�ݺ�ߣshows by User: augustopucci

�ݺ�ߣshows by User: augustopucci / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: augustopucci / Tue, 31 Mar 2009 05:06:45 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: augustopucci WIC2006 - Research Paper Recommender Systems: A Random-Walk Based Approach /slideshow/wic2006-research-paper-recommender-systems-a-randomwalk-based-approach/1226463 wic2006-090331050647-phpapp02
Every day researchers from all over the world have to filter the huge mass of existing research papers with the crucial aim of finding out useful publications related to their current work. In this paper we propose a research paper recommending algorithm based on the Citation Graph and random-walker properties. The PaperRank algorithm is able to assign a preference score to a set of documents contained in a digital library and linked one each other by bibliographic references. A data set of papers extracted by ACM Portal has been used for testing and very promising performances have been measured.]]>
Every day researchers from all over the world have to filter the huge mass of existing research papers with the crucial aim of finding out useful publications related to their current work. In this paper we propose a research paper recommending algorithm based on the Citation Graph and random-walker properties. The PaperRank algorithm is able to assign a preference score to a set of documents contained in a digital library and linked one each other by bibliographic references. A data set of papers extracted by ACM Portal has been used for testing and very promising performances have been measured.]]> Tue, 31 Mar 2009 05:06:45 GMT /slideshow/wic2006-research-paper-recommender-systems-a-randomwalk-based-approach/1226463 augustopucci@slideshare.net(augustopucci) WIC2006 - Research Paper Recommender Systems: A Random-Walk Based Approach augustopucci Every day researchers from all over the world have to filter the huge mass of existing research papers with the crucial aim of finding out useful publications related to their current work. In this paper we propose a research paper recommending algorithm based on the Citation Graph and random-walker properties. The PaperRank algorithm is able to assign a preference score to a set of documents contained in a digital library and linked one each other by bibliographic references. A data set of papers extracted by ACM Portal has been used for testing and very promising performances have been measured. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/wic2006-090331050647-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Every day researchers from all over the world have to filter the huge mass of existing research papers with the crucial aim of finding out useful publications related to their current work. In this paper we propose a research paper recommending algorithm based on the Citation Graph and random-walker properties. The PaperRank algorithm is able to assign a preference score to a set of documents contained in a digital library and linked one each other by bibliographic references. A data set of papers extracted by ACM Portal has been used for testing and very promising performances have been measured.

WIC2006 - Research Paper Recommender Systems: A Random-Walk Based Approach from Augusto Pucci, PhD

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0 ESANN2006 - A Cyclostationary Neural Network model for the prediction of the NO2 concentration /slideshow/esann2006-a-cyclostationary-neural-network-model-for-the-prediction-of-the-no2-concentration/1226458 esann2006-090331050433-phpapp02
Air pollution control is a major environmental concern. The quality of air is an important factor for everyday life in cities, since it affects the health of the community and directly influences the sustainability of our lifestyles and production methods. In this paper we propose a cyclostationary neural network (CNN) model for the prediction of the NO2 concentration. The cyclostationary nature of the problem guides the construction of the CNN architecture, which is composed by a number of MLP blocks equal to the cyclostationary period in the analyzed phenomenon, and is independent of exogenous inputs. Some preliminary experimentation shows that the CNN model significantly outperforms standard statistical tools usually employed for this task.]]>
Air pollution control is a major environmental concern. The quality of air is an important factor for everyday life in cities, since it affects the health of the community and directly influences the sustainability of our lifestyles and production methods. In this paper we propose a cyclostationary neural network (CNN) model for the prediction of the NO2 concentration. The cyclostationary nature of the problem guides the construction of the CNN architecture, which is composed by a number of MLP blocks equal to the cyclostationary period in the analyzed phenomenon, and is independent of exogenous inputs. Some preliminary experimentation shows that the CNN model significantly outperforms standard statistical tools usually employed for this task.]]> Tue, 31 Mar 2009 05:04:32 GMT /slideshow/esann2006-a-cyclostationary-neural-network-model-for-the-prediction-of-the-no2-concentration/1226458 augustopucci@slideshare.net(augustopucci) ESANN2006 - A Cyclostationary Neural Network model for the prediction of the NO2 concentration augustopucci Air pollution control is a major environmental concern. The quality of air is an important factor for everyday life in cities, since it affects the health of the community and directly influences the sustainability of our lifestyles and production methods. In this paper we propose a cyclostationary neural network (CNN) model for the prediction of the NO2 concentration. The cyclostationary nature of the problem guides the construction of the CNN architecture, which is composed by a number of MLP blocks equal to the cyclostationary period in the analyzed phenomenon, and is independent of exogenous inputs. Some preliminary experimentation shows that the CNN model significantly outperforms standard statistical tools usually employed for this task. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/esann2006-090331050433-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Air pollution control is a major environmental concern. The quality of air is an important factor for everyday life in cities, since it affects the health of the community and directly influences the sustainability of our lifestyles and production methods. In this paper we propose a cyclostationary neural network (CNN) model for the prediction of the NO2 concentration. The cyclostationary nature of the problem guides the construction of the CNN architecture, which is composed by a number of MLP blocks equal to the cyclostationary period in the analyzed phenomenon, and is independent of exogenous inputs. Some preliminary experimentation shows that the CNN model significantly outperforms standard statistical tools usually employed for this task.

ESANN2006 - A Cyclostationary Neural Network model for the prediction of the NO2 concentration from Augusto Pucci, PhD

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0 Microsoft - Volatility modeling and analysis /slideshow/microsoft-volatility-modeling-and-analysis/1226442 msft-090331045959-phpapp02
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A ga]]> Tue, 31 Mar 2009 04:59:58 GMT /slideshow/microsoft-volatility-modeling-and-analysis/1226442 augustopucci@slideshare.net(augustopucci) Microsoft - Volatility modeling and analysis augustopucci A ga <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/msft-090331045959-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> A ga

Microsoft - Volatility modeling and analysis from Augusto Pucci, PhD

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0 Webkdd2006 /slideshow/webkdd2006-presentation/971032 webkdd2006-1233317516062718-3
"A Random-Walk Based Scoring Algorithm Applied to Recommender Engines" Presentation at WebKDD2006 conference.]]>
"A Random-Walk Based Scoring Algorithm Applied to Recommender Engines" Presentation at WebKDD2006 conference.]]> Fri, 30 Jan 2009 06:16:25 GMT /slideshow/webkdd2006-presentation/971032 augustopucci@slideshare.net(augustopucci) Webkdd2006 augustopucci "A Random-Walk Based Scoring Algorithm Applied to Recommender Engines" Presentation at WebKDD2006 conference. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/webkdd2006-1233317516062718-3-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> "A Random-Walk Based Scoring Algorithm Applied to Recommender Engines" Presentation at WebKDD2006 conference.

Webkdd2006 from Augusto Pucci, PhD

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0 https://cdn.slidesharecdn.com/profile-photo-augustopucci-48x48.jpg?cb=1536232671 Currently working in the Internet and Mobile Banking unit within the Digital and Physical Banking Area at Banca Monte dei Paschi di Siena. In my previous role as Online Banking Specialist at UniCredit Business Integrated Solutions, I had been involved in the new Global Internet and Mobile Banking program (Italy, Austria, Germany), applying the Agile Scrum practice. I was also in charge for Bank Austria Internet Banking asset acting as Key Professional. In my previous experience as Head of Organizational Development at Biverbanca, and former PMO for the same company, I have been in charge for strategic projects including business plan definition, organizational re-design, company core pr... it.linkedin.com/in/augustopucci https://cdn.slidesharecdn.com/ss_thumbnails/wic2006-090331050647-phpapp02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/wic2006-research-paper-recommender-systems-a-randomwalk-based-approach/1226463 WIC2006 - Research Pap... https://cdn.slidesharecdn.com/ss_thumbnails/esann2006-090331050433-phpapp02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/esann2006-a-cyclostationary-neural-network-model-for-the-prediction-of-the-no2-concentration/1226458 ESANN2006 - A Cyclosta... https://cdn.slidesharecdn.com/ss_thumbnails/msft-090331045959-phpapp02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/microsoft-volatility-modeling-and-analysis/1226442 Microsoft - Volatility...