1,720,972 research outputs found
OntoExtractor : a tool for semi-automatic generation and maintenance of taxonomies from semi-structured documents
No full textThis chapter introduces OntoExtractor, a tool for semi-automatic generation of taxonomy from a set of documents or data sources. The tool generates the taxonomy in a bottom-up fashion: starting from structural analysis of the documents, it generates a set of clusters, which can be refined by a further grouping generated by content analysis. Metadata describing the content of each cluster is automatically generated and analysed by the tool for generating the final taxonomy. A simulation of a tool, based on implicit and explicit voting mechanism, for the maintenance of the taxonomy is also described.
The author describes a system that can be used to generate taxonomy from a heterogeneous source of information, using wrappers for converting the original format of the document to a structured one. This way OntoExtractor can virtually generate taxonomy from any source of information just adding the proper wrapper. Moreover, the trust mechanism allows a reliable method for maintaining the taxonomy and for overcoming the unavoidable generation of wrong classes in the taxonomy
Matching operators in data integration
No full textThis paper discusses the role of matching operators in Data Integration process. The paper proposes acategorization of matching operators, with the aim of distinguishing different relations to the possiblegoals of an integration process and their impact on the implementation of the mappings defining thisintegration. In order to lead the discussion some example
METHOD AND DEVICES FOR ACCESS CONTROL
No full textThe invention relates to a method and system which provides access control and access control enforcement particularly in relation to business process data streams. Embodiments of the invention provide a method and a set of components (referred to as: Policy Administration Point, Policy Enforcement Point, Filter Updater, Log De-Multiplexer) for fast online filtering of process logs based on access rights. In one embodiment the method comprises a series of steps to (i) encode each user's access rights to the process log in a machine readable format (ii) use such encoding together with incoming process events to compute a custom online filter to be applied to the process log as it is being recorded (iii) execute logical log de-multiplexing, enabling each user to query, inspect and monitor a separate event flow. In specific embodiments, the four components are virtual devices, respectively in charge of policy encoding (Policy Administration Point), policy evaluation and enforcement (Policy Enforcement Point), computation of an online filter with enforcement of log integrity constraints (Filter Updater), and generation of virtual event flows and support for policy changes and rights' revocations (Log De-Multiplexer)
Which role for an ontology of uncertainty?
Full text linkAn Ontology of Uncertainty, like the one proposed by the W3C’s UR3W-XG incubator group, provides a vocabulary to annotate
different sources of information with different types of uncertainty. Here
we argue that such annotations should be clearly mapped to corresponding reasoning and representation strategies. This mapping allows the system to analyse the information on the basis of its uncertainty model,
running the inference proccess according to the respective uncertainty.
As a proof of concepts we present a data integration system implementing a semantics-aware matching strategy based on an ontological representation of the uncertain/inconsistent matching relations generated by the various matching operators. In this scenario the sources of information
to be analyzed according to different uncertainty models are independent
and no intersection among them is to be managed. This particular case allows a straight-forward use of the Ontology of Uncertainty to drive the reasoning process, although in general the assumption of independence among the source of information is a lucky case. This position paper
highlights the need of additional work on the Ontology of Uncertainty in order to support reasoning processes when combinations of uncertainty models are to be applied on a single source of information
Method and apparatus for processing electronic data
No full textThe present invention relates to a method and apparatus for processing electronic data, and in particular, to a method and apparatus for assisting a user to map different descriptions of stored electronic data, or ontologies or data schema, to one another to render considerably easier the process of enabling computers to process stored electronic data stored on different heterogeneous databases according to correspondingly different methodologies. In particular, it relates to a method of generating a mapping from a global ontology to a plurality of databases and/or database tables to enable queries rendered using the global ontology to be answered using data stored in the database tables
Facing big data variety in a model driven approach
No full textDespite the benefits of investing in Big Data systems are largely recognised, their adoption have been slower than expected. Actually, organisations and companies cannot migrate their systems to new a technological infrastructure without a safe integration to their legacy systems and data. For these reasons, it is required to evolve Big Data technologies with mature functions for supporting portability, interoperability and reusability. This paper illustrates a practical use case exploiting the Model-driven capabilities of the TOREADOR platform as a way to fast track the uptake of business-driven Big Data models
A toward framework for generic uncertainty management
Full text linkThe need for an automatic inference process able to deal with information coming from unreliable sources is becoming a relevant issue both on corporate networks and on the open Web.
Mathematical theories to reason with uncertain information have been successfully applied in several situations, but each one of these models is tailored to deal with a specific semantics of uncertainty.
In this paper, we put forward the idea of using explicit representations of the different types of uncertainty for partitioning the inference process into parts. By coordinating multiple independent reasoning processes, we are sometimes able to apply a specific model to each type of uncertain information, and recombine the final results via a suitable reconciliation process.
We validated our approach applying it to the classic schema matching problem, and using the Ontology Alignment Evaluation Initiative, (OAEI) tests to assess the results
Semantics-aware matching strategy (SAMS) for the ontology mediated data integration (ODDI)
No full textData integration systems are used to integrate heterogeneous data sources in a single view. Recent work on business intelligence highlights the need of on-time, reliable and sound data access systems relying on methods based on semi-automatic procedures. A crucial factor for any semi-automatic algorithm is that of the matching strategy. Different categories of matching operators carry different semantics. For this reason, combining them into a single strategy is a non-trivial process that has to take into account a variety of options. This paper presents SAMS, a matching strategy based on a semantics-aware categorisation of matching operators that allows to group similar attributes on a semantically-rich form
Toward behavioral business process analysis
No full textThis work adresses the problem estimating correlations between process observables and KPI/SLA violation metrics. This analysis is aimed at providing business process owners with a suggestion of potential causality between groups of process parameters and violations. Obviously, static regression analysis cannot establish causality. We introduce a notion of Behavioral Analysis of business process instances and argue that, under suitable assumptions, Granger correlation can be used to highlight potential causality between business process observables and violations of leading KPIs. To handle the combinatorial explosion of the process observables search space, we describe a game theoretical approach for identifying (sets of) time-shifted process attributes to be tested
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