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16 results on '"Tseng, Frank S. C."'

1. Formalizing Graph Database and Graph Warehouse for On-Line Analytical Processing in Social Networks

Author

Tseng, Frank S. C., Chou, Annie Y. H., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Arai, Kohei, editor, Bhatia, Rahul, editor, and Kapoor, Supriya, editor

Published
2020
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3. Generating Social Relationships from Relational Databases for Graph Database Creation and Social Business Intelligence Management

Author

Tseng, Frank S. C., Chou, Annie Y. H., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Arai, Kohei, editor, Kapoor, Supriya, editor, and Bhatia, Rahul, editor

Published
2019
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6. An Integration of Fuzzy Association Rules and WordNet for Document Clustering

Author

Chen, Chun-Ling, Tseng, Frank S. C., Liang, Tyne, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Theeramunkong, Thanaruk, editor, Kijsirikul, Boonserm, editor, Cercone, Nick, editor, and Ho, Tu-Bao, editor

Published
2009
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8. Spatiotemporal Data Warehousing for Event Tracking Applications.

Author

TSENG, FRANK S. C. and CHOU, ANNE Y. H.

Subjects
DATA warehousing, CONTACT tracing, DATA management, TEMPORAL databases, DIGITAL footprint, BUSINESS intelligence
Abstract

In this paper, we propose a multidimensional spatiotemporal modeling framework of data warehouse creation for tracing dynamic events in contemporary applications, like crowd contact tracing for Covid-19 prevention. Such a framework offers a natural and consistent solution for slowly changing dimension management. It provides a progressive evolution from traditional static data management to modem dynamic data analysis with spatiotemporal tracking capabilities for IoT applications. Based on such a framework, entity-centered resource integration and related business intelligence applications can be rig· orously developed, managed and properly tracked. [ABSTRACT FROM AUTHOR]

Published
2022
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16. Design of a multi-dimensional query expression for document warehouses.

Author

Tseng, Frank S. C.

Subjects
*DATA warehousing, *MANAGEMENT information systems, *RECORDS management, *QUERY languages (Computer science), *COMPUTER science, *DATABASE management, *INFORMATION science, *INFORMATION resources management
Abstract

During the past decade, data warehousing has been widely adopted in the business community. It provides multi-dimensional analyses on cumulated historical business data for helping contemporary administrative decision-makings. However, many data warehousing query language in present only provides on-line analytical processing (OLAP) for numeric data. For example, MDX (Multi-Dimensional eXpressions) has been proposed as a query language to allow describing multi-dimensional queries over databases with OLAP capabilities. Nevertheless, it is believed there is only about 20% information can be extracted from data warehouse concerning numeric data only, the other 80% information is hidden in non-numeric data or even in documents. Therefore, many researchers now advocate it is time to conduct research works on document warehousing to capture complete business intelligence. Document warehouse, unlike traditional document management systems, include extensive semantic information about documents, cross-document feature relations, and document grouping or clustering to provide a more accurate and more efficient access to text-oriented business intelligence. In this paper, we extend the structure of MDX into a new one containing complete constructs for querying document warehouses. The traditional MDX only contains SELECT, FROM, and WHERE clauses, which is not rich enough for document warehousing. In this paper, we present how to extend the language constructs to include GROUP BY, HAVING, and ORDER BY to design an SQL-like query language for document warehousing. The work is essential for establishing an infrastructure to help combining text processing with numeric OLAP processing technologies. Hopefully, the combination of data warehousing and document warehousing will be one of the most important kernels of knowledge management and customer relationship management applications. [ABSTRACT FROM AUTHOR]

Published
2005
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