Reasoning & Querying – State of the Art

Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF

Data Model and Query Constructs for Versatile Web Query Languages

As the Semantic Web is gaining momentum, the need for truly versatile query languages becomes increasingly apparent. A Web query language is called versatile if it can access in the same query program data in different formats (e.g. XML and RDF). Most query languages are not versatile: they have not been specifically designed to cope with both worlds, providing a uniform language and common constructs to query and transform data in various formats. Moreover, most of them do not provide a flexible data model that is powerful enough to naturally convey both Semantic Web data formats (especially RDF and Topic Maps) and XML. This article highlights challenges related to the data model and language constructs for querying both standard Web and Semantic Web data with an emphasis on facilitating sophisticated reasoning. It is shown that Xcerpt’s data model and querying constructs are particularly well-suited for the Semantic Web, but that some adjustments of the Xcerpt syntax allow for even more effective and natural querying of RDF and Topic Maps

AMaχoS—Abstract Machine for Xcerpt

Web query languages promise convenient and efficient access to Web data such as XML, RDF, or Topic Maps. Xcerpt is one such Web query language with strong emphasis on novel high-level constructs for effective and convenient query authoring, particularly tailored to versatile access to data in different Web formats such as XML or RDF. However, so far it lacks an efficient implementation to supplement the convenient language features. AMaχoS is an abstract machine implementation for Xcerpt that aims at efficiency and ease of deployment. It strictly separates compilation and execution of queries: Queries are compiled once to abstract machine code that consists in (1) a code segment with instructions for evaluating each rule and (2) a hint segment that provides the abstract machine with optimization hints derived by the query compilation. This article summarizes the motivation and principles behind AMaχoS and discusses how its current architecture realizes these principles

Initial Draft of a Possible Declarative Semantics for the Language

This article introduces a preliminary declarative semantics for a subset of the language Xcerpt (so-called grouping-stratifiable programs) in form of a classical (Tarski style) model theory, adapted to the specific requirements of Xcerpt’s constructs (e.g. the various aspects of incompleteness in query terms, grouping constructs in rule heads, etc.). Most importantly, the model theory uses term simulation as a replacement for term equality to handle incomplete term specifications, and an extended notion of substitutions in order to properly convey the semantics of grouping constructs. Based upon this model theory, a fixpoint semantics is also described, leading to a first notion of forward chaining evaluation of Xcerpt program

Model Theory and Entailment Rules for RDF Containers, Collections and Reification

An RDF graph is, at its core, just a set of statements consisting of subjects, predicates and objects. Nevertheless, since its inception practitioners have asked for richer data structures such as containers (for open lists, sets and bags), collections (for closed lists) and reification (for quoting and provenance). Though this desire has been addressed in the RDF primer and RDF Schema specification, they are explicitely ignored in its model theory. In this paper we formalize the intuitive semantics (as suggested by the RDF primer, the RDF Schema and RDF semantics specifications) of these compound data structures by two orthogonal extensions of the RDFS model theory (RDFCC for RDF containers and collections, and RDFR for RDF reification). Second, we give a set of entailment rules that is sound and complete for the RDFCC and RDFR model theories. We show that complexity of RDFCC and RDFR entailment remains the same as that of simple RDF entailment

Enriching Existing Test Collections with OXPath

Extending TREC-style test collections by incorporating external resources is a time consuming and challenging task. Making use of freely available web data requires technical skills to work with APIs or to create a web scraping program specifically tailored to the task at hand. We present a light-weight alternative that employs the web data extraction language OXPath to harvest data to be added to an existing test collection from web resources. We demonstrate this by creating an extended version of GIRT4 called GIRT4-XT with additional metadata fields harvested via OXPath from the social sciences portal Sowiport. This allows the re-use of this collection for other evaluation purposes like bibliometrics-enhanced retrieval. The demonstrated method can be applied to a variety of similar scenarios and is not limited to extending existing collections but can also be used to create completely new ones with little effort.Comment: Experimental IR Meets Multilinguality, Multimodality, and Interaction - 8th International Conference of the CLEF Association, CLEF 2017, Dublin, Ireland, September 11-14, 201

XPath: Looking Forward

The location path language XPath is of particular importance for XML applications since it is a core component of many XML processing standards such as XSLT or XQuery. In this paper, based on axis symmetry of XPath, equivalences of XPath 1.0 location paths involving reverse axes, such as anc and prec, are established. These equivalences are used as rewriting rules in an algorithm for transforming location paths with reverse axes into equivalent reverse-axis-free ones. Location paths without reverse axes, as generated by the presented rewriting algorithm, enable efficient SAX-like streamed data processing of XPath

Term-Specific Eigenvector-Centrality in Multi-Relation Networks

Fuzzy matching and ranking are two information retrieval techniques widely used in web search. Their application to structured data, however, remains an open problem. This article investigates how eigenvector-centrality can be used for approximate matching in multi-relation graphs, that is, graphs where connections of many different types may exist. Based on an extension of the PageRank matrix, eigenvectors representing the distribution of a term after propagating term weights between related data items are computed. The result is an index which takes the document structure into account and can be used with standard document retrieval techniques. As the scheme takes the shape of an index transformation, all necessary calculations are performed during index tim