Search (93 results, page 1 of 5)

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Abstract

The Web has become the world's largest database, with search being the main tool that allows organizations and individuals to exploit its huge amount of information. Search on the Web has been traditionally based on textual and structural similarities, ignoring to a large degree the semantic dimension, i.e., understanding the meaning of the query and of the document content. Combining search and semantics gives birth to the idea of semantic search. Traditional search engines have already advertised some semantic dimensions. Some of them, for instance, can enhance their generated result sets with documents that are semantically related to the query terms even though they may not include these terms. Nevertheless, the exploitation of the semantic search has not yet reached its full potential. In this book, Roberto De Virgilio, Francesco Guerra and Yannis Velegrakis present an extensive overview of the work done in Semantic Search and other related areas. They explore different technologies and solutions in depth, making their collection a valuable and stimulating reading for both academic and industrial researchers. The book is divided into three parts. The first introduces the readers to the basic notions of the Web of Data. It describes the different kinds of data that exist, their topology, and their storing and indexing techniques. The second part is dedicated to Web Search. It presents different types of search, like the exploratory or the path-oriented, alongside methods for their efficient and effective implementation. Other related topics included in this part are the use of uncertainty in query answering, the exploitation of ontologies, and the use of semantics in mashup design and operation. The focus of the third part is on linked data, and more specifically, on applying ideas originating in recommender systems on linked data management, and on techniques for the efficiently querying answering on linked data.

Content

Inhalt: Introduction.- Part I Introduction to Web of Data.- Topology of the Web of Data.- Storing and Indexing Massive RDF Data Sets.- Designing Exploratory Search Applications upon Web Data Sources.- Part II Search over the Web.- Path-oriented Keyword Search query over RDF.- Interactive Query Construction for Keyword Search on the SemanticWeb.- Understanding the Semantics of Keyword Queries on Relational DataWithout Accessing the Instance.- Keyword-Based Search over Semantic Data.- Semantic Link Discovery over Relational Data.- Embracing Uncertainty in Entity Linking.- The Return of the Entity-Relationship Model: Ontological Query Answering.- Linked Data Services and Semantics-enabled Mashup.- Part III Linked Data Search engines.- A Recommender System for Linked Data.- Flint: from Web Pages to Probabilistic Semantic Data.- Searching and Browsing Linked Data with SWSE.

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Abstract

As an important support tool in science research, specialized information systems are rapidly changing their character. The potential for improvement compared with today's usual systems is enormous. This fact will be demonstrated by means of two problem complexes: - WWW search engines, which were developed without any government grants, are increasingly dominating the scene. Does the WWW displace information centers with their high quality databases? What are the results we can get nowadays using general WWW search engines? - In addition to the WWW and specialized databases, scientists now use WWW library catalogues of digital libraries, which combine the catalogues from an entire region or a country. At the same time, however, they are faced with highly decentralized heterogeneous databases which contain the widest range of textual sources and data, e.g. from surveys. One consequence is the presence of serious inconsistencies in quality, relevance and content analysis. Thus, the main problem to be solved is as follows: users must be supplied with heterogeneous data from different sources, modalities and content development processes via a visual user interface without inconsistencies in content development, for example, seriously impairing the quality of the search results, e. g. when phrasing their search inquiry in the terminology to which they are accustomed

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Abstract

The middle of the 1990s are coined by the increased enthusiasm for the possibilities of the WWW, which has only recently deviated - at least in relation to scientific information - for the differentiated measuring of its advantages and disadvantages. Web Information Retrieval originated as a specialized discipline with great commercial significance (for an overview see Lewandowski 2005). Besides the new technological structure that enables the indexing and searching (in seconds) of unimaginable amounts of data worldwide, new assessment processes for the ranking of search results are being developed, which use the link structures of the Web. They are the main innovation with respect to the traditional "mother discipline" of Information Retrieval. From the beginning, link structures of Web pages are applied to commercial search engines in a wide array of variations. From the perspective of scientific information, link topology based approaches were in essence trying to solve a self-created problem: on the one hand, it quickly became clear that the openness of the Web led to an up-tonow unknown increase in available information, but this also caused the quality of the Web pages searched to become a problem - and with it the relevance of the results. The gatekeeper function of traditional information providers, which narrows down every user query to focus on high-quality sources was lacking. Therefore, the recognition of the "authoritativeness" of the Web pages by general search engines such as Google was one of the most important factors for their success.

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Source

Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou

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Abstract

After the launch of the World Wide Web, it became clear that searching documentson the Web would not be trivial. Well-known engines to search the web, like Google, focus on search in web documents using keywords. The documents are structured and indexed to ensure keywords match documents as accurately as possible. However, searching by keywords does not always suice. It is oen the case that users do not know exactly how to formulate the search query or which keywords guarantee retrieving the most relevant documents. Besides that, it occurs that users rather want to browse information than looking up something specific. It turned out that there is need for systems that enable more interactivity and facilitate the gradual refinement of search queries to explore the Web. Users expect more from the Web because the short keyword-based queries they pose during search, do not suffice for all cases. On top of that, the Web is changing structurally. The Web comprises, apart from a collection of documents, more and more linked data, pieces of information structured so they can be processed by machines. The consequently applied semantics allow users to exactly indicate machines their search intentions. This is made possible by describing data following controlled vocabularies, concept lists composed by experts, published uniquely identifiable on the Web. Even so, it is still not trivial to explore data on the Web. There is a large variety of vocabularies and various data sources use different terms to identify the same concepts.
This PhD-thesis describes how to effectively explore linked data on the Web. The main focus is on scenarios where users want to discover relationships between resources rather than finding out more about something specific. Searching for a specific document or piece of information fits in the theoretical framework of information retrieval and is associated with exploratory search. Exploratory search goes beyond 'looking up something' when users are seeking more detailed understanding, further investigation or navigation of the initial search results. The ideas behind exploratory search and querying linked data merge when it comes to the way knowledge is represented and indexed by machines - how data is structured and stored for optimal searchability. Queries and information should be aligned to facilitate that searches also reveal connections between results. This implies that they take into account the same semantic entities, relevant at that moment. To realize this, we research three techniques that are evaluated one by one in an experimental set-up to assess how well they succeed in their goals. In the end, the techniques are applied to a practical use case that focuses on forming a bridge between the Web and the use of digital libraries in scientific research. Our first technique focuses on the interactive visualization of search results. Linked data resources can be brought in relation with each other at will. This leads to complex and diverse graphs structures. Our technique facilitates navigation and supports a workflow starting from a broad overview on the data and allows narrowing down until the desired level of detail to then broaden again. To validate the flow, two visualizations where implemented and presented to test-users. The users judged the usability of the visualizations, how the visualizations fit in the workflow and to which degree their features seemed useful for the exploration of linked data.
The ideas behind exploratory search and querying linked data merge when it comes to the way knowledge is represented and indexed by machines - how data is structured and stored for optimal searchability. eries and information should be aligned to facilitate that searches also reveal connections between results. This implies that they take into account the same semantic entities, relevant at that moment. To realize this, we research three techniques that are evaluated one by one in an experimental set-up to assess how well they succeed in their goals. In the end, the techniques are applied to a practical use case that focuses on forming a bridge between the Web and the use of digital libraries in scientific research.
Our first technique focuses on the interactive visualization of search results. Linked data resources can be brought in relation with each other at will. This leads to complex and diverse graphs structures. Our technique facilitates navigation and supports a workflow starting from a broad overview on the data and allows narrowing down until the desired level of detail to then broaden again. To validate the flow, two visualizations where implemented and presented to test-users. The users judged the usability of the visualizations, how the visualizations fit in the workflow and to which degree their features seemed useful for the exploration of linked data. There is a difference in the way users interact with resources, visually or textually, and how resources are represented for machines to be processed by algorithms. This difference complicates bridging the users' intents and machine executable queries. It is important to implement this 'translation' mechanism to impact the search as favorable as possible in terms of performance, complexity and accuracy. To do this, we explain a second technique, that supports such a bridging component. Our second technique is developed around three features that support the search process: looking up, relating and ranking resources. The main goal is to ensure that resources in the results are as precise and relevant as possible. During the evaluation of this technique, we did not only look at the precision of the search results but also investigated how the effectiveness of the search evolved while the user executed certain actions sequentially.
When we speak about finding relationships between resources, it is necessary to dive deeper in the structure. The graph structure of linked data where the semantics give meaning to the relationships between resources enable the execution of pathfinding algorithms. The assigned weights and heuristics are base components of such algorithms and ultimately define (the order) which resources are included in a path. These paths explain indirect connections between resources. Our third technique proposes an algorithm that optimizes the choice of resources in terms of serendipity. Some optimizations guard the consistence of candidate-paths where the coherence of consecutive connections is maximized to avoid trivial and too arbitrary paths. The implementation uses the A* algorithm, the de-facto reference when it comes to heuristically optimized minimal cost paths. The effectiveness of paths was measured based on common automatic metrics and surveys where the users could indicate their preference for paths, generated each time in a different way. Finally, all our techniques are applied to a use case about publications in digital libraries where they are aligned with information about scientific conferences and researchers. The application to this use case is a practical example because the different aspects of exploratory search come together. In fact, the techniques also evolved from the experiences when implementing the use case. Practical details about the semantic model are explained and the implementation of the search system is clarified module by module. The evaluation positions the result, a prototype of a tool to explore scientific publications, researchers and conferences next to some important alternatives.

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Abstract

The paper reports about results on the GESIS-IZ project "Competence Center Modeling and Treatment of Semantic Heterogeneity" (KoMoHe). KoMoHe supervised a terminology mapping effort, in which 'cross-concordances' between major controlled vocabularies were organized, created and managed. In this paper we describe the establishment and implementation of crossconcordances for search in a digital library (DL).

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

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].

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Abstract

In this era of the Internet and distributed, multimedia computing, new and emerging classes of information systems applications have swept into the lives of office workers and people in general. From digital libraries, multimedia systems, geographic information systems, and collaborative computing to electronic commerce, virtual reality, and electronic video arts and games, these applications have created tremendous opportunities for information and computer science researchers and practitioners. As applications become more pervasive, pressing, and diverse, several well-known information retrieval (IR) problems have become even more urgent. Information overload, a result of the ease of information creation and transmission via the Internet and WWW, has become more troublesome (e.g., even stockbrokers and elementary school students, heavily exposed to various WWW search engines, are versed in such IR terminology as recall and precision). Significant variations in database formats and structures, the richness of information media (text, audio, and video), and an abundance of multilingual information content also have created severe information interoperability problems -- structural interoperability, media interoperability, and multilingual interoperability.

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Abstract

The purpose of this paper is to examine the current state of Linked Data (LD) in archival moving image description, and propose ways in which current metadata records can be enriched and enhanced by interlinking such metadata with relevant information found in other data sets. Design/methodology/approach Several possible metadata models for moving image production and archiving are considered, including models from records management, digital curation, and the recent BIBFRAME AV Modeling Study. This research also explores how mappings between archival moving image records and relevant external data sources might be drawn, and what gaps exist between current vocabularies and what is needed to record and make accessible the full lifecycle of archiving through production, use, and reuse. Findings The author notes several major impediments to implementation of LD for archival moving images. The various pieces of information about creators, places, and events found in moving image records are not easily connected to relevant information in other sources because they are often not semantically defined within the record and can be hidden in unstructured fields. Libraries, archives, and museums must work on aligning the various vocabularies and schemas of potential value for archival moving image description to enable interlinking between vocabularies currently in use and those which are used by external data sets. Alignment of vocabularies is often complicated by mismatches in granularity between vocabularies. Research limitations/implications The focus is on how these models inform functional requirements for access and other archival activities, and how the field might benefit from having a common metadata model for critical archival descriptive activities. Practical implications By having a shared model, archivists may more easily align current vocabularies and develop new vocabularies and schemas to address the needs of moving image data creators and scholars. Originality/value Moving image archives, like other cultural institutions with significant heritage holdings, can benefit tremendously from investing in the semantic definition of information found in their information databases. While commercial entities such as search engines and data providers have already embraced the opportunities that semantic search provides for resource discovery, most non-commercial entities are just beginning to do so. Thus, this research addresses the benefits and challenges of enriching and enhancing archival moving image records with semantically defined information via LD.

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Abstract

The CACAO Project (Cross-language Access to Catalogues and Online Libraries) has been designed to implement natural language processing and cross-language information retrieval techniques to provide cross-language access to information in libraries, a critical issue in the linguistically diverse European Union. This project report addresses two metadata-related challenges for the library community in this context: "false friends" (identical words having different meanings in different languages) and term ambiguity. The possible solutions involve enriching the metadata with attributes specifying language or the source authority file, or associating potential search terms to classes in a classification system. The European Library will evaluate an early implementation of this work in late 2008.

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

Terminology registries (TRs) are a crucial element of the infrastructure required for resource discovery services, digital libraries, Linked Data, and semantic interoperability generally. They can make the content of knowledge organization systems (KOS) available both for human and machine access. The paper describes the attributes and functionality for a TR, based on a review of published literature, existing TRs, and a survey of experts. A domain model based on user tasks is constructed and a set of core metadata elements for use in TRs is proposed. Ideally, the TR should allow searching as well as browsing for a KOS, matching a user's search while also providing information about existing terminology services, accessible to both humans and machines. The issues surrounding metadata for KOS are also discussed, together with the rationale for different aspects and the importance of a core set of KOS metadata for future machine-based access; a possible core set of metadata elements is proposed. This is dealt with in terms of practical experience and in relation to the Dublin Core Application Profile.

Date

22. 8.2014 17:12:54

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Abstract

To make better use of knowledge organization systems (KOS) for query expansion, we have developed a pattern-based technique for composition ontology mapping in a specific domain. The technique was tested in a two-step mapping. The user's free-text queries were first mapped to Getty's Art & Architecture Thesaurus (AAT) terms. The AAT-based queries were then mapped to a search engine's indexing vocabulary (ARTstor terms). The result indicated that our technique has improved the mapping success rate from 40% to 70%. We discuss also how the technique may be applied to other KOS mapping and how it may be implemented in practical systems.

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

The focus of this paper is the provision of terminology- and classification-based terminologies interoperability data via web services, initially using interoperability data based on the use of a Dewey Decimal Classification (DDC) spine, but with an aim to explore other possibilities in time, including the use of other spines. The High-Level Thesaurus Project (HILT) Phase IV developed pilot web services based on SRW/U, SOAP, and SKOS to deliver machine-readable terminology and crossterminology mappings data likely to be useful to information services wishing to enhance their subject search or browse services. It also developed an associated toolkit to help information services technical staff to embed HILT-related functionality within service interfaces. Several UK information services have created illustrative user interface enhancements using HILT functionality and these will demonstrate what is possible. HILT currently has the following subject schemes mounted and available: DDC, CAB, GCMD, HASSET, IPSV, LCSH, MeSH, NMR, SCAS, UNESCO, and AAT. It also has high level mappings between some of these schemes and DDC and some deeper pilot mappings available.

Date

6. 1.2011 19:22:48

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Content

Winfried Gödert: Programmatic Issues and Introduction - Dagobert Soergel: Conceptual Foundations for Semantic Mapping and Semantic Search - Jan-Helge Jacobs, Tina Mengel, Katrin Müller: Insights and Outlooks: A Retrospective View on the CrissCross Project - Yvonne Jahns, Helga Karg: Translingual Retrieval: Moving between Vocabularies - MACS 2010 - Jessica Hubrich: Intersystem Relations: Characteristics and Functionalities - Stella G Dextre Clarke: In Pursuit of Interoperability: Can We Standardize Mapping Types? - Philipp Mayr, Philipp Schaer, Peter Mutschke: A Science Model Driven Retrieval Prototype - Claudia Effenberger, Julia Hauser: Would an Explicit Versioning of the DDC Bring Advantages for Retrieval? - Gordon Dunsire: Interoperability and Semantics in RDF Representations of FRBR, FRAD and FRSAD - Maja Zumer: FRSAD: Challenges of Modeling the Aboutness - Michael Panzer: Two Tales of a Concept: Aligning FRSAD with SKOS - Felix Boteram: Integrating Semantic Interoperability into FRSAD

Date

22. 2.2013 11:34:18

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Content

Vgl.: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5386707&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D5386707.

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Abstract

Most online library catalogues are not well equipped for subject search. On the one hand it is difficult to navigate the structures of the thesauri and classification systems used for indexing. Further, there is little or no support for the integration of crosswalks between different controlled vocabularies, so that a subject search query formulated using one controlled vocabulary will not find resources indexed with another knowledge organisation system even if there exists a crosswalk between them. In this paper we will look at SemanticWeb technologies and a prototype system leveraging those technologies in order to enhance the subject search possibilities in heterogeneously indexed repositories. Finally, we will have a brief look at different initiatives aimed at integrating library data into the SemanticWeb.

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Abstract

This paper is aimed at assessing the potential of interoperable knowledge organization systems to respond to search strategies in order to retrieve information from databases in the areas of health and biomedicine. An analysis was done on the semantic consistency of synonym grouping of a term selected from the Metathesaurus, the Unified Medical Language System of the National Library of Medicine, based on the characteristics of equivalence proposed in ISO 25964: 2: 2011 and based on the following categories: semantic, morphological, syntactic and typographical variations. This paper highlights the importance of understanding the results of automatic mapping as well as the need for characterization, evaluation and selection of equivalences for preparation of consistent search strategies and presentation of search results in scientific work methodologies.

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Abstract

Repositories are web portals that provide access to learning objects. Resources can be easily located through the use of metadata, an important factor to increase the ease of searching for digital resources in repositories. However, there are as yet no similarly effective methods in order to increase access to learning objects. The main goal of this paper is to offer an alternative search system to improve access to academic learning objects and publications for several repositories through the use of information visualisation and Simple Knowledge Organization Schemes (SKOS). To this end, we have developed a visual framework and have used the Organic.Edunet and AGRIS as case studies in order to access academic and scientific publication resources respectively. In this paper, we present the results of our work through a test aimed at evaluating the whole visual framework, and offer recommendations on how to integrate this type of visual search into academic repositories based on SKOS.

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Abstract

Purpose - The general science portal "vascoda" merges structured, high-quality information collections from more than 40 providers on the basis of search engine technology (FAST) and a concept which treats semantic heterogeneity between different controlled vocabularies. First experiences with the portal show some weaknesses of this approach which come out in most metadata-driven Digital Libraries (DLs) or subject specific portals. The purpose of the paper is to propose models to reduce the semantic complexity in heterogeneous DLs. The aim is to introduce value-added services (treatment of term vagueness and document re-ranking) that gain a certain quality in DLs if they are combined with heterogeneity components established in the project "Competence Center Modeling and Treatment of Semantic Heterogeneity". Design/methodology/approach - Two methods, which are derived from scientometrics and network analysis, will be implemented with the objective to re-rank result sets by the following structural properties: the ranking of the results by core journals (so-called Bradfordizing) and ranking by centrality of authors in co-authorship networks. Findings - The methods, which will be implemented, focus on the query and on the result side of a search and are designed to positively influence each other. Conceptually, they will improve the search quality and guarantee that the most relevant documents in result sets will be ranked higher. Originality/value - The central impact of the paper focuses on the integration of three structural value-adding methods, which aim at reducing the semantic complexity represented in distributed DLs at several stages in the information retrieval process: query construction, search and ranking and re-ranking.

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Content

Master thesis Master of Science (Library and Information Studies) (MSc), Universität Wien. Advisor: Christoph Steiner. Vgl.: https://www.researchgate.net/publication/371680244_Vergabe_von_DDC-Sachgruppen_mittels_eines_Schlagwort-Thesaurus. DOI: 10.25365/thesis.70030. Vgl. dazu die Präsentation unter: https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=web&cd=&ved=0CAIQw7AJahcKEwjwoZzzytz_AhUAAAAAHQAAAAAQAg&url=https%3A%2F%2Fwiki.dnb.de%2Fdownload%2Fattachments%2F252121510%2FDA3%2520Workshop-Gabler.pdf%3Fversion%3D1%26modificationDate%3D1671093170000%26api%3Dv2&psig=AOvVaw0szwENK1or3HevgvIDOfjx&ust=1687719410889597&opi=89978449.