semantic

Abstract: Using keyword search to find relevant objects in digital libraries often results in way too large result sets. Based on the metadata associated with such objects, the faceted search paradigm allows users to structure and filter the result set, for example, using a publication type facet to show only books or videos. These facets usually focus on clear-cut characteristics of digital items, however it is very difficult to also organize the actual semantic content information into such a facet. The Semantic GrowBag approach, presented in this paper, uses the keywords provided by many authors of digital objects to automatically create light-weight topic categorization systems as a basis for a meaningful and dynamically adaptable topic facet. Using such emergent semantics enables an alternative way to filter large result sets according to the objects’ content without the need to manually classify all objects with respect to a pre-specified vocabulary. We present the details of our algorithm using the DBLP collection of computer science documents and show some experimental evidence about the quality of the achieved results.

 metadata;  categories;  facets;  semantic;  tags;  

Checkout More Details | Available Online

Abstract: Both the Resource Description Framework (RDF), used in the semantic web, and Maya Viz u-forms represent data as a graph of objects connected by labeled edges. Existing systems for flexible visualization of this kind of data require manual specification of the possible visualization roles for each data attribute. When the schema is large and unfamiliar, this requirement inhibits exploratory visualization by requiring a costly up-front data integration step. To eliminate this step, we propose an automatic technique for mapping data attributes to visualization attributes. We formulate this as a schema matching problem, finding appropriate paths in the data model for each required visualization attribute in a visualization template.

 Visualization;  data integration;  semantic;  infovis;  data-mining;  rdf;  attribute inference;  

Abstract: Sorry no abstract available for this article

 clustering;  semantic;  tagging;  folksonomy;  

Checkout More Details | Available Online

Abstract: We describe an approach for extracting semantics of tags, unstructured text-labels assigned to resources on the Web, based on each tag’s usage patterns. In particular, we focus on the problem of extracting place and event semantics for tags that are assigned to photos on Flickr, a popular photo sharing website that supports time and location (latitude/longitude) metadata. We analyze two methods inspired by well-known burst-analysis techniques and one novel method: Scale-structure Identification. We evaluate the methods on a subset of Flickr data, and show that our Scale-structure Identification method outperforms the existing techniques. The approach and methods described in this work can be used in other domains such as geo-annotated web pages, where text terms can be extracted and associated with usage patterns.

 semantic;  tags;  temporal;  flickr;  geocoding;  automatic;  

Checkout More Details | Available Online

Abstract: Sorry no abstract available for this article

 semantic;  tags;  flickr;  geocoding;  

Checkout More Details | Available Online

Abstract: Sorry no abstract available for this article

 semantic;  database;  data-mining;  

Checkout More Details | Available Online

Abstract: Sorry no abstract available for this article

 ontology;  document;  semantic;  citations;  

Checkout More Details | Available Online

Abstract: Ontologies and reasoning are the key terms brought into focus by the semantic web community. Formal representation of ontologies in a common data model on the web can be taken as a foundation for adaptive web technologies as well. This chapter describes how ontologies shared on the semantic web provide conceptualization for the links which are a main vehicle to access information on the web. The subject domain ontologies serve as constraints for generating only those links which are relevant for the domain a user is currently interested in. Furthermore, user model ontologies provide additional means for deciding which links to show, annotate, hide, generate, and reorder. The semantic web technologies provide means to formalize the domain ontologies and metadata created from them. The formalization enables reasoning for personalization decisions. This chapter describes which components are crucial to be formalized by the semantic web ontologies for adaptive web. We use examples from an eLearning domain to illustrate the principles which are broadly applicable to any information domain on the web.

 ontology;  semantic;  web;  semanticweb;  adaptive;  

Checkout More Details | Available Online

Abstract: While tags in collaborative tagging systems serve primarily an indexing purpose, facilitating search and navigation of resources, the use of the same tags by more than one individual can yield a collective classification schema. We present an approach for making explicit the semantics behind the tag space in social tagging systems, so that this collaborative organization can emerge in the form of groups of concepts and partial ontologies. This is achieved by using a combination of shallow pre-processing strategies and statistical techniques together with knowledge provided by ontologies available on the semantic web. Preliminary results on the del.icio.us and Flickr tag sets show that the approach is very promising: it generates clusters with highly related tags corresponding to concepts in ontologies and meaningful relationships among subsets of these tags can be identified.

 ontology;  semantic;  database;  folksonomy;  semanticweb;  discovery;  

Checkout More Details | Available Online

Abstract: We propose a novel method to support analytical processes by visually integrating context information directly into web pages. The context information is obtained from knowledge bases or services that provide additional information about certain concepts and instances of a knowledge domain. The approach performs implicit queries on the underlying information sources using the key phrases of the web page and visually presents the results to the user in a seamless way. The technique aims at improving the integration of different information sources into the users task. The method has two phases, an augmentation and an interaction phase. In the augmentation phase, for each key phrase the availability of additional context information is checked. All phrases for which context information is available are highlighted by adding special markups and scripts to the web page. In the interaction phase, the user can click on a highlighted phrase to receive the associated context information. The information is displayed directly in the web page in an overlay that we call a semantic lens.

 query;  semantic;  web;  automated;  web-based;  

Checkout More Details | Available Online

Abstract: Sorry no abstract available for this article

 query;  semantic;  database;  information-retrieval;  

Checkout More Details | Available Online

Abstract: Understanding networks of connections among individuals is an important element of counterterrorism analysis. Determining nodes and links for such networks is one of the most labor-intensive aspects of counterterrorism analysis. This paper presents an automated approach for generating and displaying an initial estimate of nodes and links relevant to a chosen topic. This work combines the use of entity extraction and latent semantic indexing (LSI).

 analysis;  terrorism;  semantic;  information-retrieval;  graphs;  

Checkout More Details | Available Online

Abstract: We present OntoWiki, a tool providing support for agile, distributed knowledge engineering scenarios. OntoWiki facilitates the visual presentation of a knowledge base as an information map, with different views on instance data. It enables intuitive authoring of semantic content, with an inline editing mode for editing RDF content, similar to WYSIWYG for text documents. It fosters social collaboration aspects by keeping track of changes, allowing to comment and discuss every single part of a knowledge base, enabling to rate and measure the popularity of content and honoring the activity of users. Ontowiki enhances the browsing and retrieval by offering semantic enhanced search strategies. All these techniques are applied with the ultimate goal of decreasing the entrance barrier for projects and domain experts to collaborate using semantic technologies. In the spirit of the Web 2.0 OntoWiki implements an ”architecture of participation” that allows users to add value to the application as they use it. It is available as open-source software and a demonstration platform can be accessed at http://3ba.se.

 ontology;  semantic;  collaboration;  semanticweb;  wiki;  social computing;  

Checkout More Details | Available Online

Abstract: This paper presents an automated approach to learning object models by means of useful object data extracted from data-intensive semistructured Web documents such as product descriptions. Modeling intensive data on the Web involves the following three phrases: first, we identify the object region covering the descriptions of object data when irrelevant contents from the Web documents are excluded. Second, we partition the contents of different object data appearing in the object region and construct object data using hierarchical XML outputs. Third, we induce the abstract object model from the analogous object data. This model would match the corresponding object data from a Web site more precisely and comprehensively than the existing handcrafted ontologies. The main contribution of this study is in developing a fully automated approach to extract object data and object model from semistructured Web documents using kernel-based matching and view syntax interpretation. Our system, OnModer, can automatically construct object data and induce object models from complicated Web documents, such as the technical descriptions of personal computers and digital cameras downloaded from manufacturers and vendors sites. A comparison with the available hand-crafted ontologies and tests on an open corpus demonstrate that our framework is effective in extracting meaningful and comprehensive models.

 ontology;  knowledge-discovery;  semantic;  web;  automated;  markup;  

Checkout More Details | Available Online

Abstract: To help human users and software agents find relevant knowledge on the Semantic Web, the Swoogle search engine discovers, indexes, and analyzes the ontologies and facts that are encoded in Semantic Web documents.

 ontology;  search;  semantic;  information-retrieval;  data-mining;  semanticweb;  

Checkout More Details | Available Online

Abstract: XSEarch, a semantic search engine for XML, is presented. XSEarch has a simple query language, suitable for a naive user. It returns semantically related document fragments that satisfy the users query. Query answers are ranked using extended information-retrieval techniques and are generated in an order similar to the ranking. Advanced indexing techniques were developed to facilitate e#cient implementation of XSEarch. The performance of the di#erent techniques as well as the recall...

 XML;  search;  semantic;  database;  information-retrieval;  

Checkout More Details | Available Online

Abstract: RDF and RDF Schema are two W3C standards aimed at enriching the Web with machine-processable semantic data. We have developed Sesame, an architecture for efficient storage and expressive querying of large quantities of metadata in RDF and RDF Schema. Sesames design and implementation are independent from any specific storage device. Thus, Sesame can be deployed on top of a variety of storage devices, such as relational databases, triple stores, or object-oriented databases, without having to change the query engine or other functional modules. Sesame offers support for concurrency control, independent export of RDF and RDFS information and a query engine for RQL, a query language for RDF that offers native support for RDF Schema semantics. We present an overview of Sesame as a generic architecture, as well as its implementation and our first experiences with this implementation.

 query;  semantic;  rdf;  

Checkout More Details | Available Online

Abstract: The efficient query and extraction of web data is often difficult, because web data does not conform to any data organization standard. In addition, the development of web search technology is still at a relatively early stage. Search engines provide only primitive data query capabilities, and require a detailed syntactic specification to retrieve relevant data. Furthermore, web data exists in a myriad of formats including PDF documents, images, and sound clips that are difficult to be queried. This research proposes a smart web query (SWQ) method for the semantic retrieval of web data. The SWQ method uses domain semantics represented as context ontologies to specify and formulate appropriate web queries to search. This method also relies on semantic search filters to identify and rank relevant web pages semi-automatically. Unlike traditional ontologies that are structured in a hierarchy, terms and their relationships that pertain to a particular domain are organized with a flexible structure by the context ontologies. An SWQ engine is being developed to test the proposed method. Financial trading (e.g. stocks, bonds, unit trusts) is adapted as an example domain (i.e., context) to test and validate the SWQ method and engine.

 ontology;  search;  query;  semantic;  information-retrieval;  data-mining;  semanticweb;  

Checkout More Details | Available Online

Abstract: Abstract.\ \  Technical interoperability has provided geographic information communities with substantial improvements for constructing GIS capable of very low friction and dynamic data exchanges. These technical advances stand to provide substantial advantages for sharing geographic information, however reaping these advantages in highly heterogeneous operational and organizational environments requires the understanding and resolution of semantic differences. While the OpenGIS consortium has made important progress on technical interoperability, semantic interoperability still remains an unpassed hurdle for efforts to share geographic information across organizational and institutional boundaries at the local, regional, and other levels. Identifying and resolving semantic interoperability issues is especially pertinent for data sharing and considering future developments of standards. This paper presents an overview of semantic interoperability and through case studies shows the breadth and depth of issues and approaches in different countries and at different levels of organizations. These cases illustrate the importance of developing flexible approaches to practical data sharing problems that merge semantical with technical considerations. Based on our examinations of semantic issues and approaches in ongoing research projects, we propose cognitive, computer science, and socio-technical frameworks for examining semantic interoperability.

 GIS;  semantic;  interoperability;  ogc;  

Checkout More Details | Available Online

Abstract: As the number of Internet users and the number of accessible Web pages grows, it is becoming increasingly difficult for users to find documents that are relevant to their particular needs. Users must either browse through a large hierarchy of con cepts to find the information for which they are looking or submit a query to a publicly available search engine and wade through hundreds of results, most of them irrelevant. The core of the problem is that whether the user is browsing or searching,...

 ontology;  search;  semantic;  

Checkout More Details | Available Online