<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ferretti, Michele</style></author><author><style face="normal" font="default" size="100%">Barlacchi, Gianni</style></author><author><style face="normal" font="default" size="100%">Luca Pappalardo</style></author><author><style face="normal" font="default" size="100%">Lucchini, Lorenzo</style></author><author><style face="normal" font="default" size="100%">Lepri, Bruno</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Weak nodes detection in urban transport systems: Planning for resilience in Singapore</style></title><secondary-title><style face="normal" font="default" size="100%">2018 IEEE 5th international conference on data science and advanced analytics (DSAA)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/abstract/document/8631413/authors#authors</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The availability of massive data-sets describing human mobility offers the possibility to design simulation tools to monitor and improve the resilience of transport systems in response to traumatic events such as natural and man-made disasters (e.g., floods, terrorist attacks, etc. . . ). In this perspective, we propose ACHILLES, an application to models people's movements in a given transport mode through a multiplex network representation based on mobility data. ACHILLES is a web-based application which provides an easy-to-use interface to explore the mobility fluxes and the connectivity of every urban zone in a city, as well as to visualize changes in the transport system resulting from the addition or removal of transport modes, urban zones, and single stops. Notably, our application allows the user to assess the overall resilience of the transport network by identifying its weakest node, i.e. Urban Achilles Heel, with reference to the ancient Greek mythology. To demonstrate the impact of ACHILLES for humanitarian aid we consider its application to a real-world scenario by exploring human mobility in Singapore in response to flood prevention.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Riccardo Guidotti</style></author><author><style face="normal" font="default" size="100%">Michele Berlingerio</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Where Is My Next Friend? Recommending Enjoyable Profiles in Location Based Services</style></title><secondary-title><style face="normal" font="default" size="100%">Complex Networks VII</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><pages><style face="normal" font="default" size="100%">65–78</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">How many of your friends, with whom you enjoy spending some time, live close by? How many people are at your reach, with whom you could have a nice conversation? We introduce a measure of enjoyability that may be the basis for a new class of location-based services aimed at maximizing the likelihood that two persons, or a group of people, would enjoy spending time together. Our enjoyability takes into account both topic similarity between two users and the users’ tendency to connect to people with similar or dissimilar interest. We computed the enjoyability on two datasets of geo-located tweets, and we reasoned on the applicability of the obtained results for producing friend recommendations. We aim at suggesting couples of users which are not friends yet, but which are frequently co-located and maximize our enjoyability measure. By taking into account the spatial dimension, we show how 50 % of users may find at least one enjoyable person within 10 km of their two most visited locations. Our results are encouraging, and open the way for a new class of recommender systems based on enjoyability.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">S Rinzivillo</style></author><author><style face="normal" font="default" size="100%">Fernando de Lucca Siqueira</style></author><author><style face="normal" font="default" size="100%">Lorenzo Gabrielli</style></author><author><style face="normal" font="default" size="100%">Chiara Renso</style></author><author><style face="normal" font="default" size="100%">Vania Bogorny</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Where Have You Been Today? Annotating Trajectories with DayTag</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on Spatial and Spatio-temporal Databases (SSTD)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><pages><style face="normal" font="default" size="100%">467-471</style></pages></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Igo Brilhante</style></author><author><style face="normal" font="default" size="100%">Franco Maria Nardini</style></author><author><style face="normal" font="default" size="100%">Raffaele Perego</style></author><author><style face="normal" font="default" size="100%">Chiara Renso</style></author><author><style face="normal" font="default" size="100%">de José Antônio Fernandes Macêdo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Where Shall We Go Today? Planning Touristic Tours with TripBuilder</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference CIKM 2013</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><pub-location><style face="normal" font="default" size="100%">San Francisco, USA</style></pub-location></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Franco Turini</style></author><author><style face="normal" font="default" size="100%">Barbara Furletti</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">What else can be extracted from ontologies? Influence Rules</style></title><secondary-title><style face="normal" font="default" size="100%">Software and Data Technologies</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Communications in Computer and Information Science</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Romano, Maria Francesca</style></author><author><style face="normal" font="default" size="100%">Michela Natilli</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Wine and Food Tourism First European Conference</style></title><secondary-title><style face="normal" font="default" size="100%">Edizioni ETS Pisa</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Daniel Marbach</style></author><author><style face="normal" font="default" size="100%">J.C. Costello</style></author><author><style face="normal" font="default" size="100%">Robert Küffner</style></author><author><style face="normal" font="default" size="100%">N.M. Vega</style></author><author><style face="normal" font="default" size="100%">R.J. Prill</style></author><author><style face="normal" font="default" size="100%">D.M. Camacho</style></author><author><style face="normal" font="default" size="100%">K.R. Allison</style></author><author><style face="normal" font="default" size="100%">Manolis Kellis</style></author><author><style face="normal" font="default" size="100%">J.J. Collins</style></author><author><style face="normal" font="default" size="100%">Gustavo Stolovitzky</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">DREAM5 Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Wisdom of crowds for robust gene network inference.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Methods</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat. Methods</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012 Aug</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">796-804</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Reconstructing gene regulatory networks from high-throughput data is a long-standing challenge. Through the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we performed a comprehensive blind assessment of over 30 network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae and in silico microarray data. We characterize the performance, data requirements and inherent biases of different inference approaches, and we provide guidelines for algorithm application and development. We observed that no single inference method performs optimally across all data sets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse data sets. We thereby constructed high-confidence networks for E. coli and S. aureus, each comprising ~1,700 transcriptional interactions at a precision of ~50%. We experimentally tested 53 previously unobserved regulatory interactions in E. coli, of which 23 (43%) were supported. Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Daniel Marbach</style></author><author><style face="normal" font="default" size="100%">J.C. Costello</style></author><author><style face="normal" font="default" size="100%">Robert Küffner</style></author><author><style face="normal" font="default" size="100%">N.M. Vega</style></author><author><style face="normal" font="default" size="100%">R.J. Prill</style></author><author><style face="normal" font="default" size="100%">D.M. Camacho</style></author><author><style face="normal" font="default" size="100%">K.R. Allison</style></author><author><style face="normal" font="default" size="100%">Manolis Kellis</style></author><author><style face="normal" font="default" size="100%">J.J. Collins</style></author><author><style face="normal" font="default" size="100%">Aderhold, A.</style></author><author><style face="normal" font="default" size="100%">Gustavo Stolovitzky</style></author><author><style face="normal" font="default" size="100%">Bonneau, R.</style></author><author><style face="normal" font="default" size="100%">Chen, Y.</style></author><author><style face="normal" font="default" size="100%">Cordero, F.</style></author><author><style face="normal" font="default" size="100%">Martin Crane</style></author><author><style face="normal" font="default" size="100%">Dondelinger, F.</style></author><author><style face="normal" font="default" size="100%">Drton, M.</style></author><author><style face="normal" font="default" size="100%">Esposito, R.</style></author><author><style face="normal" font="default" size="100%">Foygel, R.</style></author><author><style face="normal" font="default" size="100%">De La Fuente, A.</style></author><author><style face="normal" font="default" size="100%">Gertheiss, J.</style></author><author><style face="normal" font="default" size="100%">Geurts, P.</style></author><author><style face="normal" font="default" size="100%">Greenfield, A.</style></author><author><style face="normal" font="default" size="100%">Grzegorczyk, M.</style></author><author><style face="normal" font="default" size="100%">Haury, A.-C.</style></author><author><style face="normal" font="default" size="100%">Holmes, B.</style></author><author><style face="normal" font="default" size="100%">Hothorn, T.</style></author><author><style face="normal" font="default" size="100%">Husmeier, D.</style></author><author><style face="normal" font="default" size="100%">Huynh-Thu, V.A.</style></author><author><style face="normal" font="default" size="100%">Irrthum, A.</style></author><author><style face="normal" font="default" size="100%">Karlebach, G.</style></author><author><style face="normal" font="default" size="100%">Lebre, S.</style></author><author><style face="normal" font="default" size="100%">De Leo, V.</style></author><author><style face="normal" font="default" size="100%">Madar, A.</style></author><author><style face="normal" font="default" size="100%">Mani, S.</style></author><author><style face="normal" font="default" size="100%">Mordelet, F.</style></author><author><style face="normal" font="default" size="100%">Ostrer, H.</style></author><author><style face="normal" font="default" size="100%">Ouyang, Z.</style></author><author><style face="normal" font="default" size="100%">Pandya, R.</style></author><author><style face="normal" font="default" size="100%">Petri, T.</style></author><author><style face="normal" font="default" size="100%">Pinna, A.</style></author><author><style face="normal" font="default" size="100%">Poultney, C.S.</style></author><author><style face="normal" font="default" size="100%">Rezny, S.</style></author><author><style face="normal" font="default" size="100%">Heather J Ruskin</style></author><author><style face="normal" font="default" size="100%">Saeys, Y.</style></author><author><style face="normal" font="default" size="100%">Shamir, R.</style></author><author><style face="normal" font="default" size="100%">Alina Sirbu</style></author><author><style face="normal" font="default" size="100%">Song, M.</style></author><author><style face="normal" font="default" size="100%">Soranzo, N.</style></author><author><style face="normal" font="default" size="100%">Statnikov, A.</style></author><author><style face="normal" font="default" size="100%">N.M. Vega</style></author><author><style face="normal" font="default" size="100%">Vera-Licona, P.</style></author><author><style face="normal" font="default" size="100%">Vert, J.-P.</style></author><author><style face="normal" font="default" size="100%">Visconti, A.</style></author><author><style face="normal" font="default" size="100%">Haizhou Wang</style></author><author><style face="normal" font="default" size="100%">Wehenkel, L.</style></author><author><style face="normal" font="default" size="100%">Windhager, L.</style></author><author><style face="normal" font="default" size="100%">Zhang, Y.</style></author><author><style face="normal" font="default" size="100%">Zimmer, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Wisdom of crowds for robust gene network inference</style></title><secondary-title><style face="normal" font="default" size="100%">Nature Methods</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.scopus.com/inward/record.url?eid=2-s2.0-84870305264&amp;partnerID=40&amp;md5=04a686572bdefff60157bf68c95df7ea</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">8</style></number><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">796-804</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">S Rinzivillo</style></author><author><style face="normal" font="default" size="100%">Salvatore Ruggieri</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Who/Where Are My New Customers?</style></title><secondary-title><style face="normal" font="default" size="100%">ISMIS Industrial Session</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><pages><style face="normal" font="default" size="100%">307-317</style></pages></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Anna Monreale</style></author><author><style face="normal" font="default" size="100%">Fabio Pinelli</style></author><author><style face="normal" font="default" size="100%">Roberto Trasarti</style></author><author><style face="normal" font="default" size="100%">Fosca Giannotti</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">WhereNext: a Location Predictor on Trajectory Pattern Mining</style></title><secondary-title><style face="normal" font="default" size="100%">15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><abstract><style face="normal" font="default" size="100%">The pervasiveness of mobile devices and location based services is leading to an increasing volume of mobility data.This side eect provides the opportunity for innovative methods that analyse the behaviors of movements. In this paper we propose WhereNext, which is a method aimed at predicting with a certain level of accuracy the next location of a moving object. The prediction uses previously extracted movement patterns named Trajectory Patterns, which are a concise representation of behaviors of moving objects as sequences of regions frequently visited with a typical travel time. A decision tree, named T-pattern Tree, is built and evaluated with a formal training and test process. The tree is learned from the Trajectory Patterns that hold a certain area and it may be used as a predictor of the next location of a new trajectory finding the best matching path in the tree. Three dierent best matching methods to classify a new moving object are proposed and their impact on the quality of prediction is studied extensively. Using Trajectory Patterns as predictive rules has the following implications: (I) the learning depends on the movement of all available objects in a certain area instead of on the individual history of an object; (II) the prediction tree intrinsically contains the spatio-temporal properties that have emerged from the data and this allows us to define matching methods that striclty depend on the properties of such movements. In addition, we propose a set of other measures, that evaluate a priori the predictive power of a set of Trajectory Patterns. This measures were tuned on a real life case study. Finally, an exhaustive set of experiments and results on the real dataset are presented.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Romano, Maria Francesca</style></author><author><style face="normal" font="default" size="100%">Michela Natilli</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Wine tourism in Italy: New profiles, styles of consumption, ways of touring</style></title><secondary-title><style face="normal" font="default" size="100%">Turizam: međunarodni znanstveno-stručni časopis</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">57</style></volume><pages><style face="normal" font="default" size="100%">463–475</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Chiara Renso</style></author><author><style face="normal" font="default" size="100%">Simone Puntoni</style></author><author><style face="normal" font="default" size="100%">E. Frentzos</style></author><author><style face="normal" font="default" size="100%">Andrea Mazzoni</style></author><author><style face="normal" font="default" size="100%">Bart Moelans</style></author><author><style face="normal" font="default" size="100%">Nikos Pelekis</style></author><author><style face="normal" font="default" size="100%">F. Pini</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Wireless Network Data Sources: Tracking and Synthesizing Trajectories</style></title><secondary-title><style face="normal" font="default" size="100%">Mobility, Data Mining and Privacy</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><pages><style face="normal" font="default" size="100%">73-100</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fosca Giannotti</style></author><author><style face="normal" font="default" size="100%">Mirco Nanni</style></author><author><style face="normal" font="default" size="100%">Dino Pedreschi</style></author><author><style face="normal" font="default" size="100%">F. Samaritani</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">WebCat: Automatic Categorization of Web Search Results</style></title><secondary-title><style face="normal" font="default" size="100%">SEBD</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><pages><style face="normal" font="default" size="100%">507-518</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Francesco Bonchi</style></author><author><style face="normal" font="default" size="100%">Fosca Giannotti</style></author><author><style face="normal" font="default" size="100%">Cristian Gozzi</style></author><author><style face="normal" font="default" size="100%">Giuseppe Manco</style></author><author><style face="normal" font="default" size="100%">Mirco Nanni</style></author><author><style face="normal" font="default" size="100%">Dino Pedreschi</style></author><author><style face="normal" font="default" size="100%">Chiara Renso</style></author><author><style face="normal" font="default" size="100%">Salvatore Ruggieri</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Web Log Data Warehousing and Mining for Intelligent Web Caching</style></title><secondary-title><style face="normal" font="default" size="100%">Data and Knowledge Engineering</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">39:165, November .</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Francesco Bonchi</style></author><author><style face="normal" font="default" size="100%">Fosca Giannotti</style></author><author><style face="normal" font="default" size="100%">Cristian Gozzi</style></author><author><style face="normal" font="default" size="100%">Giuseppe Manco</style></author><author><style face="normal" font="default" size="100%">Mirco Nanni</style></author><author><style face="normal" font="default" size="100%">Dino Pedreschi</style></author><author><style face="normal" font="default" size="100%">Chiara Renso</style></author><author><style face="normal" font="default" size="100%">Salvatore Ruggieri</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Web log data warehousing and mining for intelligent web caching</style></title><secondary-title><style face="normal" font="default" size="100%">Data Knowl. Eng.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">165-189</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Francesco Bonchi</style></author><author><style face="normal" font="default" size="100%">Fosca Giannotti</style></author><author><style face="normal" font="default" size="100%">Cristian Gozzi</style></author><author><style face="normal" font="default" size="100%">Giuseppe Manco</style></author><author><style face="normal" font="default" size="100%">Mirco Nanni</style></author><author><style face="normal" font="default" size="100%">Dino Pedreschi</style></author><author><style face="normal" font="default" size="100%">Chiara Renso</style></author><author><style face="normal" font="default" size="100%">Salvatore Ruggieri</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Web log data warehousing and mining for intelligent web caching</style></title><secondary-title><style face="normal" font="default" size="100%">Data Knowl. Eng.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">165-189</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dino Pedreschi</style></author><author><style face="normal" font="default" size="100%">Salvatore Ruggieri</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Weakest Preconditions for Pure Prolog Programs</style></title><secondary-title><style face="normal" font="default" size="100%">Inf. Process. Lett.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">67</style></volume><pages><style face="normal" font="default" size="100%">145-150</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. Chiarelli</style></author><author><style face="normal" font="default" size="100%">V. Mazzotta</style></author><author><style face="normal" font="default" size="100%">Chiara Renso</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A WAM Estesa per la Composizione di Programi Logici</style></title><secondary-title><style face="normal" font="default" size="100%">GULP</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1993</style></year></dates><pages><style face="normal" font="default" size="100%">189-202</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>