Abstract
In the rapidly changing business environment, with global competition and maturing markets, competitive advantage is extremely important. Furthermore, in most industries product differentiation is no longer a decisive edge over competition. Thus, there is fierce competition to find, grow and keep loyal and profitable customers, optimize processes, adapt quickly to rapidly changing environments, and discover actionable knowledge quickly as those are the only way to grow business and profitability. Transforming a product-centric organization into a customer-centric one to achieve the above objectives is another critical step. This talk will present vision, strategy, emerging technologies and analytics using which businesses can hope to obtain sustainable competitive advantage. The talk will also provide a synergistic perspective on strategy, organizational transformation, and technology enabled relationship management. Steps and strategies involved in a successful deployment of operational and analytical infrastructure along with a landscape of key business intelligence technologies will be presented. The talk will present many examples from targeted marketing, modern marketing and briefly discuss the future of marketing.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up? Sentiment Classification Using Machine Learning Techniques. In: Proceedings of Conference on Empirical Methods in Natural Language Processing (2002)
Turney, P.: Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews. In: Proceedings of ACL 2002 (2002)
Wiebe, J., Wilson, T.: Learning to Disambiguate Potentially Subjective Expressions. In: Proceedings of CoNLL-2002 (2002)
Wilson, T., Wiebe, J., Hwa, R.: Just how mad are you? Finding strong and weak opinion clauses. In: AAAI 2004 (2004)
Wiebe, J., Wilson, T.: Learning to Disambiguate Potentially Subjective Expressions. In: CoNLL 2002 (2002)
Kim, S., Hovy, E.: Determining the Sentiment of Opinions. In: COLING 2004 (2004)
Riloff, E., Wiebe, J.: Learning extraction patterns for subjective expressions. In: EMNLP 2003 (2003)
Hu, Liu, B.: Mining and summarizing customer reviews. In: KDD 2004 (2004)
Popescu, A.-M., Etzioni, O.: Extracting Product Features and Opinions from Reviews. In: EMNLP 2005 (2005)
Ku, L.-W., Liang, Y.-T., Chen, H.-H.: Opinion Extraction, Summarization and Tracking in News and Blog Corpora. In: AAAI-CAAW (2006)
Carenini, G., Ng, R., Pauls, A.: Interactive Multimedia Summaries of Evaluative Text. In: IUI 2006 (2006)
Kobayashi, N., Inui, K., Matsumoto, Y.: Extracting Aspect-Evaluation and Aspect-of Relations in Opinion Mining. In: EMNLP 2007 (2007)
Titov, I., McDonald, R.: A Joint Model of Text and Aspect Ratings for Sentiment Summarization. In: ACL 2008 (2008)
Liu, B.: Web Data Mining: Exploring Hyperlinks, Content and Usage Data. Springer, Heidelberg (2006)
Liu, B.: Sentiment Analysis and Subjectivity. In: Indurkhya, N., Damerau, F.J. (eds.) To appear in Handbook of Natural Language Processing, 2nd edn. (2009/2010)
Pang, B., Lee, L.: Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval 2(1-2), 1135 (2008)
Narayanan, R., Liu, B., Choudhary, A.: Sentiment Analysis of Conditional Sentences. In: Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP 2009), Singapore, August 6-7 (2009)
Forrester research, http://www.comscore.com/Press_Events/Press_Releases/2007/11/Online_Consumer_Reviews_Impact_Offline_Purchasing_Behavior
Comscore and Kelsey, http://www.shop.org/c/journal_articles/view_article_content?groupId=1&articleId=702&version=1.0
Liu, B.: Sentiment Analysis and Subjectivity. To appear in Handbook of Natural Language Processing, 2nd edn. (2010)
Hu, M., Liu, B.: Mining and Summarizing Customer Reviews. In: Proceedings of the 10th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD-2004), vol. 8, pp. 168–174 (2004)
Hu, M., Liu, B.: Mining Opinion Features in Customer Reviews. In: Proceedings of the 19th National Conference on Artificial Intelligence, vol. 7, pp. 755–760 (2004)
Popescu, A., Etzioni, O.: Extracting product features and opinions from reviews. In: Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, pp. 339–346 (2005)
Liu, B., Hu, M., Cheng, J.: Opinion Observer: Analyzing and Comparing Opinions. WWW 5, 342–351 (2005)
Kim, S., Pantel, P., Chklovski, T., Pennacchiotti, M.: Automatically Assessing Review Helpfulness. In: EMNLP, vol. 7, pp. 423–430 (2006)
He, B., Macdonald, C., He, J., Ounis, I.: An Effective Statistical Approach to Blog Post Opinion Retrieval. CIKM 10, 1063–1069 (2008)
Zhang, K., Narayanan, R., Choudhary, A.: Mining Online Customer Reviews for Ranking Products. Technical Report CUCIS-2009-11-001, Center for Ultra-scale Computing and Information Security (November 2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Choudhary, A.N., Narayanan, R., Zhang, K. (2010). High-End Analytics and Data Mining for Sustainable Competitive Advantage. In: Prasad, S.K., Vin, H.M., Sahni, S., Jaiswal, M.P., Thipakorn, B. (eds) Information Systems, Technology and Management. ICISTM 2010. Communications in Computer and Information Science, vol 54. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12035-0_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-12035-0_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12034-3
Online ISBN: 978-3-642-12035-0
eBook Packages: Computer ScienceComputer Science (R0)