Raquel Trillo

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.

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.

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

Using semantic techniques to access web data

Nowadays, people frequently use different keyword-based web search engines to find the information they need on the web. However, many words are polysemous and, when these words are used to query a search engine, its output usually includes links to web pages referring to their different meanings. Besides, results with different meanings are mixed up, which makes the task of finding the relevant information difficult for the users, especially if the user-intended meanings behind the input keywords are not among the most popular on the web. In this paper, we propose a set of semantics techniques to group the results provided by a traditional search engine into categories defined by the different meanings of the input keywords. Differently from other proposals, our method considers the knowledge provided by ontologies available on the web in order to dynamically define the possible categories. Thus, it is independent of the sources providing the results that must be grouped. Our experimental results show the interest of the proposal.

From keywords to queries: discovering the user's intended meaning

Regarding web searches, users have become used to keyword-based search interfaces due to their ease of use. However, this implies a semantic gap between the users information need and the input of search engines, as keywords are a simplification of the real user query. Thus, the same set of keywords can be used to search different information. Besides, retrieval approaches based only on syntactic matches with user keywords are not accurate enough when users look for information not so popular on the Web. So, there is a growing interest in developing semantic search engines that overcome these limitations. In this paper, we focus on the front-end of semantic search systems and propose an approach to translate a list of user keywords into an unambiguous query, expressed in a formal language, that represents the exact semantics intended by the user. We aim at not sacrificing any possible interpretation while avoiding generating semantically equivalent queries. To do so, we apply several semantic techniques that consider the properties of the operators and the semantics behind the keywords. Moreover, our approach also allows us to present the queries to the user in a compact representation. Experimental results show the feasibility of our approach and its effectiveness in facilitating the users to express their intended query.

Semantic Discovery of the User Intended Query in a Selectable Target Query Language

The syntactic approach of most of Web search engines still has the drawback of not considering the semantics of the keywords entered by the user. So, users usually have to browse many hits looking for the information they want. In this paper, we present a system that, given a set of keywords with well defined semantics, automatically generates a set of formal queries, in the query language of the users choice, which attempt to capture what the user had in mind when she or he wrote those keywords. The system uses ontologies and a description logics reasoner to perform a semantic enrichment of user keywords to improve the discovering of possible user queries and to reject semantically inconsistent queries.

SQX-Lib: Developing a Semantic Query Expansion System in a Media Group

Recently, there has been an exponential growth in the amount of digital data stored in repositories. Therefore, the efficient and effective retrieval of information from them has become a key issue. Organizations use traditional architectures and methodologies based on classical relational databases, but these approaches do not consider the semantics of the data or they perform complex ETL processes from relational repositories to triple repositories. Most companies do not carry out this type of migration due to lack of time, money or knowledge. In this paper we present a system that performs a semantic query expansion to improve information retrieval from traditional relational databases repositories. We have also linked it to an actual system and we have carried out a set of tests in a real Media Group organization. Results are very promising and show the interest of the proposal.

Push-Based Recommendations in Mobile Computing Using a Multi-Layer Contextual Approach

Nowadays, due to the high availability of heterogeneous data sources that can provide interesting information, users usually suffer from information overload. Therefore, the development of adaptive information systems that can offer personalized information and filter out irrelevant data for a user is required. Significant work has been developed to solve this problem in the area of the so-called recommendation systems. However, context information has only started to be considered recently to build recommendation systems, despite being key to obtain more accurate recommendations. Moreover, even with some context information, there is still a significant gap between the fields of mobile computing and recommendation systems. In this paper, we focus on push-based recommendations (i.e., recommendations not explicitly requested) for mobile users, as it represents the most challenging and effective approach for recommending items in mobile environments. As opposed to existing work, a generic model that fits different domains is proposed. This model is based on the definition of the concept of environment and manages the impact of dynamic events and all the actors involved in the mobile recommendation process.

GeoSPRINGS: Towards a Location-Aware Mobile Agent Platform

Mobile agent technology enables the autonomous migration of code from one computer/device to another, to efficiently exploit the available computing resources or access data locally. It can provide interesting advantages in distributed and mobile computing scenarios. However, existing mobile agent platforms do not offer facilities for the design of agents that are location-aware and that can support a variety of communication options, including mobile ad hoc communications.

A female engineer in every school

This paper presents a novel initiative carried out in the Spanish region of Aragon in the last three years to promote engineering vocations among primary school children, especially among girls. Another objective is to make visible the role of women in the engineering field and to put into value their contributions. To do so, women working in this areas, both from the academic and professional fields, visit schools to sensitize teachers and give a talk and run a workshop with the kids. Workshops are creative, collaborative, without a final closed result, each group creates their designs or proposes their solutions. In this way, it is intended to offer girls a positive experience that promotes their self-perceived effectiveness, accompanied by women that can represent models for them. The initiative, which has evolved over its three years of existence, aims to reverse the decline of vocations in the field of STEM careers and increase the presence of women in these studies.