Sales intelligence using web mining

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5633 LNAI, Issue , 2009, Pages 131-145

  Popova, Viara ^a   John, Robert ^a   Stockton, David ^a  

^a DE MONTFORT UNIVERSITY   (United Kingdom)

Author keywords

Machine learning; Natural language processing; Text mining; Web content mining

Indexed keywords

K-NEAREST NEIGHBOURS; KNOWLEDGE EXTRACTION; MACHINE LEARNING ALGORITHMS; MACHINE-LEARNING; MULTI LAYER PERCEPTRON; NATURAL LANGUAGE PROCESSING; TEXT MINING; WEB CONTENT MINING; WEB MINING; WEB PAGE;

COMPUTATIONAL LINGUISTICS; DATA MINING; DECISION TREES; EXPERIMENTS; NATURAL LANGUAGE PROCESSING SYSTEMS; SUPPORT VECTOR MACHINES; WEBSITES;

LEARNING ALGORITHMS;

EID: 76249093246     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-03067-3_12     Document Type: Conference Paper

References (26)

1. Billsus, D., Pazzani, M.: A Personal News Agent that Talks, Learns and Explains. In: Proceedings of the Third International Conference on Autonomous Agents (Agents 1999), Seattle, Washington (1999)
2. Chakrabarti, S., van den Berg, M., Dom, B.: Focused crawling: A new approach to topicspecific web resource discovery. Computer Networks 31(11-16), 1623-1640 (1999)
3. Cooley, R.: Classification of News Stories Using Support Vector Machines. In: IJCAI 1999 Workshop on Text Mining (1999)
4. Cunningham, H., Maynard, D., Bontcheva, K., Tablan, V.: GATE: A Framework and Graphical Development Environment for Robust NLP Tools and Applications. In: Proceedings of the 40th Anniversary Meeting of the Association for Computational Linguistics (ACL 2002), Philadelphia (2002)
5. Diligenti, M., Coetzee, F., Lawrence, S., Giles, C.L., Gori, M.: Focused crawling using context graphs. In: Proceedings of the 26th International Conference on Very Large Databases (VLDB), pp. 527-534 (2000)
6. Eikvil, L.: Information Extraction from World Wide Web - A Survey. Technical Report 945 (1999)
7. Frank, E., Bouckaert, R.R.: Naive Bayes for Text Classification with Unbalanced Classes. In: Fürnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) PKDD 2006. LNCS, vol. 4213, pp. 503-510. Springer, Heidelberg (2006)
8. Joachims, T.: Text Categorization with Support Vector Machines: Learning with Many Relevant Features. In: Nédellec, C., Rouveirol, C. (eds.) ECML 1998. LNCS, vol. 1398. Springer, Heidelberg (1998)
9. Kosala, R., Blockeel, H.: Web Mining Research: A Survey. SIGKDD Explorations 2, 1-15 (2000)
10. Kumaran, G., Allan, J.: Text Classification and Named Entities for New Event Detection. In: Proceedings of SIGIR 2004, pp. 297-304 (2004)
11. le Cessie, S., van Houwelingen, J.C.: Ridge Estimators in Logistic Regression. Applied Statistics 41(1), 191-201 (1992)
12. Li, Y., Bontcheva, K., Cunningham, H.: SVM Based Learning System For Information Extraction. In: Winkler, J.R., Niranjan, M., Lawrence, N.D. (eds.) Deterministic and Statistical Methods in Machine Learning. LNCS (LNAI), vol. 3635, pp. 319-339. Springer, Heidelberg (2005)
13. Manning, C.D., Schütze, H.: Foundations of Statistical Natural Language Processing. MIT Press, Cambridge (1999)
14. Masand, B., Lino, G., Waltz, D.: Classifying News Stories Using Memory Based Reasoning. In: International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 59-65 (1992)
15. Mccallum, A., Nigam, K.: A Comparison of Event Models for Naive Bayes Text Classification. In: Proceedings of the AAAI 1998 Workshop on Learning for Text Categorization (1998)
16. Menczer, F.: ARACHNID: Adaptive Retrieval Agents Choosing Heuristic Neighborhoods for Information Discovery. In: Fisher, D. (ed.) Proceedings of the 14th International Conference on Machine Learning (ICML 1997). Morgan Kaufmann, San Francisco (1997)
17. Platt, J.: Fast Training of Support Vector Machines using Sequential Minimal Optimization. In: Schoelkopf, B., Burges, C., Smola, A. (eds.) Advances in Kernel Methods - Support Vector Learning. MIT Press, Cambridge (1998)
18. Quinlan, R.: C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo (1993)
19. Rennie, J.D., Shih, L., Teevan, J., Karger, D.R.: Tackling the Poor Assumptions of Naive Bayes Text Classifiers. In: Proceedings of the International Conference on Machine Learning (ICML 2003), pp. 616-623 (2003)
20. Salton, G., McGill, M.: Introduction to Modern Information Retrieval. McGraw-Hill, New York (1983)
21. Selamat, A., Omatu, S.: Web Page Feature Selection and Classification Using Neural Networks. Information Sciences 158, 69-88 (2004)
22. Vapnik, V.: The Nature of Statistical Learning Theory. Springer, New York (1995)
23. Wermter, S.: Hung, Ch.: Selforganizing Classification on the Reuters News Corpus. In: Proceedings of the 19th international conference on Computational linguistics, Taipei, Taiwan, pp. 1-7 (2002)
24. Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)
25. Yang, Y.: An Evaluation of Statistical Approaches to Text Categorization. Information Retrieval 1, 69-90 (1999)
26. th International Conference on Computational Linguistics (COLING 1992), pp. 447-453 (1992)