Learning to Identify Comparative Sentences in Chinese Text
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Entity discovery and assignment for opinion mining applications
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Discovery of significant emerging trends
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Identifying potential adverse effects using the web: A new approach to medical hypothesis generation
Journal of Biomedical Informatics
Learning to find comparable entities on the web
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
More than words: Social networks' text mining for consumer brand sentiments
Expert Systems with Applications: An International Journal
| Hi-index | 0.00 |
In recent years, product discussion forums have become a rich environment in which consumers and potential adopters exchange views and information. Researchers and practitioners are starting to extract user sentiment about products from user product reviews. Users often compare different products, stating which they like better and why. Extracting information about product comparisons offers a number of challenges; recognizing and normalizing entities (products) in the informal language of blogs and discussion groups require different techniques than those used for entity extraction in the more formal text of newspapers and scientific articles. We present a case study in extracting information about comparisons between running shoes and between cars, describe an effective methodology, and show how it produces insight into how consumers view the running shoe and car markets.