Search (133 results, page 2 of 7)

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Abstract

Current retrieval and recommendation approaches rely on hard-wired data models. This hinders personalized cus-tomizations to meet information needs of users in a more flexible manner. Therefore, the paper investigates how similarity-basedretrieval strategies can be combined with graph queries to enable users or system providers to explore repositories in the LinkedOpen Data (LOD) cloud more thoroughly. For this purpose, we developed novel content-based recommendation approaches.They rely on concept annotations of Simple Knowledge Organization System (SKOS) vocabularies and a SPARQL-based querylanguage that facilitates advanced and personalized requests for openly available knowledge graphs. We have comprehensivelyevaluated the novel search strategies in several test cases and example application domains (i.e., travel search and multimediaretrieval). The results of the web-based online experiments showed that our approaches increase the recall and diversity of rec-ommendations or at least provide a competitive alternative strategy of resource access when conventional methods do not providehelpful suggestions. The findings may be of use for Linked Data-enabled recommender systems (LDRS) as well as for semanticsearch engines that can consume LOD resources. (PDF) Similarity-based knowledge graph queries for recommendation retrieval. Available from: https://www.researchgate.net/publication/333358714_Similarity-based_knowledge_graph_queries_for_recommendation_retrieval [accessed May 21 2020].

Content

Vgl.: https://www.researchgate.net/publication/333358714_Similarity-based_knowledge_graph_queries_for_recommendation_retrieval. Vgl. auch: http://semantic-web-journal.net/content/similarity-based-knowledge-graph-queries-recommendation-retrieval-1.

Source

Semantic Web. 10(2019) 6, S.1007-1037

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Abstract

Today's conventional search engines hardly do provide the essential content relevant to the user's search query. This is because the context and semantics of the request made by the user is not analyzed to the full extent. So here the need for a semantic web search arises. SWS is upcoming in the area of web search which combines Natural Language Processing and Artificial Intelligence. The objective of the work done here is to design, develop and implement a semantic search engine- SIEU(Semantic Information Extraction in University Domain) confined to the university domain. SIEU uses ontology as a knowledge base for the information retrieval process. It is not just a mere keyword search. It is one layer above what Google or any other search engines retrieve by analyzing just the keywords. Here the query is analyzed both syntactically and semantically. The developed system retrieves the web results more relevant to the user query through keyword expansion. The results obtained here will be accurate enough to satisfy the request made by the user. The level of accuracy will be enhanced since the query is analyzed semantically. The system will be of great use to the developers and researchers who work on web. The Google results are re-ranked and optimized for providing the relevant links. For ranking an algorithm has been applied which fetches more apt results for the user query.

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Abstract

Faceted arrangement of entities and typed relations for representing different associations between the entities are established tools in knowledge representation. In this paper, a proposal is being discussed combining both tools to draw inferences along relational paths. This approach may yield new benefit for information retrieval processes, especially when modeled for heterogeneous environments in the Semantic Web. Faceted arrangement can be used as a selection tool for the semantic knowledge modeled within the knowledge representation. Typed relations between the entities of different facets can be used as restrictions for selecting them across the facets.

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Abstract

We scho how the beenfits of the view-based search method, developed within the information retrieval community, can be extended with ontology-based search, developed within the Semantic Web community, and with semantic recommendations. As a proof of the concept, we have implemented an ontology-and view-based search engine and recommendations system Ontogaotr for RDF(S) repositories. Ontogator is innovative in two ways. Firstly, the RDFS.based ontologies used for annotating metadata are used in the user interface to facilitate view-based information retrieval. The views provide the user with an overview of the repositorys contents and a vocabulary for expressing search queries. Secondlyy, a semantic browsing function is provided by a recommender system. This system enriches instance level metadata by ontologies and provides the user with links to semantically related relevant resources. The semantic linkage is specified in terms of logical rules. To illustrate and discuss the ideas, a deployed application of Ontogator to a photo repository of the Helsinki University Museum is presented.

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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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

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.

Theme

Semantisches Umfeld in Indexierung u. Retrieval
Semantic Web

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Abstract

The main objective of the MultimediaN E-Culture project is to demonstrate how novel semantic-web and presentation technologies can be deployed to provide better indexing and search support within large virtual collections of culturalheritage resources. The architecture is fully based on open web standards in particular XML, SVG, RDF/OWL and SPARQL. One basic hypothesis underlying this work is that the use of explicit background knowledge in the form of ontologies/vocabularies/thesauri is in particular useful in information retrieval in knowledge-rich domains. This paper gives some details about the internals of the demonstrator.

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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

Background: Because of the increasing number of electronic resources, designing efficient tools to retrieve and exploit them is a major challenge. Some improvements have been offered by semantic Web technologies and applications based on domain ontologies. In life science, for instance, the Gene Ontology is widely exploited in genomic applications and the Medical Subject Headings is the basis of biomedical publications indexation and information retrieval process proposed by PubMed. However current search engines suffer from two main drawbacks: there is limited user interaction with the list of retrieved resources and no explanation for their adequacy to the query is provided. Users may thus be confused by the selection and have no idea on how to adapt their queries so that the results match their expectations. Results: This paper describes an information retrieval system that relies on domain ontology to widen the set of relevant documents that is retrieved and that uses a graphical rendering of query results to favor user interactions. Semantic proximities between ontology concepts and aggregating models are used to assess documents adequacy with respect to a query. The selection of documents is displayed in a semantic map to provide graphical indications that make explicit to what extent they match the user's query; this man/machine interface favors a more interactive and iterative exploration of data corpus, by facilitating query concepts weighting and visual explanation. We illustrate the benefit of using this information retrieval system on two case studies one of which aiming at collecting human genes related to transcription factors involved in hemopoiesis pathway. Conclusions: The ontology based information retrieval system described in this paper (OBIRS) is freely available at: http://www.ontotoolkit.mines-ales.fr/ObirsClient/. This environment is a first step towards a user centred application in which the system enlightens relevant information to provide decision help.

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Abstract

This document contains and presents test cases for the Web Ontology Language (OWL) approved by the Web Ontology Working Group. Many of the test cases illustrate the correct usage of the Web Ontology Language (OWL), and the formal meaning of its constructs. Other test cases illustrate the resolution of issues considered by the Working Group. Conformance for OWL documents and OWL document checkers is specified.

Date

14. 8.2011 13:33:22

Theme

Semantic Web

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Abstract

More and more cultural heritage institutions publish their collections, vocabularies and metadata on the Web. The resulting Web of linked cultural data opens up exciting new possibilities for searching and browsing through these cultural heritage collections. We report on ongoing work in which we investigate the estimation of relevance in this Web of Culture. We study existing measures of semantic distance and how they apply to two use cases. The use cases relate to the structured, multilingual and multimodal nature of the Culture Web. We distinguish between measures using the Web, such as Google distance and PMI, and measures using the Linked Data Web, i.e. the semantic structure of metadata vocabularies. We perform a small study in which we compare these semantic distance measures to human judgements of relevance. Although it is too early to draw any definitive conclusions, the study provides new insights into the applicability of semantic distance measures to the Web of Culture, and clear starting points for further research.

Date

26.12.2011 13:40:22

Theme

Semantic Web

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Abstract

This document describes in brief how to express the content and structure of a classification scheme, and metadata about a classification scheme, in RDF using the SKOS vocabulary. RDF allows data to be linked to and/or merged with other RDF data by semantic web applications. The Semantic Web, which is based on the Resource Description Framework (RDF), provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. Publishing classifications schemes in SKOS will unify the great many of existing classification efforts in the framework of the Semantic Web.

Theme

Klassifikationssysteme im Online-Retrieval

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Date

11. 2.2011 18:22:25

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

SKOS (Simple Knowledge Organisation System) provides a model for expressing the basic structure and content of concept schemes such as thesauri, classification schemes, subject heading lists, taxonomies, folksonomies, and other types of controlled vocabulary. As an application of the Resource Description Framework (RDF) SKOS allows concepts to be documented, linked and merged with other data, while still being composed, integrated and published on the World Wide Web. This document is an implementors guide for those who would like to represent their concept scheme using SKOS. In basic SKOS, conceptual resources (concepts) can be identified using URIs, labelled with strings in one or more natural languages, documented with various types of notes, semantically related to each other in informal hierarchies and association networks, and aggregated into distinct concept schemes. In advanced SKOS, conceptual resources can be mapped to conceptual resources in other schemes and grouped into labelled or ordered collections. Concept labels can also be related to each other. Finally, the SKOS vocabulary itself can be extended to suit the needs of particular communities of practice.

Theme

Semantic Web

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Abstract

Semantic Search has become an active research of Semantic Web in recent years. The classification methodology plays a pretty critical role in the beginning of search process to disambiguate irrelevant information. However, the applications related to Folksonomy suffer from many obstacles. This study attempts to eliminate the problems resulted from Folksonomy using existing semantic technology. We also focus on how to effectively integrate heterogeneous ontologies over the Internet to acquire the integrity of domain knowledge. A faceted logic layer is abstracted in order to strengthen category framework and organize existing available ontologies according to a series of steps based on the methodology of faceted classification and ontology construction. The result showed that our approach can facilitate the integration of inconsistent or even heterogeneous ontologies. This paper also generalizes the principles of picking appropriate facets with which our facet browser completely complies so that better semantic search result can be obtained.

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

Ontologies have proven to be an essential element in many applications. They are used in agent systems, knowledge management systems, and e-commerce platforms. They can also generate natural language, integrate intelligent information, provide semantic-based access to the Internet, and extract information from texts in addition to being used in many other applications to explicitly declare the knowledge embedded in them. However, not only are ontologies useful for applications in which knowledge plays a key role, but they can also trigger a major change in current Web contents. This change is leading to the third generation of the Web-known as the Semantic Web-which has been defined as "the conceptual structuring of the Web in an explicit machine-readable way."1 This definition does not differ too much from the one used for defining an ontology: "An ontology is an explicit, machinereadable specification of a shared conceptualization."2 In fact, new ontology-based applications and knowledge architectures are developing for this new Web. A common claim for all of these approaches is the need for languages to represent the semantic information that this Web requires-solving the heterogeneous data exchange in this heterogeneous environment. Here, we don't decide which language is best of the Semantic Web. Rather, our goal is to help developers find the most suitable language for their representation needs. The authors analyze the most representative ontology languages created for the Web and compare them using a common framework.

Theme

Semantic Web

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Abstract

Starting from an unsolved problem of information retrieval this paper presents an ontology-based model for indexing and retrieval. The model combines the methods and experiences of cognitive-to-interpret indexing languages with the strengths and possibilities of formal knowledge representation. The core component of the model uses inferences along the paths of typed relations between the entities of a knowledge representation for enabling the determination of hit quantities in the context of retrieval processes. The entities are arranged in aspect-oriented facets to ensure a consistent hierarchical structure. The possible consequences for indexing and retrieval are discussed.

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Abstract

The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents. This document serves as an introduction to OWL 2 and the various other OWL 2 documents. It describes the syntaxes for OWL 2, the different kinds of semantics, the available profiles (sub-languages), and the relationship between OWL 1 and OWL 2.

Theme

Semantic Web

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Abstract

Intuition suggests that one way to enhance the information retrieval process would be the use of phrases to characterize the contents of text. A number of researchers, however, have noted that phrases alone do not improve retrieval effectiveness. In this paper we briefly review the use of phrases in information retrieval and then suggest extensions to this paradigm using semantic information. We claim that semantic processing, which can be viewed as expressing relations between the concepts represented by phrases, will in fact enhance retrieval effectiveness. The availability of the UMLS® domain model, which we exploit extensively, significantly contributes to the feasibility of this processing.

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Abstract

This paper evaluates the use of an explicit domain ontology in an information retrieval tool. The evaluation compares the performance of ontology-enhanced retrieval with keyword retrieval for a fixed set of queries across several data sets. The robustness of the IR approach is assessed by comparing the performance of the tool on the original data set with that on previously unseen data.