Eduardo Mena

OBSERVER: An Approach for Query Processing in Global Information Systems Based on Interoperation Across Pre-Existing Ontologies

There has been an explosion in the types, availability and volume of data accessible in an information system, thanks to the World Wide Web (the Web) and related inter-networking technologies. In this environment, there is a critical need to replace or complement earlier database integration approaches and current browsing and keyword-based techniques with concept-based approaches. Ontologies are increasingly becoming accepted as an important part of any concept or semantics based solution, and there is increasing realization that any viable solution will need to support multiple ontologies that may be independently developed and managed. In particular, we consider the use of concepts from pre-existing real world domain ontologies for describing the content of the underlying data repositories. The most challenging issue in this approach is that of vocabulary sharing, which involves dealing with the use of different terms or concepts to describe similar information. In this paper, we describe the architecture, design and implementation of the OBSERVER system. Brokering across the domain ontologies is enabled by representing and utilizing interontology relationships such as (but not limited to) synonyms, hyponyms and hypernyms across terms in different ontologies. User queries are rewritten by using these relationships to obtain translations across ontologies. Well established metrics like precision and recall based on the extensions underlying the concepts are used to estimate the loss of information, if any.

Location-dependent query processing: Where we are and where we are heading

The continuous development of wireless networks and mobile devices has motivated an intense research in mobile data services. Some of these services provide the user with context-aware information. Specifically, location-based services and location-dependent queries have attracted a lot of interest. In this article, the existing literature in the field of location-dependent query processing is reviewed. The technological context (mobile computing) and support middleware (such as moving object databases and data stream technology) are described, location-based services and location-dependent queries are defined and classified, and different query processing approaches are reviewed and compared.

Emergent semantics principles and issues

Information and communication infrastructures underwent a rapid and extreme decentralization process over the past decade: From a world of statically and partially connected central servers rose an intricate web of millions of information sources loosely connecting one to another. Today, we expect to witness the extension of this revolution with the wide adoption of meta-data standards like RDF or OWL underpinning the creation of a semantic web. Again, we hope for global properties to emerge from a multiplicity of pair-wise, local interactions, resulting eventually in a self-stabilizing semantic infrastructure. This paper represents an effort to summarize the conditions under which this revolution would take place as well as an attempt to underline its main properties, limitations and possible applications.

Web-Based Measure of Semantic Relatedness

Semantic relatedness measures quantify the degree in which some words or concepts are related, considering not only similarity but any possible semantic relationship among them. Relatedness computation is of great interest in different areas, such as Natural Language Processing, Information Retrieval, or the Semantic Web. Different methods have been proposed in the past; however, current relatedness measures lack some desirable properties for a new generation of Semantic Web applications: maximum coverage, domain independence, and universality. In this paper, we explore the use of a semantic relatedness measure between words, that uses the Web as knowledge source. This measure exploits the information about frequencies of use provided by existing search engines. Furthermore, taking this measure as basis, we define a new semantic relatedness measure among ontology terms. The proposed measure fulfils the above mentioned desirable properties to be used on the Semantic Web. We have tested extensively this semantic measure to show that it correlates well with human judgment, and helps solving some particular tasks, as word sense disambiguation or ontology matching.

Comparison and Performance Evaluation of Mobile Agent Platforms

Mobile agents are considered a very interesting technology to develop applications for mobile, pervasive, and distributed computing. Thus, they present a combination of unique features, such as their autonomy and capability to move to remote computers to process data there and save remote communications. Many mobile agent platforms have been developed since the late nineties. While some of them have been abandoned, others continue releasing new versions that fix bugs detected or offer new interesting features. Moreover, other new platforms have appeared in the last few years. So, a common problem when one wants to benefit from mobile agent technology to develop distributed applications is the decision about which platform to use. In this paper, we provide an up-to-date evaluation of existing mobile agent platforms. We compare them qualitatively and evaluate their performance.

Location-dependent queries in mobile contexts: distributed processing using mobile agents

With the current advances of mobile computing technology, we are witnessing an explosion in the development of applications that provide mobile users with a wide range of services. In this paper, we present a system that supports distributed processing of continuous location-dependent queries in mobile environments. The system that we propose presents the following main advantages: 1) it is a general solution for the processing of location-dependent queries in scenarios where not only the users issuing queries, but also other interesting objects can move; 2) it performs an efficient processing of these queries in a continuous way; 3) it is especially well adapted to environments where location data are distributed in a network and processing tasks can be performed in parallel, allowing a high scalability; and 4) it optimizes wireless communications. We use mobile agents to carry the processing tasks wherever they are needed. Thus, agents are in charge of tracking the location of interesting moving objects and refreshing the answer to a query efficiently. We evaluate the usefulness of the presented proposal showing that the system achieves a good precision and scales up well

Using cooperative mobile agents to monitor distributed and dynamic environments

Monitoring the changes in data values obtained from the environment (e.g., locations of moving objects) is a primary concern in many fields, as for example in the pervasive computing environment. The monitoring task is challenging from a double perspective. First and foremost, the environment can be highly dynamic in terms of the rate of data changes. Second, the monitored data are often not available from a single computer/device but are distributed; moreover, the set of data providers can change along the course of time. Therefore, obtaining a global snapshot of the environment and keeping it up-to-date is not easy, especially if the conditions (e.g., network delays) change. In this article, a decentralized, loose, and fault-tolerant monitoring approach based on the use of mobile agents is described. Mobile agents allow easy tracking of the involved computers, carrying the monitoring tasks to wherever they are needed. A deadline-based mechanism is used to coordinate the cooperative agents, which strive to perform their continuous tasks in time while considering data as recent as possible, constantly adapting themselves to new environmental conditions (changing communication and processing delays). This approach has been successfully used in a real environment and experiments were carried out to prove its feasibility and benefits.

Querying the web: a multiontology disambiguation method

The lack of explicit semantics in the current Web can lead to ambiguity problems: for example, current search engines return unwanted information since they do not take into account the exact meaning given by user to the keywords used. Though disambiguation is a very well-known problem in Natural Language Processing and other domains, traditional methods are not flexible enough to work in a Web-based context.In this paper we have identified some desirable properties that a Web-oriented disambiguation method should fulfill, and make a proposal according to them. The proposed method processes a set of related keywords in order to discover and extract their implicit semantics, obtaining their most suitable senses according to their context. The possible senses are extracted from the knowledge represented by a pool of ontologies available in the Web. This method applies an iterative disambiguation algorithm that uses a semantic relatedness measure based on Google frequencies. Our proposal makes explicit the semantics of keywords by means of ontology terms; this information can be used for different purposes, such as improving the search and retrieval of underlying relevant information.

Enriching an ontology with multilingual information

Organizations working in amultilingual environment demand multilingual ontologies. To solve this problem we propose LabelTranslator, a system that automatically localizes ontologies. Ontology localization consists of adapting an ontology to a concrete language and cultural community. LabelTranslator takes as input an ontology whose labels are described in a source natural language and obtains the most probable translation into a target natural language of each ontology label. Our main contribution is the automatization of this process which reduces human efforts to localize an ontology manually. First, our system uses a translation service which obtains automatic translations of each ontology label (name of an ontology term) from/into English, German, or Spanish by consulting different linguistic resources such as lexical databases, bilingual dictionaries, and terminologies. Second, a ranking method is used to sort each ontology label according to similarity with its lexical and semantic context. The experiments performed in order to evaluate the quality of translation show that our approach is a good approximation to automatically enrich an ontology with multilingual information.

SPRINGS: a scalable platform for highly mobile agents in distributed computing environments

In the last decade, mobile agents have arisen as a promising paradigm to build distributed and mobile computing applications. However, mobile agents have not been massively adopted. One of the reasons could be that some issues have yet to be solved to increase the confidence of developers. Thus, scalability problems sometimes arise in applications with a high number of mobile agents when calls and trips happen very frequently. In this paper we present SPRINGS, a novel Java-based mobile agent system which is scalable, flexible, and easy to use. Our work has been motivated by our experience with mobile agents in several research projects. We focus on scalability issues and efficient maintenance of location-independent agent references in dynamic scenarios where agents communicate and travel frequently among computers. We have obtained encouraging performance results through an extensive set of experiments. Moreover, our tests show that SPRINGS achieves a degree of concurrency that other well-known platforms cannot reach