Paper Info
Title
Opinion analysis for business intelligence applications
Abstract
More than ever before, business analysts have access to public forums in which opinions and sentiments about companies, products, and policies are expressed in unstructured form. Mining information from public sources is of great importance to many business intelligence applications such as credit rating or company reputation. We have implemented a supervised machine-learning system which uses linguistic information to classify text by rating (good or bad, for example, or 1 to 5 stars). In an evaluation we have obtained good results in comparison with the state-of-the-art in opinion mining. We are further developing the system to classify each text according to a "qualitative variable" category from an ontology specially developed for Business Intelligence (BI). This work will allow us to generate RDF statements to populate a knowledge base for BI.
Year
DOI
Venue
2008
10.1145/1452567.1452570
OBI
Keywords
Field
DocType
opinion analysis,public source,supervised machine-learning system,business analyst,opinion mining,mining information,credit rating,business intelligence application,public forum,linguistic information,good result,business intelligence
Data science,Rule-based machine translation,Ontology,Sentiment analysis,Knowledge management,Credit rating,Knowledge base,Business intelligence,RDF,Business,Reputation
Conference
Citations 
PageRank 
References 
16
0.93
15
Authors
5
Name
Order
Citations
PageRank
Adam Funk131417.90
Yaoyong Li239326.55
Horacio Saggion31119112.62
Kalina Bontcheva42538211.33
Christian Leibold5160.93