Search (85 results, page 2 of 5)

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Date

1. 2.2016 18:25:22

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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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Source

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

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Date

22. 7.2006 17:56:22

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Abstract

Search is the preferred method to access information in today's computing systems. The Web, accessed through search engines, is universally recognized as the source for answering users' information needs. However, offering a link to a Web page does not cover all information needs. Even simple problems, such as "Which theater offers an at least three-stars action movie in London close to a good Italian restaurant," can only be solved by searching the Web multiple times, e.g., by extracting a list of the recent action movies filtered by ranking, then looking for movie theaters, then looking for Italian restaurants close to them. While search engines hint to useful information, the user's brain is the fundamental platform for information integration. An important trend is the availability of new, specialized data sources-the so-called "long tail" of the Web of data. Such carefully collected and curated data sources can be much more valuable than information currently available in Web pages; however, many sources remain hidden or insulated, in the lack of software solutions for bringing them to surface and making them usable in the search context. A new class of tailor-made systems, designed to satisfy the needs of users with specific aims, will support the publishing and integration of data sources for vertical domains; the user will be able to select sources based on individual or collective trust, and systems will be able to route queries to such sources and to provide easyto-use interfaces for combining them within search strategies, at the same time, rewarding the data source owners for each contribution to effective search. Efforts such as Google's Fusion Tables show that the technology for bringing hidden data sources to surface is feasible.

Source

Semantic search over the Web. Eds.: R. De Virgilio, et al

Theme

Semantic Web

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Abstract

Purpose - The paper aims to argue that digital library retrieval should be based on semantic representations and propose a semantic infrastructure for digital libraries. Design/methodology/approach - The approach taken is formal model based on subject representation for digital libraries. Findings - Search engines and search techniques have fallen short of user expectations as they do not give context based retrieval. Deploying semantic web technologies would lead to efficient and more precise representation of digital library content and hence better retrieval. Though digital libraries often have metadata of information resources which can be accessed through OAI-PMH, much remains to be accomplished in making digital libraries semantic web compliant. This paper presents a semantic infrastructure for digital libraries, that will go a long way in providing them and web based information services with products highly customised to users needs. Research limitations/implications - Here only a model for semantic infrastructure is proposed. This model is proposed after studying current user-centric, top-down models adopted in digital library service architectures. Originality/value - This paper gives a generic model for building semantic infrastructure for digital libraries. Faceted ontologies for digital libraries is just one approach. But the same may be adopted by groups working with different approaches in building ontologies to realise efficient retrieval in digital libraries.

Footnote

Beitrag eines Themenheftes "Digital libraries and the semantic web: context, applications and research".

Theme

Semantic Web

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Abstract

Across the world, millions of users interact with search engines every day to satisfy their information needs. As the Web grows bigger over time, such information needs, manifested through user search queries, also become more complex. However, there has been no systematic study that quantifies the structural complexity of Web search queries. In this research, we make an attempt towards understanding and characterizing the syntactic complexity of search queries using a multi-pronged approach. We use traditional statistical language modeling techniques to quantify and compare the perplexity of queries with natural language (NL). We then use complex network analysis for a comparative analysis of the topological properties of queries issued by real Web users and those generated by statistical models. Finally, we conduct experiments to study whether search engine users are able to identify real queries, when presented along with model-generated ones. The three complementary studies show that the syntactic structure of Web queries is more complex than what n-grams can capture, but simpler than NL. Queries, thus, seem to represent an intermediate stage between syntactic and non-syntactic communication.

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Abstract

The ever growing popularity of the Internet as a source of information, coupled with the accompanying growth in the number of documents made available through the World Wide Web, is leading to an increasing demand for more efficient and accurate information retrieval tools. Numerous techniques have been proposed and tried for improving the effectiveness of searching the World Wide Web for documents relevant to a given topic of interest. The specification of appropriate keywords and phrases by the user is crucial for the successful execution of a query as measured by the relevance of documents retrieved. Lack of users' knowledge an the search topic and their changing information needs often make it difficult for them to find suitable keywords or phrases for a query. This results in searches that fail to cover all likely aspects of the topic of interest. We describe a scheme that attempts to remedy this situation by automatically expanding the user query through the analysis of initially retrieved documents. Experimental results to demonstrate the effectiveness of the query expansion scheure are presented.

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Abstract

The Medical professionals and researchers need information from reputable sources to accomplish their work. Unfortunately, the Web has a large number of documents that are irrelevant to their work, even those documents that purport to be "medically-related." This paper describes an architecture designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, or "concept space," and Kohonen-based Self-Organizing Map (SOM) technologies to provide searchers with finegrained results. Initial results indicate that these systems provide complementary retrieval functionalities. HelpfulMed not only allows users to search Web pages and other online databases, but also allows them to build searches through the use of an automatic thesaurus and browse a graphical display of medical-related topics. Evaluation results for each of the different components are included. Our spidering algorithm outperformed both breadth-first search and PageRank spiders an a test collection of 100,000 Web pages. The automatically generated thesaurus performed as well as both MeSH and UMLS-systems which require human mediation for currency. Lastly, a variant of the Kohonen SOM was comparable to MeSH terms in perceived cluster precision and significantly better at perceived cluster recall.

Footnote

Teil eines Themenheftes: "Web retrieval and mining: A machine learning perspective"

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Abstract

The emergence of general audience digital libraries (GADLs) defines a context that represents a hybrid of both "traditional" IR, using primarily bibliographic resources provided by database vendors, and "popular" IR, exemplified by public search systems available on the World Wide Web. Findings of a study investigating end-user searching and response to a GADL are reported. Data collected from a Web-based end-user survey and data logs of resource usage for a Web-based GADL were analyzed for user characteristics, patterns of access and use, and user feedback. Cross-tabulations using respondent demographics revealed several key differences in how the system was used and valued by users of different age groups. Older users valued the service more than younger users and engaged in different searching and viewing behaviors. The GADL more closely resembles traditional retrieval systems in terms of content and purpose of use, but is more similar to popular IR systems in terms of user behavior and accessibility. A model that defines the dual context of the GADL environment is derived from the data analysis and existing IR models in general and other specific contexts. The authors demonstrate the distinguishing characteristics of this IR context, and discuss implications for the development and evaluation of future GADLs to accommodate a variety of user needs and expectations.

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Abstract

With the advance of the semantic Web, increasing amounts of data are available in a structured and machine-understandable form. This opens opportunities for users to employ semantic queries instead of simple keyword-based ones to accurately express the information need. However, constructing semantic queries is a demanding task for human users [11]. To compose a valid semantic query, a user has to (1) master a query language (e.g., SPARQL) and (2) acquire sufficient knowledge about the ontology or the schema of the data source. While there are systems which support this task with visual tools [21, 26] or natural language interfaces [3, 13, 14, 18], the process of query construction can still be complex and time consuming. According to [24], users prefer keyword search, and struggle with the construction of semantic queries although being supported with a natural language interface. Several keyword search approaches have already been proposed to ease information seeking on semantic data [16, 32, 35] or databases [1, 31]. However, keyword queries lack the expressivity to precisely describe the user's intent. As a result, ranking can at best put query intentions of the majority on top, making it impossible to take the intentions of all users into consideration.

Source

Semantic search over the Web. Eds.: R. De Virgilio, et al

Theme

Semantic Web

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Date

30. 3.2001 13:35:22

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Abstract

Der Hersteller von Bibliothekssoftware BOND erweitert sein Produktangebot um eine innovative Neuheit, den Assoziativ-OPAC SpiderSearch. Dieser graphische Web-OPAC sucht zu einem Stichwort Assoziative, d.h. sinn- oder sprachwissenschaftlich verwandte Begriffe. Diese baut er spinnennetzartig um den zentralen Suchbegriff herum auf. Anhand der ihm angebotenen Assoziative kann sich der Leser sehr einfach und anschaulich durch den Medienbestand der Bibliothek klicken. So findet er schnell und komfortabel relevante Medien, die mit herkömmlichen Suchverfahren nur schwer recherchierbar wären. Mühsame Überlegungen über verwandte Suchbegriffe und angrenzende Themengebiete bleiben dem Benutzer erspart. Dies übernimmt SpiderSearch und navigiert den Benutzer ähnlich wie beim Surfen durch Webseiten durch sämtliche Themen, die mit dem Suchbegriff in Zusammenhang stehen. Auch aufwändiges Durchblättern einer riesigen Suchergebnisliste ist nicht nötig. Durch die im semantischen Netz vorgeschlagenen Begriffe, kann der Benutzer sein Thema genau eingrenzen und erhält in seiner Trefferliste nur passende Medien. Diese ordnet SpiderSearch nach ihrer Relevanz, so dass der Leser die benötigte Literatur einfach und komfortabel findet. Wie auch im normalen Web-OPAC enthält die Trefferliste Angaben zu Titel, Standort und Verfügbarkeit des Mediums. Zur einfachen Zuordnung der Medienart ist jedem Medium ein entsprechendes Symbol zugewiesen. Per Mausklick erhält der Benutzer Detailangaben zum Medium und optional eine Ansicht des Buchcovers. SpiderSearch ist ein Zusatzmodul zur Software BIBLIOTHECA2000 von BOND und setzt auf den Web-OPAL auf. Vor allem bei Öffentlichen Bibliotheken stößt SpiderSearch auf großes Interesse. Erste Anwender bieten Ihren Lesern bereits dieses neue Sucherlebnis.

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Content

"Der Hersteller von Bibliothekssoftware BOND erweitert sein Produktangebot um den Assoziativ-OPAC SpiderSearch. Dieser graphische Web-OPAC sucht zu einem Stichwort Assoziative, d.h. sinnoder sprachwissenschaftlich verwandte Begriffe. Diese baut er spinnennetzartig um den zentralen Suchbegriff herum auf. Anhand der ihm angebotenen Assoziative kann sich der Leser sehr einfach und anschaulich durch den Medienbestand der Bibliothek klicken. So findet er schnell und komfortabel relevante Medien, die mit herkömmlichen Suchverfahren nur schwer recherchierbar wären. Überlegungen über verwandte Suchbegriffe und angrenzende Themengebiete bleiben dem Benutzer erspart: SpiderSearch navigiert den Benutzer ähnlich wie beim Surfen durch Webseiten durch sämtliche Themen, die mit dem Suchbegriff in Zusammenhang stehen. Auch aufwändiges Durchblättern einer riesigen Suchergebnisliste ist nicht nötig. Durch die im semantischen Netz vorgeschlagenen Begriffe kann der Benutzer sein Thema genau eingrenzen und erhält in seiner Trefferliste nur passende Medien. Diese ordnet SpiderSearch nach ihrer Relevanz, so dass der Leser die benötigte Literatur einfach und komfortabel findet. Wie auch im normalen Web-OPAC enthält die Trefferliste Angaben zu Titel, Standort und Verfügbarkeit des Mediums. Zur einfachen Zuordnung der Medienart ist jedem Medium ein entsprechendes Symbol zugewiesen. Per Mausklick erhält der Benutzer Detailangaben zum Medium und optional eine Ansicht des Buchcovers. SpiderSearch ist ein Zusatzmodul zur Software BIBLIOTHECA2000 von BOND und setzt auf den Web-OPAC auf."

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Abstract

10 Jahre Internet haben die WeIt um die Bibliotheken herum stark geändert. Der Web-OPAC war eine Antwort der Bibliotheken. Doch reicht ein Web-OPAC im Zeitalter des Internets noch aus? Außer Web ist es doch der alte Katalog. Ca. 90% aller Bibliotheksrecherchen durch Benutzer sind Themenrecherchen. Ein Anteil dieser Recherchen bringt kein Ergebnis. Es kann leicht gemessen werden, dass null Medien gefunden wurden. Die Gründe hierfür wurden auch immer wieder untersucht: Plural- anstelle Singularformen, zu spezifische Suchbegriffe, Schreib- oder Bedienungsfehler. Zu wenig untersucht sind aber die Recherchen, die nicht mit einer Ausleihe enden, denn auch dann kann man in vielen Fällen von einem Retrieval-Mangel ausgehen. Schließlich: Von den ausgeliehenen Büchern werden nach Einschätzung vieler Bibliothekare 80% nicht weiter als bis zum Inhaltsverzeichnis gelesen (außer in Präsenzbibliotheken) - und erst nach Wochen zurückgegeben. Ein Politiker würde dies neudeutsch als "ein Vermittlungsproblem" bezeichnen. Ein Controller als nicht hinreichende Kapitalnutzung. Einfacher machen es sich immer mehr Studenten und Wissenschaftler, ihr Wissensaustausch vollzieht sich zunehmend an anderen Orten. Bibliotheken (als Funktion) sind unverzichtbar für die wissenschaftliche Kommunikation. Deshalb geht es darum, Wege zu finden und auch zu beschreiten, welche die Schätze von Bibliotheken (als Institution) effizienter an die Zielgruppe bringen. Der Einsatz von Information Retrieval-Technologie, neue Erschließungsmethoden und neuer Content sind Ansätze dazu. Doch die bisherigen Verbundstrukturen und Abhängigkeit haben das hier vorgestellte innovative Projekt keineswegs gefördert. Innovation entsteht wie die Innvoationsforschung zeigt eigentlich immer an der Peripherie: in Bregenz fing es an.

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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

Semantic Web

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Abstract

Search Engines have become an integral part of our day to day life. Our reliance on search engines increases with every passing day. With the amount of data available on Internet increasing exponentially, it becomes important to develop new methods and tools that help to return results relevant to the queries and reduce the time spent on searching. The results should be diverse but at the same time should return results focused on the queries asked. Relation Based Page Rank [4] algorithms are considered to be the next frontier in improvement of Semantic Web Search. The probability of finding relevance in the search results as posited by the user while entering the query is used to measure the relevance. However, its application is limited by the complexity of determining relation between the terms and assigning explicit meaning to each term. Trust Rank is one of the most widely used ranking algorithms for semantic web search. Few other ranking algorithms like HITS algorithm, PageRank algorithm are also used for Semantic Web Searching. In this paper, we will provide a comparison of few ranking approaches.

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Abstract

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

Source

The Semantic Web: research and applications ; second European Semantic WebConference, ESWC 2005, Heraklion, Crete, Greece, May 29 - June 1, 2005 ; proceedings. Eds.: A. Gómez-Pérez u. J. Euzenat

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Abstract

With ever increasing information being available to the end users, search engines have become the most powerful tools for obtaining useful information scattered on the Web. However, it is very common that even most renowned search engines return result sets with not so useful pages to the user. Research on semantic search aims to improve traditional information search and retrieval methods where the basic relevance criteria rely primarily on the presence of query keywords within the returned pages. This work is an attempt to explore different relevancy ranking approaches based on semantics which are considered appropriate for the retrieval of relevant information. In this paper, various pilot projects and their corresponding outcomes have been investigated based on methodologies adopted and their most distinctive characteristics towards ranking. An overview of selected approaches and their comparison by means of the classification criteria has been presented. With the help of this comparison, some common concepts and outstanding features have been identified.

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Source

Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon