Dimitris Plexousakis

RQL: a declarative query language for RDF

Real-scale Semantic Web applications, such as Knowledge Portals and E-Marketplaces, require the management of large volumes of metadata, i.e., information describing the available Web content and services. Better knowledge about their meaning, usage, accessibility or quality will considerably facilitate an automated processing of Web resources. The Resource Description Framework (RDF) enables the creation and exchange of metadata as normal Web data. Although voluminous RDF descriptions are already appearing, sufficiently expressive declarative languages for querying both RDF descriptions and schemas are still missing. In this paper, we propose a new RDF query language called RQL. It is a typed functional language (a la OQL) and relies on a formal model for directed labeled graphs permitting the interpretation of superimposed resource descriptions by means of one or more RDF schemas. RQL adapts the functionality of semistructured/XML query languages to the peculiarities of RDF but, foremost, it enables to uniformly query both resource descriptions and schemas. We illustrate the RQL syntax, semantics and typing system by means of a set of example queries and report on the performance of our persistent RDF Store employed by the RQL interpreter.

Ontology change: Classification and survey

Ontologies play a key role in the advent of the Semantic Web. An important problem when dealing with ontologies is the modification of an existing ontology in response to a certain need for change. This problem is a complex and multifaceted one, because it can take several different forms and includes several related subproblems, like heterogeneity resolution or keeping track of ontology versions. As a result, it is being addressed by several different, but closely related and often overlapping research disciplines. Unfortunately, the boundaries of each such discipline are not clear, as the same term is often used with different meanings in the relevant literature, creating a certain amount of confusion. The purpose of this paper is to identify the exact relationships between these research areas and to determine the boundaries of each field, by performing a broad review of the relevant literature.

Alleviating the sparsity problem of collaborative filtering using trust inferences

Collaborative Filtering (CF), the prevalent recommendation approach, has been successfully used to identify users that can be characterized as “similar” according to their logged history of prior transactions. However, the applicability of CF is limited due to the sparsity problem, which refers to a situation that transactional data are lacking or are insufficient. In an attempt to provide high-quality recommendations even when data are sparse, we propose a method for alleviating sparsity using trust inferences. Trust inferences are transitive associations between users in the context of an underlying social network and are valuable sources of additional information that help dealing with the sparsity and the cold-start problems. A trust computational model has been developed that permits to define the subjective notion of trust by applying confidence and uncertainty properties to network associations. We compare our method with the classic CF that does not consider any transitive associations. Our experimental results indicate that our method of trust inferences significantly improves the quality performance of the classic CF method.

Semantic QoS Metric Matching

As the Web service paradigm gains popularity for its promise to transform the way business is conducted, the number of deployed Web services grows with a fast rate. While sophisticated semantic discovery mechanisms have been invented to overcome the UDDIs syntactic discovery solution in order to provide more recallable and precise results, the amount of functionally equivalent Web services returned is still large. The solution to this problem is the description of the QoS non-functional aspect of Web services. QoS encompasses the performance of Web services and can be used as a discriminator factor for refining Web service advertisement result lists. However, most scientific efforts presented so far are purely syntactic and are not capturing all aspects of QoS-based Web service description leading to imprecise syntactic discovery mechanisms. This paper presents a novel, rich and extensible ontology-based approach for describing QoS of Web services that complements OWL-S. It is shown that, by using this approach and by introducing the concept of semantic QoS metric matching, QoS-based syntactic matchmaking and selection algorithms are transformed to semantic ones leading to better results

On labeling schemes for the semantic web

This paper focuses on the optimization of the navigation through voluminous subsumption hierarchies of topics employed by Portal Catalogs like Netscape Open Directory (ODP). We advocate for the use of labeling schemes for modeling these hierarchies in order to efficiently answer queries such as subsumption check, descendants, ancestors or nearest common ancestor, which usually require costly transitive closure computations. We first give a qualitative comparison of three main families of schemes, namely bit vector, prefix and interval based schemes. We then show that two labeling schemes are good candidates for an efficient implementation of label querying using standard relational DBMS, namely, the Dewey Prefix scheme [6] and an Interval scheme by Agrawal, Borgida and Jagadish [1]. We compare their storage and query evaluation performance for the 16 ODP hierarchies using the PostgreSQL engine.

A formal framework for business process modelling and design

We present a formal framework for enterprise and business process modelling. The concepts of our framework (objectives and goals, roles and actors, actions and processes, responsibilities and constraints) allow business analysts to capture enterprise knowledge in a way that is both intuitive and mathematically formal. We also outline the basic steps of a methodology that allows business analysts to produce detailed, formal specifications of business processes from high-level enterprise objectives. The use of a formal language permits us to verify that the specifications possess certain correctness properties, namely that the responsibilities assigned to roles are fulfilled, and that constraints are maintained as a result of process execution.

On applying the AGM theory to DLs and OWL

It is generally acknowledged that any Knowledge Base (KB) should be able to adapt itself to new information received. This problem has been extensively studied in the field of belief change, the dominating approach being the AGM theory. This theory set the standard for determining the rationality of a given belief change mechanism but was placed in a certain context which makes it inapplicable to logics used in the Semantic Web, such as Description Logics (DLs) and OWL. We believe the Semantic Web community would benefit from the application of the AGM theory to such logics. This paper is a preliminary study towards the feasibility of this application. Our approach raises interesting theoretical challenges and has an important practical impact too, given the central role that DLs and OWL play in the Semantic Web.

A Survey of Semantics-Based Approaches for Context Reasoning in Ambient Intelligence

A key issue in the study of Ambient Intelligence is reasoning about context. The aim of context reasoning is to deduce new knowledge, based on the available context data. The endmost goal is to make the ambient services more ”intelligent”; closer to the specific needs of their users. The main challenges of this effort derive from the imperfect context information, and the dynamic and heterogeneous nature of the ambient environments. In this paper, we focus on semantics-based approaches for reasoning about context. We describe how each approach addresses the requirements of ambient environments, identify their limitations, and propose possible future research directions.

Mixed-Integer Programming for QoS-Based Web Service Matchmaking

QoS-based Web service (WS) discovery has been recognized as the main solution for filtering and selecting between functionally equivalent WSs stored in registries or other types of repositories. There are two main techniques for QoS-based WS matchmaking (filtering): ontology-based and constraint programming (CP)-based. Unfortunately, the first technique is not efficient as it is based on the rather immature technology of ontology reasoning, while the second one is not accurate as it is based on syntactic QoS-based descriptions and faulty matchmaking metrics. In our previous work, we have developed an extensible and rich ontology language for QoS-based WS description. Moreover, we have devised a semantic alignment algorithm for aligning QoS-based WS descriptions so as to increase the accuracy of QoS-based WS matchmaking algorithms. Finally, we have developed two alternative CP-based QoS-based WS matchmaking algorithms: a unary-constrained and n-ary-constrained one. In this paper, we claim that mixed-integer programming (MIP) should be used as a matchmaking technique instead of CP and we provide experimental results proving it. In addition, we analyze and experimentally evaluate our matchmaking algorithms against a competing techniques one in order to demonstrate their efficiency and accuracy.

Querying the Semantic Web with RQL

Real-scale Semantic Web applications, such as Knowledge Portals and E-Marketplaces, require the management of voluminous repositories of resource metadata. The Resource Description Framework (RDF) enables the creation and exchange of metadata as any other Web data. Although large volumes of RDF descriptions are already appearing, sufficiently expressive declarative query languages for RDF are still missing. We propose RQL, a new query language adapting the functionality of semistructured or XML query languages to the peculiarities of RDF but also extending this functionality in order to uniformly query both RDF descriptions and schemas. RQL is a typed language, following a functional approach a la OQL and relies on a formal graph model that permits the interpretation of superimposed resource descriptions created using one or more RDF schemas. We illustrate the syntax, semantics and type system of RQL and report on the performance of RSSDB, our persistent RDF Store, for storing and querying voluminous RDF metadata.