DOI: 10.7763/IJCTE.2016.V8.1027
SEMEXSS — A Rule-Based Semantic Metadata Extraction System for Spreadsheets
Abstract—Spreadsheets store not only routine data but also valuable information for organization administration and planning. Finding the spreadsheets that fit users’ needs from disparate repositories is becoming increasingly important. Semantic metadata is known as metadata that describes contextually relevant about content which is based on an industry-specific or enterprise-specific custom metadata model. Therefore, semantic metadata is used by many document management systems and search systems to search documents of organizations. However, due to limitation of current metadata extraction methods, semantic metadata extraction cannot be done automatically in many cases. The objective of this paper is to propose a novel system called SEMEXSS that can extract semantic metadata automatically from spreadsheets by metadata extraction rules. The extraction rules are automatically generated by the program that reads a sample spreadsheet whose semantic metadata is defined by users via a user interface of spreadsheet software. Experiment is done to investigate time complexity of metadata extraction of the system.
Index Terms—Metadata, generating, schema, semantic, XML.
Somchai Chatvichienchai is with the Department of Information and Media Studies, University of Nagasaki, 851-2195 Japan (e-mail: somchaic@sun.ac.jp).
Cite:Somchai Chatvichienchai, "SEMEXSS — A Rule-Based Semantic Metadata Extraction System for Spreadsheets," International Journal of Computer Theory and Engineering vol. 8, no. 2, pp. 102-108, 2016.