Data Series Mining Technology Analysis Based on Web Database

Today there is much hype about big data. The discussions seem to revolve around data mining technology, social Web data, and the open source platform of NoSQL and Hadoop. However, database, data warehouse and OLAP technologies are also integral parts of big data. Big data involves data from all sources, not just social Web data. Further, big data requires not only technology, but also a painstaking process for identifying, collecting, and preparing sufficient amounts of relevant data. This paper provides a holistic view of big data.

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A Holistic View of Big Data

International Journal of Data Warehousing and Mining ◽

10.4018/ijdwm.2014070104 ◽

2014 ◽

Vol 10 (3) ◽

pp. 59-69 ◽

Cited By ~ 6

Author(s):

Won Kim ◽

Ok-Ran Jeong ◽

Chulyun Kim

Keyword(s):

Data Mining ◽

Big Data ◽

Open Source ◽

Data Warehouse ◽

Social Web ◽

Web Data ◽

Mining Technology ◽

Holistic View

Today there is much hype about big data. The discussions seem to revolve around data mining technology, social Web data, and the open source platform of NoSQL and Hadoop. However, database, data warehouse and OLAP technologies are also integral parts of big data. Big data involves data from all sources, not just social Web data. Further, big data requires not only technology, but also a painstaking process for identifying, collecting, and preparing sufficient amounts of relevant data. This paper provides a holistic view of big data.

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Design and Research on Data Warehouse of Insurance Industry

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.496-500.2108 ◽

2014 ◽

Vol 496-500 ◽

pp. 2108-2111

Author(s):

Jian Hu Zhang ◽

Lei Lei ◽

Xin You Cui ◽

Yong Wu ◽

Lin Tao Li

Keyword(s):

Data Mining ◽

Data Warehouse ◽

Domain Knowledge ◽

Insurance Industry ◽

Basic Flow ◽

Logical Model ◽

Mining Technology ◽

Concept Model ◽

Design And Implementation

Through in-depth understanding of the domain knowledge of insurance and the study of the technology of data warehouse, the paper illustrate the application of data mining technology and data warehouse technology in the insurance clients analysis, and from the basic flow of, discusse the application of data warehouse technology in the field of insurance industry. Then, from the concept of data warehouse, describe the design and implementation of data warehouse concept model and logical model.

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Using an Ontology-Based Framework to Extract External Web Data for the Data Warehouse

Visual Analytics and Interactive Technologies ◽

10.4018/978-1-60960-102-7.ch003 ◽

2011 ◽

pp. 39-59

Author(s):

Charles Greenidge ◽

Hadrian Peter

Keyword(s):

Semantic Web ◽

Data Warehouse ◽

Language Processing ◽

Web Application ◽

Data Warehouses ◽

Web Data ◽

Intermediate Data ◽

External Data ◽

Automatic Matching ◽

The Web

Data warehouses have established themselves as necessary components of an effective Information Technology (IT) strategy for large businesses. In addition to utilizing operational databases data warehouses must also integrate increasing amounts of external data to assist in decision support. An important source of such external data is the Web. In an effort to ensure the availability and quality of Web data for the data warehouse we propose an intermediate data-staging layer called the Meta-Data Engine (M-DE). A major challenge, however, is the conversion of data originating in the Web, and brought in by robust search engines, to data in the data warehouse. The authors therefore also propose a framework, the Semantic Web Application (SEMWAP) framework, which facilitates semi-automatic matching of instance data from opaque web databases using ontology terms. Their framework combines Information Retrieval (IR), Information Extraction (IE), Natural Language Processing (NLP), and ontology techniques to produce a matching and thus provide a viable building block for Semantic Web (SW) Applications.

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Web Data Warehousing Convergence

Integrated Approaches in Information Technology and Web Engineering ◽

10.4018/978-1-60566-418-7.ch018 ◽

2009 ◽

pp. 278-303

Author(s):

D. Xuan Le ◽

J. Wenny Rahayu ◽

David Taniar

Keyword(s):

Data Warehouse ◽

Object Oriented ◽

Hierarchical Structures ◽

Structured Data ◽

Integration Technique ◽

Web Data ◽

Web Based ◽

Data Semantics ◽

Object Relational ◽

Data Source

This paper proposes a data warehouse integration technique that combines data and documents from different underlying documents and database design approaches. The well-defined and structured data such as Relational, Object- oriented and Object Relational data, semi-structured data such as XML, and unstructured data such as HTML documents are integrated into a Web data warehouse system. The user specified requirement and data sources are combined to assist with the definitions of the hierarchical structures, which serve specific requirements and represent a certain type of data semantics using object-oriented features including inheritance, aggregation, association and collection. A conceptual integrated data warehouse model is then specified based on a combination of user requirements and data source structure, which creates the need for a logical integrated data warehouse model. A case study is then developed into a prototype in a Web-based environment that enables the evaluation. The evaluation of the proposed integration Web data warehouse methodology includes the verification of correctness of the integrated data, and the overall benefits of utilizing this proposed integration technique.

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