相关论文: Fuzzy data: XML may handle it

Data mining is a widely used technology for various real-life applications of data analytics and is important to discover valuable association rules in transaction databases. Interesting itemset mining plays an important role in many…

The ability to collect and analyze large amounts of data is a growing problem within the scientific community. The growing gap between data and users calls for innovative tools that address the challenges faced by big data volume, velocity…

Entity matching is a critical challenge in data integration and cleaning, central to tasks like fuzzy joins and deduplication. Traditional approaches have focused on overcoming fuzzy term representations through methods such as edit…

Over the last decade we have witnessed an increasing use of data processing in embedded systems. Where in the past the data processing was limited (if present at all) to the handling of a small number of "on-off control signals", more…

Despite substantial potential to transform bioscience, medicine, and bioengineering, whole-cell models remain elusive. One of the biggest challenges to whole-cell models is assembling the large and diverse array of data needed to model an…

While developing an information system for the University of Bern, we were faced with two major issues: managing software changes and adapting Business Information Models. Software techniques well-suited to software development teams exist,…

Web services is a collection of technologies that client-server model use also to exchange information. The Web services uses XML as the message wrapper to exchange information but the XML is always verbose and hence incurs latency in the…

Topic modeling is admittedly a convenient way to monitor markets trend. Conventionally, Latent Dirichlet Allocation, LDA, is considered a must-do model to gain this type of information. By given the merit of deducing keyword with token…

Recent work on database application development platforms has sought to include a declarative formulation of a conceptual data model in the application code, using annotations or attributes. Some recent work has used metadata to include the…

Locating and distilling the valuable relevant information continued to be the major challenges of Information Retrieval (IR) Systems owing to the explosive growth of online web information. These challenges can be considered the XML…

Open data is an emerging paradigm to share large and diverse datasets -- primarily from governmental agencies, but also from other organizations -- with the goal to enable the exploitation of the data for societal, academic, and commercial…

To optimize telecom service management, it is necessary that information about telecom services is highly related to the most popular telecom service. To this end, we propose an algorithm for mining target-oriented fuzzy correlation rules.…

Nowadays, journalism is facilitated by the existence of large amounts of digital data sources, including many Open Data ones. Such data sources are extremely heterogeneous, ranging from highly struc-tured (relational databases),…

XML-based communication governs most of today's systems communication, due to its capability of representing complex structural and hierarchical data. However, XML document structure is considered a huge and bulky data that can be reduced…

Clustering multivariate time series data is a crucial task in many domains, as it enables the identification of meaningful patterns and groups in time-evolving data. Traditional approaches, such as crisp clustering, rely on the assumption…

Large textual corpora are often represented by the document-term frequency matrix whose elements are the frequency of terms; however, this matrix has two problems: sparsity and high dimensionality. Four dimension reduction strategies are…

Unstructured data, in the form of text, images, video, and audio, is produced at exponentially higher rates. In tandem, machine learning (ML) methods have become increasingly powerful at analyzing unstructured data. Modern ML methods can…

Fuzzy clustering, which allows an article to belong to multiple clusters with soft membership degrees, plays a vital role in analyzing publication data. This problem can be formulated as a constrained optimization model, where the goal is…

The business intelligence and decision-support systems used in many application domains casually rely on data warehouses, which are decision-oriented data repositories modeled as multidimensional (MD) structures. MD structures help navigate…

Storing data is easy, but finding and using data is not. It is desirable that the data is stored in a structured format, which can be preserved and retrieved in future. Creating Metadata for the data is one way of creating structured data…