Matteo Magnani

The ML-Model for Multi-layer Social Networks

In this paper we introduce a new model to represent an interconnected network of networks. This model is fundamental to reason about the real organization of on-line social networks, where users belong to and interact on different networks at the same time. In addition we extend traditional SNA measures to deal with this multiplicity of networks and we apply the model to a real dataset extracted from two microblogging sites.

Schema integration based on uncertain semantic mappings

Schema integration is the activity of providing a unified representation of multiple data sources. The core problems in schema integration are: schema matching, i.e. the identification of correspondences, or mappings, between schema objects, and schema merging, i.e. the creation of a unified schema based on the identified mappings. Existing schema matching approaches attempt to identify a single mapping between each pair of objects, for which they are 100% certain of its correctness. However, this is impossible in general, thus a human expert always has to validate or modify it. In this paper, we propose a new schema integration approach where the uncertainty in the identified mappings that is inherent in the schema matching process is explicitly represented, and that uncertainty propagates to the schema merging process, and finally it is depicted in the resulting integrated schema.

A Survey on Uncertainty Management in Data Integration

In the last few years, uncertainty management has come to be recognized as a fundamental aspect of data integration. It is now accepted that it may not be possible to remove uncertainty generated during data integration processes and that uncertainty in itself may represent a source of relevant information. Several issues, such as the aggregation of uncertain mappings and the querying of uncertain mediated schemata, have been addressed by applying well-known uncertainty management theories. However, several problems lie unresolved. This article sketches an initial picture of this highly active research area; it details existing works in the light of a homogeneous framework, and identifies and discusses the leading issues awaiting solutions.

Social network data and practices: the case of friendfeed

Due to their large worldwide adoption, Social Network Sites (SNSs) have been widely used in many global events as an important source to spread news and information. While the searchability and persistence of this information make it ideal for sociological research, a quantitative approach is still challenging because of the size and complexity of the data. In this paper we provide a first analysis of Friendfeed, a well-known and feature-rich SNS.

BPMN: how much does it cost? an incremental approach

In this paper we propose some extensions of the businessprocess modeling notation (BPMN) to be able to evaluate the overallcost of business process diagrams. The BPMN is very expressive, and ageneral treatment of this problem is very complex. Therefore, it seemsreasonable to define classes of business process diagrams capturing realprocesses and to develop efficient analysis methods for these classes. Inthe paper we define some relevant subsets of the BPMN, extend themwith the concept of cost, and provide computational models for eachclass, in most cases reducing them to existing problems for which efficientsolutions already exist.

Information Propagation Analysis in a Social Network Site

One of the most interesting and still not completely understood phenomena happening in Social Network Sites is their ability to spread (or not) units of information which may aggregate to form large distributed conversations. In this paper we present the result of an empirical study on a Large Social Database (LSD) aimed at measuring the factors enabling information spreading in Social Network Sites.

Friendfeed Breaking News: Death of a Public Figure

Microblogging sites allow users to post short messages online, offering a reliable way to communicate and to spread information quickly and efficiently; moreover, they can host complex conversational activities. The objectives of this paper are to model how breaking news circulate in a microblogging network, to identify relevant patterns of news propagation and to increase our understanding of the underlying sociological motivations. This study has been conducted on a real social database collected from a well known microblogging site by observing the reactions of its users to a relevant public event.

A unified approach to structured and XML data modeling and manipulation

In this paper we propose an approach to defining logical database models, based on the instantiation of a general abstract model, and discuss its application to the management of mixed XML/relational data. Our abstract model is equipped with a parametric query algebra and relational-like algebraic equivalences, that do not have to be redefined when new models are generated. We present an instantiation of our model that unifies the main approaches to represent and manipulate relational and XML data, and in particular SQL, SQL/XML, XQuery, and Oracles XML Type. Additionally, our algebra can represent queries not expressible by other algebras taken from the literature. Among others, it can represent nested XQuery expressions with no constraints on nesting and on node constructors.

Conversation retrieval from twitter

The process of retrieving conversations from social network sites differs from traditional Web information retrieval because it involves human communication aspects, like the degree of interest in the conversation explicitly or implicitly expressed by the interacting people and their influence/popularity. Our demo allows users to include these aspects into the search process. The system allows the retrieval of millions of conversations generated on the popular Twitter social network site, and in particular conversations about trending topics.

XML and relational data: towards a common model and algebra

In this paper we present a model for the management of relational, XML, and mixed data. The main high-level approaches to manipulate XML, i.e., SQL/XML, XQuery, and object/relational XML columns, can all be based on our common model and algebra. Our query algebra, yet very simple, can represent queries not expressible by other proposals and by the current implementation of TAX. Moreover, we show that relational-like logical query rewriting can be extended to our algebraic expressions.