Paper Info
Title
Approaches to analyse corporate tags for business intelligence purposes
Abstract
The information overload in business organizations hampers the information analysis process. Business intelligence tools can be used to analyse large amounts of information, however in most cases they only focus on structured information. More and more companies annotate tags to unstructured information to improve the information retrieval. We propose to exploit tags and tagging data to generate business intelligence. We believe that the analysis of large amounts of unstructured information for business intelligence purposes can be reduced to analysing tags and tag data. In the paper, we suggest that (1) tags and tag data can produce business intelligence from large amounts of unstructured information provided that some prerequisites are taken into account, (2) propose two step-by-step approaches of how existing mining and statistical techniques can be applied on tags and tagged data (3) by means of a tag data set from a European company, we provide preliminary evidence that the proposed approaches applied on corporate tags produce promising results regarding business intelligence.
Year
DOI
Venue
2008
10.1145/1452567.1452575
OBI
Keywords
Field
DocType
business intelligence,information retrieval,tag data,corporate tag,information analysis process,business intelligence tool,business intelligence purpose,large amount,structured information,information overload,unstructured information,information analysis,algorithms
Data science,Information overload,Information retrieval,Computer science,Exploit,Local information systems,Business intelligence
Conference
Citations 
PageRank 
References 
0
0.34
7
Authors
1
Name
Order
Citations
PageRank
Céline Van Damme1132.20