1,721,143 research outputs found
MergeGraphs: a web-based system for merging heterogeneous big graphs
No full textThe quantity and quality of the information represented by means of graph structures is more and more increasing nowadays. Merging this information assumes a deep relevance in order to identify unknown relationships and properties and conduct different kinds of analysis. However, this task is complicated due to the variety of formats with which graphs are represented and their size. In this paper we propose mergeGraphs, a web based system in which the user can graphically drag and drop heterogeneous graphs and specify transformation and merging operations (union, intersection and join). The obtained execution plan is translated in Pig Latin scripts and executed in a cluster of machines. The use of Google App/Compute Engines allow to develop a scalable distributed approach
Protection and administration of XML data sources
No full textEXtensible Markup Language (XML) security has become a relevant research topic due to the widespread use of XML as the language for information interchange and document definition over the Web. In this context, developing an access control mechanism in terms of XML is an important step for Web information security. In this paper, we present the protection and administration facilities of Author-X, a Java-based system for discretionary access control to XML documents. Relevant features of Author-X are both a set-oriented and a document-oriented credential-based document protection, a differentiated protection of document/document type contents through the support of multi-granularity protection objects and positive/negative authorizations, and the support for different access control strategies. In this paper, we focus on the strategies we have developed for enforcing access control. Additionally, we provide a description of the environment we have developed to help the Security Officer in performing administrative activities related to both security policy and subject credential management
Making the analysis of the Italian legislative system easy : the ILMA web portal
Full text linkThe Italian Law-Making Archive, denoted ILMA, is a new web application for supporting the analysis of the Italian legislative processes. It aims to overcome the shortcomings that commonly affect quantitative analyses of legislative systems providing ready-to-use data on the Italian context organized in a relational structure and included in a unique repository. After having compared ILMA with other web information systems, the article describes the database architecture, proposes several examples of potential customized analyses that scholars may conduct through ILMA and, finally, explains its main functionalities for querying the database and exporting data
VisualPedia: Wiki per la didattica a supporto di strumenti con diverse forme di disabilità
No full textUser-centered recommendation services in Internet of things Era
No full textIn the Internet of Things era, we need to face increased masses of data, across all domains. Current researches have long been working to develop methods that help users to identify, extract, visualize and understand useful information from these huge masses of high dimensional and often weakly structured and/or non-standardized data. Our goal is to propose a solution for supporting users to interactively analyze such data flow and to visualize their most relevant parts through proper interaction style, without getting overwhelmed. In the paper, we describe a multi-level recommendation system (RS) by providing users with a decisionmaking process interactively accessible and by integrating it with social and crowdsourcing analysis, and interpretations that can lead to a new and meaningful use and presentation of data. to provide users with a decision-making process interactively accessible and enriched with social and crowdsourcing analysis tools, and interpretations that can lead to a new and meaningful use and presentation of data. The challenge is to enable effective human control over powerful machine algorithms based on a set of recommendation services used to filter data and choose proper data visualization and interaction style for supporting user’s insight, discoveries and decision making
Drug repositioning through pharmacological spaces integration based on networks projections
Full text linkMotivations. Drug development is a costly and failure-prone process and, in recent years, pharmaceutical industry has experienced a difficult period whereby productivity has not kept pace with increases in research and development costs. As a consequence, quite recently research efforts focused on a novel paradigm for drug development, named drug repurposing, to discover novel pharmacological applications of existing drugs. Computational approaches for drug repositioning focused mainly on small-scale applications, such as the analysis of specific classes of drugs or drugs for specific diseases. Large-scale applications, involving a relatively large number of drugs and diseases, count only a few examples. Despite the availability of many drug repositioning methods, they all suffer from a serious limitation: the inference task is performed in an inhomogeneous similarity space induced by the relationships existing between drugs and a second type of entity (e.g. disease, target, or ligand set), thus making difficult the integration of multiple sources of biomolecular and chemical data into a homogeneous pharmacological space.
Methods. To overcome this limitation we propose a general framework based on bipartite networks projections for the construction of homogeneous pharmacological spaces. The nature of these network structured projected spaces allows the application of prediction algorithms to homogeneous pharmacological spaces and improves the integration of different chemical, biomolecular and clinical sources of information. At the core of the proposed approach there is the notion of homogeneous pharmacological similarity space defined as a collection of similarities between drugs induced by common relationships between drugs and a second type of suitable entities (i.e. drug-protein target). The reconciliation between these heterogeneous similarity spaces is performed by means of a network projection operation enabling the reduction of a network composed by two types of nodes (i.e. drugs and drug targets) to a network composed only by drugs. A key feature of the proposed framework is its ability to integrate networks of different sizes, enabling the combination of both high and low coverage networks and resulting into a progressively enriched pharmacological similarity network. We also propose a novel and very fast kernelized semi-supervised network based method for ranking drugs according to their likelihood to belong to a given therapeutic category.
Results. We evaluated the proposed approach by integrating two pharmacological similarity spaces accounting, respectively, for chemical similarity and drug-targets interaction similarity, in order to rank about 1300 U.S. Food and Drug Administration (FDA) approved drugs according to DrugBank 3.0 therapeutic categories. The experimental setup is based on a canonical 5-fold cross validation scheme repeated 10 times. The analysis of the precision at fixed recall levels (see Figure), shows that the integration of pharmacological spaces constructed through the proposed network projections significantly enhances the results obtained with different network-based ranking methods. Moreover our proposed kernelized semi-supervised method for ranking drugs according to a given therapeutic category is at least comparable in terms of AUC and precision at fixed recall, and orders of magnitude faster than state-of-the-art ranking methods. Despite a thorough analysis of the results relative to each therapeutic category is out of the scope of this preliminary investigation, the analysis of the top ranked false positives predicted in three drug categories shows that our proposed approach can be successfully applied to discover potential drug candidates for novel therapeutic indications
A Trigger-Based Approach for Communication Personalization
No full textCommunication personalization is assuming more and more relevance nowadays. The possibility to specify policies for being reached from other people as well as policies for specifying means by which reaching other people is considered from the research community as well as the Telecommunication Companies. In this paper we present a policy language and its engine for specifying and enforcing policies for routing messages arriving at a subscribed user. These policies are on the characteristics of the actors involved in the communication process: the users, the devices they hold, the message/call, and the environment in which the communication occurs
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