Loredana Caruccio

Relaxed Functional Dependencies—A Survey of Approaches

Recently, there has been a renovated interest in functional dependencies due to the possibility of employing them in several advanced database operations, such as data cleaning, query relaxation, record matching, and so forth. In particular, the constraints defined for canonical functional dependencies have been relaxed to capture inconsistencies in real data, patterns of semantically related data, or semantic relationships in complex data types. In this paper, we have surveyed 35 of such functional dependencies, providing a classification criteria, motivating examples, and a systematic analysis of them.

Visual data integration based on description logic reasoning

Despite many innovative systems supporting the data integration process, designers advocate more abstract metaphors to master the inherent complexity of this activity. In fact, the visual notations provided in many modern data integration systems might run into scale up problems when facing the integration of big data sources. Thus, higher level visual notations and automatic schema mapping mechanisms might be the key factors to make the data integration process more tractable. In this paper we present the Conceptual Data Integration Language (CoDIL), a visual language providing conceptual level visual mechanisms to manipulate and integrate data sources, together with a formalization of the language icon operators by means of ALCN Description Logic. The formalization allowed us to define the logic-level semantics of CoDIL, providing reasoning rules for validating the correctness of a data integration process and for generating the logic-level reconciled schema.

Understanding user intent on the web through interaction mining

Predicting the goals of internet users can be extremely useful in e-commerce, online entertainment, and many other internet-based applications. One of the crucial steps to achieve this is to classify internet queries based on available features, such as contextual information, keywords and their semantic relationships. Beyond these methods, in this paper we propose to mine user interaction activities to predict the intent of the user during a navigation session. However, since in practice it is necessary to use a suitable mix of all such methods, it is important to exploit all the mentioned features in order to properly classify users based on their common intents. To this end, we have performed several experiments aiming to empirically derive a suitable classifier based on the mentioned features.

Synchronization of Queries and Views Upon Schema Evolutions: A Survey

One of the problems arising upon the evolution of a database schema is that some queries and views defined on the previous schema version might no longer work properly. Thus, evolving a database schema entails the redefinition of queries and views to adapt them to the new schema. Although this problem has been mainly raised in the context of traditional information systems, solutions to it are also advocated in other database-related areas, such as Data Integration, Web Data Integration, and Data Warehouses. The problem is a critical one, since industrial organizations often need to adapt their databases and data warehouses to frequent changes in the real world. In this article, we provide a survey of existing approaches and tools to the problem of adapting queries and views upon a database schema evolution; we also propose a classification framework to enable a uniform comparison method among many heterogeneous approaches and tools.

On the Discovery of Relaxed Functional Dependencies

Functional dependencies (fds) express important relationships among data, which can be used for several goals, including schema normalization and data cleansing. However, to solve several issues in emerging application domains, such as the identification of data inconsistencies or patterns of semantically related data, it has been necessary to relax the fd definition through the introduction of approximations in data comparison and/or validity. Moreover, while fds were originally specified at design time, with the availability of massive data and computational power many algorithms have been devised to automatically discover them from data, including algorithms for discovering some types of relaxed fds. In this paper we present a technique that exploits lattice-based algorithms for the discovery of fds from data, in order to detect relaxed fds. Moreover, we introduce an algorithm to determine a proper distance threshold for a given relaxed fd holding over the entire database.

Evolutionary mining of relaxed dependencies from big data collections

Many modern application contexts, especially those related to the semantic Web, advocate for automatic techniques capable of extracting relationships between semi-structured data, for several purposes, such as the identification of inconsistencies or patterns of semantically related data, query rewriting, and so forth. One way to represent such relationships is to use relaxed functional dependencies (rfds), since they can embed approximate matching paradigms to compare unstructured data, and admit the possibility of exceptions for them. To this end, thresholds might need to be specified in order to limit the similarity degree in approximate comparisons or the occurrence of exceptions. Thanks to the availability of huge amount of data, including unstructured data available on the Web, nowadays it is possible to automatically discover rfds from data. However, due to the many different combinations of similarity and exception thresholds, the discovery process has an exponential complexity. Thus, it is vital devising proper optimization strategies, in order to make the discovery process feasible. To this end, in this paper, we propose a genetic algorithm to discover rfds from data, also providing an empirical evaluation demonstrating its effectiveness.

A tool supporting end-user development of access control in web applications

End-user development (EUD) is drawing an increasing attention due to the necessity of users to frequently extend and personalize their applications. In particular, EUD in the context of Web (EUDWeb...

Supporting Access Control within a Mockup-based EUDWeb Environment

End-user development (EUD) is receiving increasing attention, due to the necessity of frequent extensions and personalizations of applications. In particular, EUDWeb technologies have focused on the support of web development tasks which are generally perceived to be complex by end-user developers. However an area of neglect within current EUDWeb environments is the support for the specification and implementation of access control, although it is perceived as a particularly complex task. Thus, in this paper we propose an EUDWeb approach and tool for the specification and generation of web applications embedding access control mechanisms. We extended a previous mockup-based EUDWeb approach by introducing visual assistance mechanisms enabling the specification of role-based access control policies and their plugging within the application logic.

A Wizard Based EUDWeb Development Process

The pervasiveness of technological media in the daily life of the people has given rise to the end-user development (EUD) research area, which aims to empower end-users to be developers of their applications. The moving towards Web technologies introduced further challenges for EUD researchers. With respect to the significant number of solutions that have been developed, including methodologies and tools, little effort has been produced to support end-users in a proper development process of their applications. In this paper, we propose a wizard-based development process guiding the users towards the construction of own Web applications (Webapps), letting them accomplish complex tasks, such as those related to security and access control.

A sketch-based conceptual level data integration methodology

Nowadays, enterprises often need to integrate heterogeneous data sources for many purposes. Given the inherent complexity of this process, several solutions based on visual manipulation paradigms have been proposed to shoot at the complexity of low-level data integration activities. However, when dealing with complex data sources the use of visual notations might suffer from scale-up problems. One way to solve this problem is to raise the data integration activity at more an abstract level. In this paper, we present a methodology for reconciling data sources at the level of their conceptual Schemas. The methodology provides a sketch-based language for manipulating conceptual Schemas, a tool prototype, and logic based inference mechanisms to handle lower level schema integration, metadata generation, and loading of data from sources to the reconciled database. We also provide a usability study to prove the effectiveness of the proposed methodology.