Eloisa Vargiu

Eurecat, Health, Department Member

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Eloisa Vargiu, researcher of eHealth R&D group at Barcelona Digital, holds a Ph.D. degree in Electronic and Computer Engineering by the University of Cagliari (Italy). During her Ph.D., she studied the pro-active and adaptive behavior of agents and she developed a hierarchical agent architecture.

In the same period, she collaborated with the CRS4, an interdisciplinary research center located in Sardinia. During her post-doc activity, she worked on different projects on bioinformatics and information retrieval. She has collaborated more than 10 years with the Intelligent Agents and Soft-Computing (IASC) group at the Departament of Electrical and Electronic Engineering (DIEE), of Cagliari.

She is co-author of more than 50 peer-reviewed publications in internation journals and conferences, as well as co-editor of 3 books.
Phone: +34-93-553.4540 ext. 2222
Address: Roc Boronat, 117
Barcelona

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Books by Eloisa Vargiu

New Challenges in Distributed Information Filtering and Retrieval. DART 2011: Revised and Invited Papers

Advances in Distributed Agent-based Retrieval Tools

Information Retrieval and Mining in Distributed Environments

Intelligent Information Access

Intelligent Information Access techniques attempt to overcome the limitations of current search d... more Intelligent Information Access techniques attempt to overcome the limitations of current search devices by providing personalized information items and product/ service recommendations. They normally utilize direct or indirect user input and facilitate the information search and decision processes, according to user needs, preferences and usage patterns. Recent developments at the intersection of Information Retrieval, Information Filtering, Machine Learning, User Modelling, Natural Language Processing and Human-Computer Interaction offer novel solutions that empower users to go beyond single-session lookup tasks and that aim at serving the more complex requirement: “Tell me what I don’t know that I need to know”. Information filtering systems, specifically recommender systems, have been revolutionizing the way information seekers find what they want, because they effectively prune large information spaces and help users in selecting items that best meet their needs and preferences. Recommender systems rely strongly on the use of various machine learning tools and algorithms for learning how to rank, or predict user evaluation, of items. Information Retrieval systems, on the other hand, also attempt to address similar filtering and ranking problems for pieces of information such as links, pages, and documents. But they generally focus on the development of global retrieval techniques, often neglecting individual user needs and preferences. The book aims to investigate current developments and new insights into methods, techniques and technologies for intelligent information access from a multidisciplinary perspective. It comprises six chapters authored by participants in the research event Intelligent Information Access, held in Cagliari (Italy) in December 2008.

Papers by Eloisa Vargiu

Protein Secondary Structure Prediction Through a Cooperative MultiAgent Learning Approach

by Andrea Addis and Eloisa Vargiu

System and Information …, Jan 1, 2007

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DHG: A System for Generating Macro-Operators from Static Domain Analysis

by Eloisa Vargiu and Giuliano Armano

Artificial Intelligence and Applications, 2005

ABSTRACT The attempt of dealing with the complexity of planning tasks by resorting to abstraction... more ABSTRACT The attempt of dealing with the complexity of planning tasks by resorting to abstraction techniques is a central issue in the field of automated planning. Although the generality of the approach has not been proved always useful on domains selected for benchmarking purposes, in our opinion it will play a central role as soon as the focus will move from artificial to real problems. In this case, it will be crucial to have a tool for automatically generating abstraction hierarchies from a domain description. This paper ...

An Extension to PDDL for Hierarchical Planning

by Eloisa Vargiu and Giuliano Armano

This paper describes an extension to PDDL, devised to support hierarchical planning. The proposed... more

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A novel semantic approach to document collections

by Eloisa Vargiu, Giuliano Armano, Andrea Addis, and Franco Tuveri

IADIS Multi Conference on Computer Science and Information Systems, 2008

Available document collections are more and more required for supervised text categorization task... more Available document collections are more and more required for supervised text categorization tasks. They are typically collections of documents classified by domain engineers. In this paper, we propose a semantic text categorization approach able to automatically create document collections in which documents are classified according to WordNet Domains taxonomy. Experiments have been performed by training a classifier with an automatic document collection and comparing results with those obtained

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Experimental assessment of a threshold selection algorithm for tuning classifiers in the field of hierarchical text categorization

by Eloisa Vargiu, Giuliano Armano, and Andrea Addis

Proceedings of 17th RCRA International Workshop on Experimental evaluation of algorithms for solving problems with combinatorial explosion, 2010

Text Categorization is the task of assigning predefined categories to text documents. It can prov... more Text Categorization is the task of assigning predefined categories to text documents. It can provide conceptual views of document collections and has many important applications in the real world. Nowadays, most of the research on text categorization has focused on mapping text documents to a set of categories among which structural relationships hold. Without loss of generality, let us assume that a classifier entrusted with recognizing documents of a given category outputs a degree of ...

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A system for generating macro-operators from static domain analysis

by Eloisa Vargiu and Giuliano Armano

Proceeding (453) Artificial Intelligence and Applications, 2005

A recommender system based on a generic contextual advertising approach

by Eloisa Vargiu, Giuliano Armano, and Andrea Addis

The IEEE symposium on …, Jun 22, 2010

Contextual advertising and automatic recommendation are emerging fields deeply studied by researc... more Contextual advertising and automatic recommendation are emerging fields deeply studied by researchers in information retrieval. So far, these fields have been separately investigated and several solutions have been independently proposed in the literature. Nevertheless, in our view, there are common issues that drive us to think that systems devised to solve one of the task above could be simply re-adapted to solve the other. In this paper, we propose a novel recommendation system based on a generic solution typically ...

Improving contextual advertising by adopting collaborative filtering

by Eloisa Vargiu and Giuliano Armano

ACM Transactions on the Web, 2013

ABSTRACT Contextual advertising can be viewed as an information filtering task aimed at selecting... more ABSTRACT Contextual advertising can be viewed as an information filtering task aimed at selecting suitable ads to be suggested to the final “user”, that is, the Web page in hand. Starting from this insight, in this article we propose a novel system, which adopts a collaborative filtering approach to perform contextual advertising. In particular, given a Web page, the system relies on collaborative filtering to classify the page content and to suggest suitable ads accordingly. Useful information is extracted from “inlinks”, that is, similar pages that link to the Web page in hand. In so doing, collaborative filtering is used in a content-based setting, giving rise to a hybrid contextual advertising system. After being implemented, the system has been experimented with about 15000 Web pages extracted from the Open Directory Project. Comparative experiments with a content-based system have been performed. The corresponding results highlight that the proposed system performs better. A suitable case study is also provided to enable the reader to better understand how the system works and its effectiveness.

DHG: a system for generating macro-operators from static domain analysis

by Eloisa Vargiu and Giuliano Armano

Proceedings of Artificial Intelligence and Applications (AIA), Feb 14, 2005

The attempt of dealing with the complexity of planning tasks by resorting to abstraction techniqu... more The attempt of dealing with the complexity of planning tasks by resorting to abstraction techniques is a central issue in the field of automated planning. Although the generality of the approach has not been proved always useful on domains selected for benchmarking purposes, in our opinion it will play a central role as soon as the focus will move from artificial to real problems. In this case, it will be crucial to have a tool for automatically generating abstraction hierarchies from a domain description. This paper ...

An Agent Approach to High Level Workflow Management in Functional Genomics

by Giuliano Armano, Luciano Milanesi, and Eloisa Vargiu

Proceedings of NETTAB, 2005

Materials and Methods Current workflow strategies deal with a network of nodes in which each node... more Materials and Methods Current workflow strategies deal with a network of nodes in which each node represent a particular application. This is an application-oriented view, in which the user is required to know details of each application in order to choose the best parameters and to configure the pipeline. These problems become relevant especially in workflows with a large number of applications.

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From a generic multiagent architecture to multiagent information retrieval systems

by Eloisa Vargiu, Giuliano Armano, and Andrea Addis

AT2AI-6, sixth international workshop, from agent theory to agent implementation, May 1, 2008

Information Retrieval, MultiAgent Systems, Applications way, automated content-based document man... more Information Retrieval, MultiAgent Systems, Applications way, automated content-based document management tasks [have gained a main task in the information systems ﬁeld [30]. In particular, web information retrieval is highly popular and presents a technical challenge due to the heterogeneity and size of the web, which is continuously growing (see [17],

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SLB: A Novel Protein Encoding Method for Secondary Structure Prediction

by Giuliano Armano and Eloisa Vargiu

Abstract: It is widely acknowledged that encoding methods play a fundamental role in the field of... more Abstract: It is widely acknowledged that encoding methods play a fundamental role in the field of protein secondary structure prediction, their task being to transform the available biological information in a form directly usable by the underlying predictor. This transformation is particularly critical, as the relationship between primary and secondary structure is very subtle and difficult to capture. In this paper we compare three different encoding methods and introduce a new encoding which we show to be superior. ...

Generating abstractions from static domain analysis

by Eloisa Vargiu and Giuliano Armano

Workshop dagli Oggetti agli Agenti-Sistemi Intelligenti e Computazione Pervasiva (WOA’03), Cagliari (Italy), 2003

Abstract—This paper addresses the problem of how to implement a proactive behavior according to a... more Abstract—This paper addresses the problem of how to implement a proactive behavior according to a two-tiered (ie, both theoretical and pragmatic) perspective. Theoretically, we claim that abstraction must be used to render agents able to solve complex problems. Pragmatically, we illustrate a technique devised to generate abstract spaces starting from a “ground” description of the domain being modeled.

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Monitoring Boats in Marine Reserves: A MAS Solution

by Giuliano Armano, Eloisa Vargiu, and Andrea Addis

10th Workshop dagli Oggetti agli Agenti (WOA 2009), 2009

The application of agent methodologies in process monitoring and control is a relatively novel ap... more The application of agent methodologies in process monitoring and control is a relatively novel approach, particularly suitable for distributed and dislocated systems. As for marine reservers, access monitoring is aimed at avoiding intrusions of unauthorized boats–also considering that, typically, marine reserves are located in areas not easily accessible. Typical solutions consist of using radar systems or suitable cameras activated by movement sensors. In this paper, we present a multiagent system aimed at monitoring boats in ...

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A Multiagent System for Retrieving Bioinformatics Publications From Web Sources

by Eloisa Vargiu, Giuliano Armano, and Andrea Addis

IEEE Transactions on Nanobioscience, 2000

A growing amount of information is currently being generated and stored in the World Wide Web (WW... more A growing amount of information is currently being generated and stored in the World Wide Web (WWW). In particular, researchers in any field can find a lot of publications and scientific literature. In our view, beyond conventional search engines, users need specific tools and methods for an effective use of the available scientific resources. In this way, personalization and information filtering techniques are primary features to be provided. In this paper, a multiagent system for extracting bioinformatics publications from web sources, and successively classifying them according to users interests, is presented. The system is built upon a generic architecture aimed at retrieving, filtering and managing information among different and heterogeneous information sources. To evaluate the performance of the system, several tests have been performed with publications extracted from the BMC Bioinformatics site and from the PubMed Central digital archive.

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Experimenting the Performance of Abstraction Mechanisms Through a Parametric Hierarchical Planner

by Eloisa Vargiu and Giuliano Armano

Applied Informatics, 2003

In this paper, the parametric hierarchical planner HW[] is presented, devised to perform experime... more In this paper, the parametric hierarchical planner HW[] is presented, devised to perform experiments on abstraction mechanisms. The system has been designed to embed any PDDL-compliant planner -to be considered as a "parameter" with respect to the overall planning system. By suitably switching between abstraction levels, HW[] exploits the embedded planner to search for solutions at any required level of abstraction. Some preliminary experiments are reported, performed on five domains taken from the AIPS 2002, 2000 and 1998 planning competitions. A step further in validating experimental results has been made by embedding two different planners. Comparative results, obtained by assessing the performances measured with and without abstraction, put into evidence that the hierarchical approach can significantly speed up the search.

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