Word association norms, mutual information, and lexicography
Computational Linguistics
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Opinion observer: analyzing and comparing opinions on the Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
Inducing information extraction systems for new languages via cross-language projection
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Independence and commitment: assumptions for rapid training and execution of rule-based POS taggers
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Movie review mining and summarization
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Ontology-based information extraction for business intelligence
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Integrating web feed opinions into a corporate data warehouse
Proceedings of the 2nd International Workshop on Business intelligencE and the WEB
Automatic sentiment classification of product reviews using maximal phrases based analysis
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
Automatic detection of political opinions in tweets
ESWC'11 Proceedings of the 8th international conference on The Semantic Web
MOETA: a novel text-mining model for collecting and analysing competitive intelligence
International Journal of Advanced Media and Communication
Storing and analysing voice of the market data in the corporate data warehouse
Information Systems Frontiers
| Hi-index | 0.00 |
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.