Combining Concept- with Content-based Multimedia Retrieval

The arrival of the XML standard opened new doors for structured document search. Common approach in XML retrieval is to directly exploit the documents structure. However this is likely to fail for two reasons. First of all, it neglects the rich multimedia character of documents on the Internet, where a wide variety of multimedia objects can be found such as text, images and streaming video. Secondly, using the document structure as the basis for searching the content of a document can easily lead to semantical misinterpretation of the document's content. This chapter discusses an approach for searching rich multimedia document collections, that tackles these two problems using a combination of conceptual search and content-based retrieval

Indexing real-world data using semi-structured documents

We address the problem of deriving meaningful semantic index information for a multi-media database using a semi-structured docu-ment model. We show how our framework, called {em feature grammars, can be used to (1)~exploit third-party interpretation modules for real-world unstructured components, and (2)~use context-free grammars to convert such poorly or unstructured input to semi-structured output. The basic idea is to enrich context-free grammars with special symbols called detectors, which provide for the necessary structure {em just-in-time to satisfy a parser look-ahead. A prototype implementation has been constructed in the Acoi project to demonstrate the feasibility of this approach for indexing both images and audio documents

Querying XML Documents Made Easy: Nearest Concept Queries

Due to the ubiquity and popularity of XML, users often are in the following situation: they want to query XML documents which contain potentially interesting information but they are unaware of the mark-up structure that is used. For example, it is easy to guess the contents of an XML bibliography file whereas the mark-up depends on the methodological, cultural and personal background of the author(s). Nonetheless, it is this hierarchical structure that forms the basis of XML query languages. In this paper we exploit the tree structure of XML documents to equip users with a powerful tool, the meet operator, that lets them query databases with whose content they are familiar, but without requiring knowledge of tags and hierarchies. Our approach is based on computing the lowest common ancestor of nodes in the XML syntax tree: eg, given two strings, we are looking for nodes whose offspring contains these two strings. The novelty of this approach is that the result type is unknown at query formulation time and dependent on the database instance. If the two strings are an author's name and a year, mainly publications of the author in this year are returned. If the two strings are numbers the result mostly consists of publications that have the numbers as year or page numbers. Because the result type of a query is not specified by the user we refer to the lowest common ancestor as nearest concept We also present a running example taken from the bibliography domain, and demonstrate that the operator can be implemented efficiently

Flexible and scalable digital library search

In this report the development of a specialised search engine for a digital library is described. The proposed system architecture consists of three levels: the conceptual, the logical and the physical level. The conceptual level schema enables by its exposure of a domain specific schema semantically rich conceptual search. The logical level provides a description language to achieve a high degree of flexibility for multimedia retrieval. The physical level takes care of scalable and efficient persistent data storage. The role, played by each level, changes during the various stages of a search engine's lifecycle: (1) modeling the index, (2) populating and maintaining the index and (3) querying the index. The integration of all this functionality allows the combination of both conceptual and content-based querying in the query stage. A search engine for the Australian Open tennis tournament website is used as a running example, which shows the power of the complete architecture and its various component

Optical and electrical characteristics of (LiCl)x(P2O5)1-x glass.

Homogeneous (LiCl) x (P2O5)1 − x glasses were synthesised using a melt-quenching method for x = 0.1–0.6 in the interval of 0.05. The amorphous structure of the samples was evident by the X-ray diffraction spectrum. The short range structures of the binary phosphate samples were examined by Fourier transform infrared spectroscopy, whilst the density of the samples was measured as supportive data for the investigations. The results of refractive indices as measured using an ellipsometer reveal the homogeneity of samples and was found to depend on the glass composition. The electrical properties of the glasses were investigated by ac impedance spectroscopy from 10 mHz to 1 MHz for temperatures ranging from room temperature to 573 K. An estimation of the bulk resistivity was obtained by taking the intercepts on the real axis at low frequencies of the complex impedance plot. The dc conductivities derived from the reciprocal of resistivity values were found to obey the Arrhenius relationship, and its activation energy shows a decreasing trend with the increase in LiCl content in the glass. Lastly, an equivalent circuits consisting of real and complex capacitors is proposed to describe the dielectric response of the glass

Lightweight Semantics in the CLARIN Infrastructure

One of the aims of the European CLARIN infrastructure is to allow scholars to easily find and integrate data from a wide range of sources. This brings not only the problem of a broad diversity of formats and data structures, but also of terminology and semantics. To enable semantic interoperability the infrastructure uses lightweight semantic annotations, i.e., metadata and potentially resources refer to concepts in a concept registry to make their semantics explicit. This approach has been fully realized in the CLARIN joint metadata domain. The metadata uses a component-based framework, CMDI (Component Metadata Infrastructure), where resource specific metadata profiles can be assembled from reusable and adaptable components. The components themselves and the metadata elements they group use concept links to refer to metadata concepts from Dublin Core or the ISOcat Data Category Registry. Both these registries contain basically a flat or very shallow list of concepts, i.e., there is no rich set of ontological relationships between the concepts. Still this creates a semantic layer on top of the metadata profiles that helps to overcome different modeling choices made by the metadata modelers. The SMC (Semantic Mapping Component) browser helps the modelers to get insight in how components are semantically related. Metadata records of many different kinds are hosted by tens of CLARIN centers. For the central CLARIN catalogue these metadata records are harvested and mapped to a set of common facets. This mapping process uses the semantic layer, i.e., in a profile it finds metadata elements that use a concept related to the facet and selects all the instances of these elements as facet values. Further refinements of this mapping process, e.g., taking more of the context of the elements in to account, are currently investigated. Additional registries are currently being developed. The first is a relation registry, which stores at least equivalence and near sameness relations between concepts. The second is a schema registry, which stores semantically annotated schema’s for the content of linguistic sources