-
Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005)
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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
- Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
-
Faaborg, A.; Lagoze, C.: Semantic browsing (2003)
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- Abstract
- We have created software applications that allow users to both author and use Semantic Web metadata. To create and use a layer of semantic content on top of the existing Web, we have (1) implemented a user interface that expedites the task of attributing metadata to resources on the Web, and (2) augmented a Web browser to leverage this semantic metadata to provide relevant information and tasks to the user. This project provides a framework for annotating and reorganizing existing files, pages, and sites on the Web that is similar to Vannevar Bushrsquos original concepts of trail blazing and associative indexing.
- Source
- Research and advanced technology for digital libraries : 7th European Conference, proceedings / ECDL 2003, Trondheim, Norway, August 17-22, 2003
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Franklin, R.A.: Re-inventing subject access for the semantic web (2003)
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- Abstract
- First generation scholarly research on the Web lacked a firm system of authority control. Second generation Web research is beginning to model subject access with library science principles of bibliographic control and cataloguing. Harnessing the Web and organising the intellectual content with standards and controlled vocabulary provides precise search and retrieval capability, increasing relevance and efficient use of technology. Dublin Core metadata standards permit a full evaluation and cataloguing of Web resources appropriate to highly specific research needs and discovery. Current research points to a type of structure based on a system of faceted classification. This system allows the semantic and syntactic relationships to be defined. Controlled vocabulary, such as the Library of Congress Subject Headings, can be assigned, not in a hierarchical structure, but rather as descriptive facets of relating concepts. Web design features such as this are adding value to discovery and filtering out data that lack authority. The system design allows for scalability and extensibility, two technical features that are integral to future development of the digital library and resource discovery.
- Date
- 30.12.2008 18:22:46
-
Scheir, P.; Pammer, V.; Lindstaedt, S.N.: Information retrieval on the Semantic Web : does it exist? (2007)
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- Abstract
- Plenty of contemporary attempts to search exist that are associated with the area of Semantic Web. But which of them qualify as information retrieval for the Semantic Web? Do such approaches exist? To answer these questions we take a look at the nature of the Semantic Web and Semantic Desktop and at definitions for information and data retrieval. We survey current approaches referred to by their authors as information retrieval for the Semantic Web or that use Semantic Web technology for search.
-
Mayfield, J.; Finin, T.: Information retrieval on the Semantic Web : integrating inference and retrieval
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- Abstract
- One vision of the Semantic Web is that it will be much like the Web we know today, except that documents will be enriched by annotations in machine understandable markup. These annotations will provide metadata about the documents as well as machine interpretable statements capturing some of the meaning of document content. We discuss how the information retrieval paradigm might be recast in such an environment. We suggest that retrieval can be tightly bound to inference. Doing so makes today's Web search engines useful to Semantic Web inference engines, and causes improvements in either retrieval or inference to lead directly to improvements in the other.
- Date
- 12. 2.2011 17:35:22
-
Multimedia content and the Semantic Web : methods, standards, and tools (2005)
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- Classification
- 006.7 22
- Date
- 7. 3.2007 19:30:22
- DDC
- 006.7 22
- Footnote
- Rez. in: JASIST 58(2007) no.3, S.457-458 (A.M.A. Ahmad): "The concept of the semantic web has emerged because search engines and text-based searching are no longer adequate, as these approaches involve an extensive information retrieval process. The deployed searching and retrieving descriptors arc naturally subjective and their deployment is often restricted to the specific application domain for which the descriptors were configured. The new era of information technology imposes different kinds of requirements and challenges. Automatic extracted audiovisual features are required, as these features are more objective, domain-independent, and more native to audiovisual content. This book is a useful guide for researchers, experts, students, and practitioners; it is a very valuable reference and can lead them through their exploration and research in multimedia content and the semantic web. The book is well organized, and introduces the concept of the semantic web and multimedia content analysis to the reader through a logical sequence from standards and hypotheses through system examples, presenting relevant tools and methods. But in some chapters readers will need a good technical background to understand some of the details. Readers may attain sufficient knowledge here to start projects or research related to the book's theme; recent results and articles related to the active research area of integrating multimedia with semantic web technologies are included. This book includes full descriptions of approaches to specific problem domains such as content search, indexing, and retrieval. This book will be very useful to researchers in the multimedia content analysis field who wish to explore the benefits of emerging semantic web technologies in applying multimedia content approaches. The first part of the book covers the definition of the two basic terms multimedia content and semantic web. The Moving Picture Experts Group standards MPEG7 and MPEG21 are quoted extensively. In addition, the means of multimedia content description are elaborated upon and schematically drawn. This extensive description is introduced by authors who are actively involved in those standards and have been participating in the work of the International Organization for Standardization (ISO)/MPEG for many years. On the other hand, this results in bias against the ad hoc or nonstandard tools for multimedia description in favor of the standard approaches. This is a general book for multimedia content; more emphasis on the general multimedia description and extraction could be provided.
Semantic web technologies are explained, and ontology representation is emphasized. There is an excellent summary of the fundamental theory behind applying a knowledge-engineering approach to vision problems. This summary represents the concept of the semantic web and multimedia content analysis. A definition of the fuzzy knowledge representation that can be used for realization in multimedia content applications has been provided, with a comprehensive analysis. The second part of the book introduces the multimedia content analysis approaches and applications. In addition, some examples of methods applicable to multimedia content analysis are presented. Multimedia content analysis is a very diverse field and concerns many other research fields at the same time; this creates strong diversity issues, as everything from low-level features (e.g., colors, DCT coefficients, motion vectors, etc.) up to the very high and semantic level (e.g., Object, Events, Tracks, etc.) are involved. The second part includes topics on structure identification (e.g., shot detection for video sequences), and object-based video indexing. These conventional analysis methods are supplemented by results on semantic multimedia analysis, including three detailed chapters on the development and use of knowledge models for automatic multimedia analysis. Starting from object-based indexing and continuing with machine learning, these three chapters are very logically organized. Because of the diversity of this research field, including several chapters of recent research results is not sufficient to cover the state of the art of multimedia. The editors of the book should write an introductory chapter about multimedia content analysis approaches, basic problems, and technical issues and challenges, and try to survey the state of the art of the field and thus introduce the field to the reader.
The final part of the book discusses research in multimedia content management systems and the semantic web, and presents examples and applications for semantic multimedia analysis in search and retrieval systems. These chapters describe example systems in which current projects have been implemented, and include extensive results and real demonstrations. For example, real case scenarios such as ECommerce medical applications and Web services have been introduced. Topics in natural language, speech and image processing techniques and their application for multimedia indexing, and content-based retrieval have been elaborated upon with extensive examples and deployment methods. The editors of the book themselves provide the readers with a chapter about their latest research results on knowledge-based multimedia content indexing and retrieval. Some interesting applications for multimedia content and the semantic web are introduced. Applications that have taken advantage of the metadata provided by MPEG7 in order to realize advance-access services for multimedia content have been provided. The applications discussed in the third part of the book provide useful guidance to researchers and practitioners properly planning to implement semantic multimedia analysis techniques in new research and development projects in both academia and industry. A fourth part should be added to this book: performance measurements for integrated approaches of multimedia analysis and the semantic web. Performance of the semantic approach is a very sophisticated issue and requires extensive elaboration and effort. Measuring the semantic search is an ongoing research area; several chapters concerning performance measurement and analysis would be required to adequately cover this area and introduce it to readers."
- LCSH
- Information storage and retrieval systems
- RSWK
- Semantic Web / Multimedia / Automatische Indexierung / Information Retrieval
- Subject
- Semantic Web / Multimedia / Automatische Indexierung / Information Retrieval
Information storage and retrieval systems
-
Subirats, I.; Prasad, A.R.D.; Keizer, J.; Bagdanov, A.: Implementation of rich metadata formats and demantic tools using DSpace (2008)
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- Abstract
- This poster explores the customization of DSpace to allow the use of the AGRIS Application Profile metadata standard and the AGROVOC thesaurus. The objective is the adaptation of DSpace, through the least invasive code changes either in the form of plug-ins or add-ons, to the specific needs of the Agricultural Sciences and Technology community. Metadata standards such as AGRIS AP, and Knowledge Organization Systems such as the AGROVOC thesaurus, provide mechanisms for sharing information in a standardized manner by recommending the use of common semantics and interoperable syntax (Subirats et al., 2007). AGRIS AP was created to enhance the description, exchange and subsequent retrieval of agricultural Document-like Information Objects (DLIOs). It is a metadata schema which draws from Metadata standards such as Dublin Core (DC), the Australian Government Locator Service Metadata (AGLS) and the Agricultural Metadata Element Set (AgMES) namespaces. It allows sharing of information across dispersed bibliographic systems (FAO, 2005). AGROVOC68 is a multilingual structured thesaurus covering agricultural and related domains. Its main role is to standardize the indexing process in order to make searching simpler and more efficient. AGROVOC is developed by FAO (Lauser et al., 2006). The customization of the DSpace is taking place in several phases. First, the AGRIS AP metadata schema was mapped onto the metadata DSpace model, with several enhancements implemented to support AGRIS AP elements. Next, AGROVOC will be integrated as a controlled vocabulary accessed through a local SKOS or OWL file. Eventually the system will be configurable to access AGROVOC through local files or remotely via webservices. Finally, spell checking and tooltips will be incorporated in the user interface to support metadata editing. Adapting DSpace to support AGRIS AP and annotation using the semantically-rich AGROVOC thesaurus transform DSpace into a powerful, domain-specific system for annotation and exchange of bibliographic metadata in the agricultural domain.
- 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
-
Krause, J.: Shell Model, Semantic Web and Web Information Retrieval (2006)
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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.
-
Hollink, L.; Assem, M. van: Estimating the relevance of search results in the Culture-Web : a study of semantic distance measures (2010)
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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
-
Ding, L.; Finin, T.; Joshi, A.; Peng, Y.; Cost, R.S.; Sachs, J.; Pan, R.; Reddivari, P.; Doshi, V.: Swoogle : a Semantic Web search and metadata engine (2004)
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- Abstract
- Swoogle is a crawler-based indexing and retrieval system for the Semantic Web, i.e., for Web documents in RDF or OWL. It extracts metadata for each discovered document, and computes relations between documents. Discovered documents are also indexed by an information retrieval system which can use either character N-Gram or URIrefs as keywords to find relevant documents and to compute the similarity among a set of documents. One of the interesting properties we compute is rank, a measure of the importance of a Semantic Web document.
- Source
- CIKM '04 Proceedings of the thirteenth ACM international conference on Information and knowledge management
-
Heflin, J.; Hendler, J.: Semantic interoperability on the Web (2000)
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- Abstract
- XML will have a profound impact on the way data is exchanged on the Internet. An important feature of this language is the separation of content from presentation, which makes it easier to select and/or reformat the data. However, due to the likelihood of numerous industry and domain specific DTDs, those who wish to integrate information will still be faced with the problem of semantic interoperability. In this paper we discuss why this problem is not solved by XML, and then discuss why the Resource Description Framework is only a partial solution. We then present the SHOE language, which we feel has many of the features necessary to enable a semantic web, and describe an existing set of tools that make it easy to use the language.
- Date
- 11. 5.2013 19:22:18
-
Brunetti, J.M.; Roberto García, R.: User-centered design and evaluation of overview components for semantic data exploration (2014)
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- Abstract
- Purpose - The growing volumes of semantic data available in the web result in the need for handling the information overload phenomenon. The potential of this amount of data is enormous but in most cases it is very difficult for users to visualize, explore and use this data, especially for lay-users without experience with Semantic Web technologies. The paper aims to discuss these issues. Design/methodology/approach - The Visual Information-Seeking Mantra "Overview first, zoom and filter, then details-on-demand" proposed by Shneiderman describes how data should be presented in different stages to achieve an effective exploration. The overview is the first user task when dealing with a data set. The objective is that the user is capable of getting an idea about the overall structure of the data set. Different information architecture (IA) components supporting the overview tasks have been developed, so they are automatically generated from semantic data, and evaluated with end-users. Findings - The chosen IA components are well known to web users, as they are present in most web pages: navigation bars, site maps and site indexes. The authors complement them with Treemaps, a visualization technique for displaying hierarchical data. These components have been developed following an iterative User-Centered Design methodology. Evaluations with end-users have shown that they get easily used to them despite the fact that they are generated automatically from structured data, without requiring knowledge about the underlying semantic technologies, and that the different overview components complement each other as they focus on different information search needs. Originality/value - Obtaining semantic data sets overviews cannot be easily done with the current semantic web browsers. Overviews become difficult to achieve with large heterogeneous data sets, which is typical in the Semantic Web, because traditional IA techniques do not easily scale to large data sets. There is little or no support to obtain overview information quickly and easily at the beginning of the exploration of a new data set. This can be a serious limitation when exploring a data set for the first time, especially for lay-users. The proposal is to reuse and adapt existing IA components to provide this overview to users and show that they can be generated automatically from the thesaurus and ontologies that structure semantic data while providing a comparable user experience to traditional web sites.
- Date
- 20. 1.2015 18:30:22
- Source
- Aslib journal of information management. 66(2014) no.5, S.519-536
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Davies, J.; Weeks, R.; Krohn, U.: QuizRDF: search technology for the Semantic Web (2004)
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- Abstract
- Important information is often scattered across Web and/or intranet resources. Traditional search engines return ranked retrieval lists that offer little or no information on the semantic relationships among documents. Knowledge workers spend a substantial amount of their time browsing and reading to find out how documents are related to one another and where each falls into the overall structure of the problem domain. Yet only when knowledge workers begin to locate the similarities and differences among pieces of information do they move into an essential part of their work: building relationships to create new knowledge. Information retrieval traditionally focuses on the relationship between a given query (or user profile) and the information store. On the other hand, exploitation of interrelationships between selected pieces of information (which can be facilitated by the use of ontologies) can put otherwise isolated information into a meaningful context. The implicit structures so revealed help users use and manage information more efficiently. Knowledge management tools are needed that integrate the resources dispersed across Web resources into a coherent corpus of interrelated information. Previous research in information integration has largely focused on integrating heterogeneous databases and knowledge bases, which represent information in a highly structured way, often by means of formal languages. In contrast, the Web consists to a large extent of unstructured or semi-structured natural language texts. As we have seen, ontologies offer an alternative way to cope with heterogeneous representations of Web resources. The domain model implicit in an ontology can be taken as a unifying structure for giving information a common representation and semantics. Once such a unifying structure exists, it can be exploited to improve browsing and retrieval performance in information access tools. QuizRDF is an example of such a tool.
-
Miles, A.: SKOS: requirements for standardization (2006)
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- Abstract
- This paper poses three questions regarding the planned development of the Simple Knowledge Organisation System (SKOS) towards W3C Recommendation status. Firstly, what is the fundamental purpose and therefore scope of SKOS? Secondly, which key software components depend on SKOS, and how do they interact? Thirdly, what is the wider technological and social context in which SKOS is likely to be applied and how might this influence design goals? Some tentative conclusions are drawn and in particular it is suggested that the scope of SKOS be restricted to the formal representation of controlled structured vocabularies intended for use within retrieval applications. However, the main purpose of this paper is to articulate the assumptions that have motivated the design of SKOS, so that these may be reviewed prior to a rigorous standardization initiative.
- Footnote
- Presented at the International Conference on Dublin Core and Metadata Applications in October 2006
-
Smith, D.A.; Shadbolt, N.R.: FacetOntology : expressive descriptions of facets in the Semantic Web (2012)
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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
-
Heery, R.; Wagner, H.: ¬A metadata registry for the Semantic Web (2002)
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- Abstract
- The Semantic Web activity is a W3C project whose goal is to enable a 'cooperative' Web where machines and humans can exchange electronic content that has clear-cut, unambiguous meaning. This vision is based on the automated sharing of metadata terms across Web applications. The declaration of schemas in metadata registries advance this vision by providing a common approach for the discovery, understanding, and exchange of semantics. However, many of the issues regarding registries are not clear, and ideas vary regarding their scope and purpose. Additionally, registry issues are often difficult to describe and comprehend without a working example. This article will explore the role of metadata registries and will describe three prototypes, written by the Dublin Core Metadata Initiative. The article will outline how the prototypes are being used to demonstrate and evaluate application scope, functional requirements, and technology solutions for metadata registries. Metadata schema registries are, in effect, databases of schemas that can trace an historical line back to shared data dictionaries and the registration process encouraged by the ISO/IEC 11179 community. New impetus for the development of registries has come with the development activities surrounding creation of the Semantic Web. The motivation for establishing registries arises from domain and standardization communities, and from the knowledge management community. Examples of current registry activity include:
* Agencies maintaining directories of data elements in a domain area in accordance with ISO/IEC 11179 (This standard specifies good practice for data element definition as well as the registration process. Example implementations are the National Health Information Knowledgebase hosted by the Australian Institute of Health and Welfare and the Environmental Data Registry hosted by the US Environmental Protection Agency.); * The xml.org directory of the Extended Markup Language (XML) document specifications facilitating re-use of Document Type Definition (DTD), hosted by the Organization for the Advancement of Structured Information Standards (OASIS); * The MetaForm database of Dublin Core usage and mappings maintained at the State and University Library in Goettingen; * The Semantic Web Agreement Group Dictionary, a database of terms for the Semantic Web that can be referred to by humans and software agents; * LEXML, a multi-lingual and multi-jurisdictional RDF Dictionary for the legal world; * The SCHEMAS registry maintained by the European Commission funded SCHEMAS project, which indexes several metadata element sets as well as a large number of activity reports describing metadata related activities and initiatives. Metadata registries essentially provide an index of terms. Given the distributed nature of the Web, there are a number of ways this can be accomplished. For example, the registry could link to terms and definitions in schemas published by implementers and stored locally by the schema maintainer. Alternatively, the registry might harvest various metadata schemas from their maintainers. Registries provide 'added value' to users by indexing schemas relevant to a particular 'domain' or 'community of use' and by simplifying the navigation of terms by enabling multiple schemas to be accessed from one view. An important benefit of this approach is an increase in the reuse of existing terms, rather than users having to reinvent them. Merging schemas to one view leads to harmonization between applications and helps avoid duplication of effort. Additionally, the establishment of registries to index terms actively being used in local implementations facilitates the metadata standards activity by providing implementation experience transferable to the standards-making process.
-
Semantic search over the Web (2012)
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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.
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Semantic applications (2018)
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- Abstract
- This book describes proven methodologies for developing semantic applications: software applications which explicitly or implicitly uses the semantics (i.e., the meaning) of a domain terminology in order to improve usability, correctness, and completeness. An example is semantic search, where synonyms and related terms are used for enriching the results of a simple text-based search. Ontologies, thesauri or controlled vocabularies are the centerpiece of semantic applications. The book includes technological and architectural best practices for corporate use.
- 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
- Information storage and retrieval
Management of Computing and Information Systems
Information Storage and Retrieval
- RSWK
- Information Retrieval
- Series
- methodology, technology, corporate use
- Subject
- Information Retrieval
Information storage and retrieval
Management of Computing and Information Systems
Information Storage and Retrieval
-
Bergamaschi, S.; Domnori, E.; Guerra, F.; Rota, S.; Lado, R.T.; Velegrakis, Y.: Understanding the semantics of keyword queries on relational data without accessing the instance (2012)
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- Abstract
- The birth of the Web has brought an exponential growth to the amount of the information that is freely available to the Internet population, overloading users and entangling their efforts to satisfy their information needs. Web search engines such Google, Yahoo, or Bing have become popular mainly due to the fact that they offer an easy-to-use query interface (i.e., based on keywords) and an effective and efficient query execution mechanism. The majority of these search engines do not consider information stored on the deep or hidden Web [9,28], despite the fact that the size of the deep Web is estimated to be much bigger than the surface Web [9,47]. There have been a number of systems that record interactions with the deep Web sources or automatically submit queries them (mainly through their Web form interfaces) in order to index their context. Unfortunately, this technique is only partially indexing the data instance. Moreover, it is not possible to take advantage of the query capabilities of data sources, for example, of the relational query features, because their interface is often restricted from the Web form. Besides, Web search engines focus on retrieving documents and not on querying structured sources, so they are unable to access information based on concepts.
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Fernández, M.; Cantador, I.; López, V.; Vallet, D.; Castells, P.; Motta, E.: Semantically enhanced Information Retrieval : an ontology-based approach (2011)
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- Abstract
- Currently, techniques for content description and query processing in Information Retrieval (IR) are based on keywords, and therefore provide limited capabilities to capture the conceptualizations associated with user needs and contents. Aiming to solve the limitations of keyword-based models, the idea of conceptual search, understood as searching by meanings rather than literal strings, has been the focus of a wide body of research in the IR field. More recently, it has been used as a prototypical scenario (or even envisioned as a potential "killer app") in the Semantic Web (SW) vision, since its emergence in the late nineties. However, current approaches to semantic search developed in the SW area have not yet taken full advantage of the acquired knowledge, accumulated experience, and technological sophistication achieved through several decades of work in the IR field. Starting from this position, this work investigates the definition of an ontology-based IR model, oriented to the exploitation of domain Knowledge Bases to support semantic search capabilities in large document repositories, stressing on the one hand the use of fully fledged ontologies in the semantic-based perspective, and on the other hand the consideration of unstructured content as the target search space. The major contribution of this work is an innovative, comprehensive semantic search model, which extends the classic IR model, addresses the challenges of the massive and heterogeneous Web environment, and integrates the benefits of both keyword and semantic-based search. Additional contributions include: an innovative rank fusion technique that minimizes the undesired effects of knowledge sparseness on the yet juvenile SW, and the creation of a large-scale evaluation benchmark, based on TREC IR evaluation standards, which allows a rigorous comparison between IR and SW approaches. Conducted experiments show that our semantic search model obtained comparable and better performance results (in terms of MAP and P@10 values) than the best TREC automatic system.
- Series
- JWS special issue on Semantic Search
- Source
- Web semantics: science, services and agents on the World Wide Web. 9(2011) no.4, S.434-452
