1,721,129 research outputs found
Cerebral metabolism in the olfactory (dis)perception. In: consensus on mcs therapies and prevention strategies
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Personalized Search based on a Memory Retrieval Theory
No full textPersonalization is the ability to retrieve information content related to users' profile and facilitate their information-seeking activities. Several environments, such as the Web, take advantage of personalization techniques because of the large amount of available information. For this reason, there is a growing interest in providing automated personalization processes during the human-computer interaction.
In this paper we introduce a new approach for user modeling, which grounds in the Search of Associative Memory (SAM) theory. By means of implicit feedback techniques, the approach is able to unobtrusively recognize user needs and monitor the user working context in order to provide important information useful to personalize traditional search tools and implement recommender systems. Experimental results based on precision and recall measures indicate improvements in comparison with traditional user models
A Comparative Analysis of State-of-the-Art Recommendation Techniques in the Movie Domain
No full textRecommender systems (RSs) represent one of the manifold applications in which Machine Learning can unfold its potential. Nowadays, most of the major online sites selling products and services provide users with RSs that can assist them in their online experience. In recent years, therefore, we have witnessed an impressive series of proposals for novel recommendation techniques that claim to ensure significative improvements compared to classic techniques. In this work, we analyze some of them from a theoretical and experimental point of view and verify whether they can deliver tangible real improvements in terms of performance. Among others, we have experimented with traditional model-based and memory-based collaborative filtering, up to the most recent recommendation techniques based on deep learning. We have chosen the movie domain as an application scenario, and a version of the classic MovieLens as a dataset for training and testing our models
An Analysis of Trends and Connections in Google, Twitter, and Wikipedia
No full textIn this paper, we propose a system for extracting, storing, and analyzing the data provided by three well-known and widespread services available online. More specifically, the system can automatically collect a real-world dataset for a selected language and/or geographical region and match similar trends expressed through different keywords. Unlike previous studies in the same area, we avoided to focus on a specific aspect and explored which resonance different topics may have between one source and another, and how quickly each source generally reacts to external events
A comparative analysis of personality-based music recommender systems
No full textThis article describes a preliminary study on considering information about the target user's personality in music recommender systems (MRSs). For this purpose, we devised and implemented four MRSs and evaluated them on a sample of real users and real-world datasets. Experimental results show that MRSs that rely on purely users' personality information are able to provide performance comparable with those of a state-of-the-art MRS, even better in terms of the diversity of the suggested items
Personalized extended government for local public administrations
No full textThis paper discusses the enterprise organization environment and reports our experience and lessons learned in developing an extension of the traditional virtual enterprise model, we named personalized extended government (PEG) model. The aim of such model is to simplify and enhance the effectiveness of e-Government services, by realizing Administration to Administration (A2A) and Administration to Citizen (A2C) processes in a personalized perspective. The features of the proposed model make it suitable for use in local public administrations. As a proof of this, it has been successfully deployed to realize the Italian Open Government Data Portal of Regione Lazio, which allows every citizen to be informed about the employment of public resources on regional territory
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