Reviews

Diane BLAKEMORE, Understanding utterance

Reviews

Andrew RADFORD, Syntactic theory and the acquisition of English syntax : the nature of early child grammars of Englis

Privacy-preserving data outsourcing in the cloud via semantic data splitting

Even though cloud computing provides many intrinsic benefits, privacy concerns related to the lack of control over the storage and management of the outsourced data still prevent many customers from migrating to the cloud. Several privacy-protection mechanisms based on a prior encryption of the data to be outsourced have been proposed. Data encryption offers robust security, but at the cost of hampering the efficiency of the service and limiting the functionalities that can be applied over the (encrypted) data stored on cloud premises. Because both efficiency and functionality are crucial advantages of cloud computing, in this paper we aim at retaining them by proposing a privacy-protection mechanism that relies on splitting (clear) data, and on the distributed storage offered by the increasingly popular notion of multi-clouds. We propose a semantically-grounded data splitting mechanism that is able to automatically detect pieces of data that may cause privacy risks and split them on local premises, so that each chunk does not incur in those risks; then, chunks of clear data are independently stored into the separate locations of a multi-cloud, so that external entities cannot have access to the whole confidential data. Because partial data are stored in clear on cloud premises, outsourced functionalities are seamlessly and efficiently supported by just broadcasting queries to the different cloud locations. To enforce a robust privacy notion, our proposal relies on a privacy model that offers a priori privacy guarantees; to ensure its feasibility, we have designed heuristic algorithms that minimize the number of cloud storage locations we need; to show its potential and generality, we have applied it to the least structured and most challenging data type: plain textual documents

Semantic clustering based on ontologies: an application to the study of visitors in a natural reserve

The development of large ontologies for general and specific domains provides new tools to improve the quality of data mining techniques such as clustering. In this paper we explain how to improve clustering results by exploiting the semantics of categorical data by means of ontologies and how this semantics can be included into a hierarchical clustering method. We want to prove that when the conceptual meaning of the values is taken into account, it is possible to find a better interpretation of the clusters. This is demonstrated with the analysis of real data collected from visitors to of a Natural Reserve. The results of our methodology are compared with the ones obtained with a classical multivariate analysis done in the same database.Peer ReviewedPostprint (published version

Detecting Term Relationships to Improve Textual Document Sanitization

Nowadays, the publication of textual documents provides critical benefits to scientific research and business scenarios where information analysis plays an essential role. Nevertheless, the possible existence of identifying or confidential data in this kind of documents motivates the use of measures to sanitize sensitive information before being published, while keeping the innocuous data unmodified. Several automatic sanitization mechanisms can be found in the literature; however, most of them evaluate the sensitivity of the textual terms considering them as independent variables. At the same time, some authors have shown that there are important information disclosure risks inherent to the existence of relationships between sanitized and non-sanitized terms. Therefore, neglecting term relationships in document sanitization represents a serious privacy threat. In this paper, we present a general-purpose method to automatically detect semantically related terms that may enable disclosure of sensitive data. The foundations of Information Theory and a corpus as large as the Web are used to assess the degree relationship between textual terms according to the amount of information they provide from each other. Preliminary evaluation results show that our proposal significantly improves the detection recall of current sanitization schemes, which reduces the disclosure risk

Cross-Linguistic Similarities in the Acquisition of English and Catalan

This paper analyses the acquisition of the functional categories Agreement (AGR-S) and Tense (TNS) by monolingual English and Catalan speaking children. The theoretical framework assumed is the Principles and Parameters model of Generative Theory. The results of the study show that all the children go through two stages in the acquisition of these two functional categories: A first prefunctional stage, characterised by the absence of syntactic projections for Agreement and Tense; and a second, functional stage, in which children start to show knowledge of the mechanisms and properties associated with the two functional categories at stake. The results of this study provide evidence for the Maturation of Functional Categories Hypothesis, as proposed by Guilfoyle and Noonan (1988), Radford (1990), and Tsimpli (1992), among others

Customization of an agent-based medical system

In this paper, the automatic customization of an agent-based medical system is approached by means of ontologies. The particular case of Home Care studied and developed in the EU K4Care project, is presented. The customization is achieved by means of generating individual versions of a reference ontology, called Actor Profile Ontology, which defines the behaviour of the actors in the multi-agent system. The paper, analyses the usability and advantages of this customization in order to add flexibility and adaptability to the system. It also shows how the personalized ontology is able to represent the liabilities and permissions of a particular user, providing the base for automatically generating the behaviour of the corresponding personal agent. A tool, called ATAPO, is also presented. It has been designed to assist the user in the personalization process. The way how this tool interacts with the system to permit the online modification of the behaviour of the agents is also discussed.Postprint (published version

Semantic similarity estimation from multiple ontologies

The version of record is available online at: http://dx.doi.org/10.1007/s10489-012-0355-yPeer ReviewedPostprint (author's final draft