Evolutionary Conceptual Clustering Based on Induced Pseudo-Metrics

We present a method based on clustering techniques to detect possible/probable novel concepts or concept drift in a Description Logics knowledge base. The method exploits a semi-distance measure defined for individuals, that is based on a finite number of dimensions corresponding to a committee of discriminating features (concept descriptions). A maximally discriminating group of features is obtained with a randomized optimization method. In the algorithm, the possible clusterings are represented as medoids (w.r.t. the given metric) of variable length. The number of clusters is not required as a parameter, the method is able to find an optimal choice by means of evolutionary operators and a proper fitness function. An experimentation proves the feasibility of our method and its effectiveness in terms of clustering validity indices. With a supervised learning phase, each cluster can be assigned with a refined or newly constructed intensional definition expressed in the adopted language.

Identity of Resources and Entities on the Web

One of the main strengths of the Web is that it allows any party of its global community to share information with any other party. This goal has been achieved by making use of a unique and uniform mechanism of identification, the uniform resource identifiers (URI). Although URIs succeed when used for retrieving resources on the Web, their suitability for identifying any kind of thing, for example, resources that are not on the Web, is not guaranteed. In this article we investigate the meaning of the identity of a Web resource, and how the current situation, as well as existing and possible future improvements, can be modeled and implemented on the Web. In particular, we propose an ontology, IRE, that provides a formal way to model both the problem and the solution spaces. IRE describes the concept of resource from the viewpoint of the Web, by reusing an ontology of information objects, built on top of DOLCE+ and its extensions. In particular, we formalize the concept of Web resource, as distinguished from the concept of a generic entity, and how those and other concepts are related, for example, by different proxy for relations. Based on the analysis formalized in IRE, we propose a formal pattern for modeling and comparing different solutions to the problems of the identity of resources.

Semantic Web Services and Mobile Agents Integration for Efficient Mobile Services

The requirement for ubiquitous service access in wireless environments presents a great challenge in light of well-known problems like high error rate and frequent disconnections. In order to satisfy this requirement, we propose the integration of two modern service technologies: Web Services and Mobile Agents. This integration allows wireless users to access and invoke semantically enriched Web Services without the need for simultaneous, online presence of the service requestor. Moreover, in order to improve the capabilities of Service registries, we exploit the advantages offered by the Semantic Web framework. Specifically, we use enhanced registries enriched with semantic information that provide semantic matching to service queries and published service descriptions. Finally, we discuss the implementation of the proposed framework and present our performance assessment findings.

Nested Optional Join for Efficient Evaluation of SPARQL Nested Optional Graph Patterns

Relational technology has shown to be very useful for scalable Semantic Web data management. Numerous researchers have proposed to use RDBMSs to store and query voluminous RDF data using SQL and RDF query languages. This chapter studies how RDF queries with the so called well-designed graph patterns and nested optional patterns can be efficiently evaluated in an RDBMS. The authors propose to extend relational algebra with a novel relational operator, nested optional join (NOJ), that is more efficient than left outer join in processing nested optional patterns of well-designed graph patterns. They design three efficient algorithms to implement the new operator in relational databases: (1) nested-loops NOJ algorithm, NL-NOJ, (2) sort-merge NOJ algorithm, SM-NOJ, and (3) simple hash NOJ algorithm, SH-NOJ. Using a real life RDF dataset, the authors demonstrate the efficiency of their algorithms by comparing them with the corresponding left outer join implementations and explore the effect of join selectivity on the performance of these algorithms.

A Fuzzy Ontology Generation Framework from Fuzzy Relational Databases

Ontology is an important part of the W3C standards for the Semantic Web used to specify standard conceptual vocabularies to exchange data among systems, provide reusable knowledge bases, and facilitate interoperability across multiple heterogeneous systems and databases. However, current ontology is not sufficient for handling vague information that is commonly found in many application domains. A feasible solution is to import the fuzzy ability to extend the classical ontology. In this article, we propose a fuzzy ontology generation framework from the fuzzy relational databases, in which the fuzzy ontology consists of fuzzy ontology structure and instances. We simultaneously consider the schema and instances of the fuzzy relational databases, and respectively transform them to fuzzy ontology structure and fuzzy RDF data model. This can ensure the integrality of the original structure as well as the completeness and consistency of the original instances in the fuzzy relational databases.

In Defense of Ambiguity Redux

URIs, a universal identification scheme, are different from human names insofar as they can provide the ability to reliably access the thing identified. URIs also can function to reference a non-accessible thing in a similar manner to how names function in natural language. There are two distinctly different relationships between names and things: access and reference. To confuse the two relations leads to underlying problems with Web architecture. Reference is by nature ambiguous in any language. So any attempts by Web architecture to make reference completely unambiguous will fail on the Web. Despite popular belief otherwise, making further ontological distinctions often leads to more ambiguity, not less. Contrary to appeals to Kripke for some sort of eternal and unique identification, reference on the Web uses descriptions and therefore there is no unambiguous resolution of reference. On the Web, what is needed is not just a simple redirection, but a uniform and logically consistent manner of associating descriptions with URIs that can be done in a number of practical ways that should be made consistent.

Tightly Coupled Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web

This chapter presents a novel approach to fuzzy description logic programs (or simply fuzzy dl-programs) under the answer set semantics, which is a tight integration of fuzzy disjunctive logic programs under the answer set semantics with fuzzy description logics. From a different perspective, it is a generalization of tightly coupled disjunctive dl-programs by fuzzy vagueness in both the description logic and the logic program component. The authors show that the new formalism faithfully extends both fuzzy disjunctive logic programs and fuzzy description logics, and that under suitable assumptions, reasoning in the new formalism is decidable. The authors present a polynomial reduction of certain fuzzy dl-programs to tightly coupled disjunctive dl-programs, and we analyze the complexity of consistency checking and query processing for certain fuzzy dl-programs. Furthermore, the authors provide a special case of fuzzy dl-programs for which deciding consistency and query processing can both be done in polynomial time in the data complexity.

Service Provisioning through Real World Objects

The last few years have seen two parallel trends emerge. The first of such trends is set by technologies such as Near Field Communication, 2D Bar codes, RFID and others that support the association of digital information with virtually every object. Using these technologies ordinary objects such as coffee mugs or advertisement posters can provide information that is easily processed. The second trend is set by (semantic) Web services that provide a way to automatically invoke functionalities across the Internet lowering interoperability barriers. The PERCI system, discussed in the chapter, provides a way to bridge between these two technologies allowing the invocation of Web services using the information gathered from the tags effectively transforming every object in a service proxy.

Semantic-Based Bluetooth-RFID Interaction for Advanced Resource Discovery in Pervasive Contexts

We propose a novel object discovery framework integrating the application layer of Bluetooth and RFID standards. The approach is motivated and illustrated in an innovative u-commerce setting. Given a request, it allows an advanced discovery process, exploiting semantically annotated descriptions of goods available in the u-marketplace. The RFID data exchange protocol and the Bluetooth service discovery protocol have been modified and enhanced to enable support for such semantic annotation of products. Modifications to the standards have been conceived to be backward compatible, thus allowing the smooth coexistence of the legacy discovery and/or identification features. Also noteworthy is the introduction of a dedicated compression tool to reduce storage/transmission problems due to the verbosity of XML-based semantic languages.

An Associative and Adaptive Network Model For Information Retrieval In The Semantic Web

While it is agreed that semantic enrichment of resources would lead to better search results, at present the low coverage of resources on the web with semantic information presents a major hurdle in realizing the vision of search on the Semantic Web. To address this problem, this chapter investigates how to improve retrieval performance in settings where resources are sparsely annotated with semantic information. Techniques from soft computing are employed to find relevant material that was not originally annotated with the concepts used in a query. The authors present an associative retrieval model for the Semantic Web and evaluate if and to which extent the use of associative retrieval techniques increases retrieval performance. In addition, the authors present recent work on adapting the network structure based on relevance feedback by the user to further improve retrieval effectiveness. The evaluation of new retrieval paradigms - such as retrieval based on technology for the Semantic Web - presents an additional challenge since no off-the-shelf test corpora exist. Hence, this chapter gives a detailed description of the approach taken to evaluate the information retrieval service the authors have built.