8,017 research outputs found
Design of Automatically Adaptable Web Wrappers
Nowadays, the huge amount of information distributed through the Web motivates studying techniques to\ud
be adopted in order to extract relevant data in an efïŹcient and reliable way. Both academia and enterprises\ud
developed several approaches of Web data extraction, for example using techniques of artiïŹcial intelligence or\ud
machine learning. Some commonly adopted procedures, namely wrappers, ensure a high degree of precision\ud
of information extracted from Web pages, and, at the same time, have to prove robustness in order not to\ud
compromise quality and reliability of data themselves.\ud
In this paper we focus on some experimental aspects related to the robustness of the data extraction process\ud
and the possibility of automatically adapting wrappers. We discuss the implementation of algorithms for\ud
ïŹnding similarities between two different version of a Web page, in order to handle modiïŹcations, avoiding\ud
the failure of data extraction tasks and ensuring reliability of information extracted. Our purpose is to evaluate\ud
performances, advantages and draw-backs of our novel system of automatic wrapper adaptation
Web Data Extraction, Applications and Techniques: A Survey
Web Data Extraction is an important problem that has been studied by means of
different scientific tools and in a broad range of applications. Many
approaches to extracting data from the Web have been designed to solve specific
problems and operate in ad-hoc domains. Other approaches, instead, heavily
reuse techniques and algorithms developed in the field of Information
Extraction.
This survey aims at providing a structured and comprehensive overview of the
literature in the field of Web Data Extraction. We provided a simple
classification framework in which existing Web Data Extraction applications are
grouped into two main classes, namely applications at the Enterprise level and
at the Social Web level. At the Enterprise level, Web Data Extraction
techniques emerge as a key tool to perform data analysis in Business and
Competitive Intelligence systems as well as for business process
re-engineering. At the Social Web level, Web Data Extraction techniques allow
to gather a large amount of structured data continuously generated and
disseminated by Web 2.0, Social Media and Online Social Network users and this
offers unprecedented opportunities to analyze human behavior at a very large
scale. We discuss also the potential of cross-fertilization, i.e., on the
possibility of re-using Web Data Extraction techniques originally designed to
work in a given domain, in other domains.Comment: Knowledge-based System
Heterogeneous data source integration for smart grid ecosystems based on metadata mining
The arrival of new technologies related to smart grids and the resulting ecosystem of applications andmanagement systems pose many new problems. The databases of the traditional grid and the variousinitiatives related to new technologies have given rise to many different management systems with several formats and different architectures. A heterogeneous data source integration system is necessary toupdate these systems for the new smart grid reality. Additionally, it is necessary to take advantage of theinformation smart grids provide. In this paper, the authors propose a heterogeneous data source integration based on IEC standards and metadata mining. Additionally, an automatic data mining framework isapplied to model the integrated information.Ministerio de EconomĂa y Competitividad TEC2013-40767-
From Method Fragments to Method Services
In Method Engineering (ME) science, the key issue is the consideration of
information system development methods as fragments. Numerous ME approaches
have produced several definitions of method parts. Different in nature, these
fragments have nevertheless some common disadvantages: lack of implementation
tools, insufficient standardization effort, and so on. On the whole, the
observed drawbacks are related to the shortage of usage orientation. We have
proceeded to an in-depth analysis of existing method fragments within a
comparison framework in order to identify their drawbacks. We suggest
overcoming them by an improvement of the ?method service? concept. In this
paper, the method service is defined through the service paradigm applied to a
specific method fragment ? chunk. A discussion on the possibility to develop a
unique representation of method fragment completes our contribution
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Use of a Fast Information Extraction Method as a Decision Support Tool
Ad-hoc extraction of information from documents can ensure the transparency of decisions made by an organization. Different Information Extraction methods have been applied to extract information from various domains. Most widely known methods use manually annotated training documents that require high development time. The automated training methods are not scalable to large application domains. We have developed a semi-automated knowledge-engineering method for building the knowledge-base with minimal efforts. Because our method reduces manual processing of the training data, the development process is very fast. We have developed a prototype application to extract information from the project-reports of the American Recovery and Reinvestment Act (ARRA) of 2009. The fast development process of our system, its scalability to large application domains, and its high extraction effectiveness will help the transparency of management decisions by extracting and mining relevant information
Survey over Existing Query and Transformation Languages
A widely acknowledged obstacle for realizing the vision of the Semantic Web is the inability
of many current Semantic Web approaches to cope with data available in such diverging
representation formalisms as XML, RDF, or Topic Maps. A common query language is the first
step to allow transparent access to data in any of these formats. To further the understanding
of the requirements and approaches proposed for query languages in the conventional as well
as the Semantic Web, this report surveys a large number of query languages for accessing
XML, RDF, or Topic Maps. This is the first systematic survey to consider query languages from
all these areas. From the detailed survey of these query languages, a common classification
scheme is derived that is useful for understanding and differentiating languages within and
among all three areas
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Computerization of workflows, guidelines and care pathways: a review of implementation challenges for process-oriented health information systems
There is a need to integrate the various theoretical frameworks and formalisms for modeling clinical guidelines, workflows, and pathways, in order to move beyond providing support for individual clinical decisions and toward the provision of process-oriented, patient-centered, health information systems (HIS). In this review, we analyze the challenges in developing process-oriented HIS that formally model guidelines, workflows, and care pathways. A qualitative meta-synthesis was performed on studies published in English between 1995 and 2010 that addressed the modeling process and reported the exposition of a new methodology, model, system implementation, or system architecture. Thematic analysis, principal component analysis (PCA) and data visualisation techniques were used to identify and cluster the underlying implementation âchallengeâ themes. One hundred and eight relevant studies were selected for review. Twenty-five underlying âchallengeâ themes were identified. These were clustered into 10 distinct groups, from which a conceptual model of the implementation process was developed. We found that the development of systems supporting individual clinical decisions is evolving toward the implementation of adaptable care pathways on the semantic web, incorporating formal, clinical, and organizational ontologies, and the use of workflow management systems. These architectures now need to be implemented and evaluated on a wider scale within clinical settings
BlogForever D2.6: Data Extraction Methodology
This report outlines an inquiry into the area of web data extraction, conducted within the context of blog preservation. The report reviews theoretical advances and practical developments for implementing data extraction. The inquiry is extended through an experiment that demonstrates the effectiveness and feasibility of implementing some of the suggested approaches. More specifically, the report discusses an approach based on unsupervised machine learning that employs the RSS feeds and HTML representations of blogs. It outlines the possibilities of extracting semantics available in blogs and demonstrates the benefits of exploiting available standards such as microformats and microdata. The report proceeds to propose a methodology for extracting and processing blog data to further inform the design and development of the BlogForever platform
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