users. The main results of this work are: - A novel scheme for indexing and retrieving objects according to multiple aspects or facets. The proposed scheme is a faceted scheme enriched with a method for specifying the combinations of terms that are valid. We give a model-theoretic interpretation to this model and we provide mechanisms for inferring the valid combinations of terms. This inference service can be exploited for preventing errors during the indexing process, which is very important especially in the case where the indexing is done collaboratively by many users, and for deriving "complete" navigation trees suitable for browsing through the Web. The proposed scheme has several advantages over the hierarchical classification schemes currently employed by Web catalogs, namely, conceptual clarity (it is easier to understand), compactness (it takes less space), and scalability (the update operations can be formulated more easily and be performed more effciently). - A exible and effecient model for building mediators over ontology based information sources. The proposed mediators support several modes of query translation and evaluation which can accommodate various application needs and levels of answer quality. The proposed model can be used for providing users with customized views of Web catalogs. It can also complement the techniques for building mediators over relational sources so as to support approximate translation of partially ordered domain values.