96,133 research outputs found
Enhanced Integrated Scoring for Cleaning Dirty Texts
An increasing number of approaches for ontology engineering from text are
gearing towards the use of online sources such as company intranet and the
World Wide Web. Despite such rise, not much work can be found in aspects of
preprocessing and cleaning dirty texts from online sources. This paper presents
an enhancement of an Integrated Scoring for Spelling error correction,
Abbreviation expansion and Case restoration (ISSAC). ISSAC is implemented as
part of a text preprocessing phase in an ontology engineering system. New
evaluations performed on the enhanced ISSAC using 700 chat records reveal an
improved accuracy of 98% as compared to 96.5% and 71% based on the use of only
basic ISSAC and of Aspell, respectively.Comment: More information is available at
http://explorer.csse.uwa.edu.au/reference
A model-driven approach to broaden the detection of software performance antipatterns at runtime
Performance antipatterns document bad design patterns that have negative
influence on system performance. In our previous work we formalized such
antipatterns as logical predicates that predicate on four views: (i) the static
view that captures the software elements (e.g. classes, components) and the
static relationships among them; (ii) the dynamic view that represents the
interaction (e.g. messages) that occurs between the software entities elements
to provide the system functionalities; (iii) the deployment view that describes
the hardware elements (e.g. processing nodes) and the mapping of the software
entities onto the hardware platform; (iv) the performance view that collects
specific performance indices. In this paper we present a lightweight
infrastructure that is able to detect performance antipatterns at runtime
through monitoring. The proposed approach precalculates such predicates and
identifies antipatterns whose static, dynamic and deployment sub-predicates are
validated by the current system configuration and brings at runtime the
verification of performance sub-predicates. The proposed infrastructure
leverages model-driven techniques to generate probes for monitoring the
performance sub-predicates and detecting antipatterns at runtime.Comment: In Proceedings FESCA 2014, arXiv:1404.043
Reasoning on Schemata of Formulae
A logic is presented for reasoning on iterated sequences of formulae over
some given base language. The considered sequences, or "schemata", are defined
inductively, on some algebraic structure (for instance the natural numbers, the
lists, the trees etc.). A proof procedure is proposed to relate the
satisfiability problem for schemata to that of finite disjunctions of base
formulae. It is shown that this procedure is sound, complete and terminating,
hence the basic computational properties of the base language can be carried
over to schemata
Unsupervised String Transformation Learning for Entity Consolidation
Data integration has been a long-standing challenge in data management with
many applications. A key step in data integration is entity consolidation. It
takes a collection of clusters of duplicate records as input and produces a
single "golden record" for each cluster, which contains the canonical value for
each attribute. Truth discovery and data fusion methods, as well as Master Data
Management (MDM) systems, can be used for entity consolidation. However, to
achieve better results, the variant values (i.e., values that are logically the
same with different formats) in the clusters need to be consolidated before
applying these methods.
For this purpose, we propose a data-driven method to standardize the variant
values based on two observations: (1) the variant values usually can be
transformed to the same representation (e.g., "Mary Lee" and "Lee, Mary") and
(2) the same transformation often appears repeatedly across different clusters
(e.g., transpose the first and last name). Our approach first uses an
unsupervised method to generate groups of value pairs that can be transformed
in the same way (i.e., they share a transformation). Then the groups are
presented to a human for verification and the approved ones are used to
standardize the data. In a real-world dataset with 17,497 records, our method
achieved 75% recall and 99.5% precision in standardizing variant values by
asking a human 100 yes/no questions, which completely outperformed a state of
the art data wrangling tool
A framework for effective management of condition based maintenance programs in the context of industrial development of E-Maintenance strategies
CBM (Condition Based Maintenance) solutions are increasingly present in industrial systems due to two
main circumstances: rapid evolution, without precedents, in the capture and analysis of data and
significant cost reduction of supporting technologies. CBM programs in industrial systems can become
extremely complex, especially when considering the effective introduction of new capabilities provided
by PHM (Prognostics and Health Management) and E-maintenance disciplines. In this scenario, any CBM
solution involves the management of numerous technical aspects, that the maintenance manager needs
to understand, in order to be implemented properly and effectively, according to the company’s strategy.
This paper provides a comprehensive representation of the key components of a generic CBM solution,
this is presented using a framework or supporting structure for an effective management of the CBM
programs. The concept “symptom of failure”, its corresponding analysis techniques (introduced by ISO
13379-1 and linked with RCM/FMEA analysis), and other international standard for CBM open-software
application development (for instance, ISO 13374 and OSA-CBM), are used in the paper for the
development of the framework. An original template has been developed, adopting the formal structure
of RCM analysis templates, to integrate the information of the PHM techniques used to capture the failure
mode behaviour and to manage maintenance. Finally, a case study describes the framework using the
referred template.Gobierno de AndalucĂa P11-TEP-7303 M
THE EVOLVING PHILOSOPHERS PROBLEM - DYNAMIC CHANGE MANAGEMENT
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