Towards the web of concepts: Extracting concepts from large datasets

Proceedings of the VLDB Endowment

Volumn 3, Issue 1, 2010, Pages 566-577

  Parameswaran, Aditya ^a   Garcia Molina, Hector ^a   Rajaraman, Anand ^b  

^a STANFORD UNIVERSITY   (United States)

^b Kosmix Corporation   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EXTRACTION;

CONCEPT EXTRACTION; EXTRACTING CONCEPT; HIGH-PRECISION; LARGE DATASETS; NOVEL TECHNIQUES; SEARCH TECHNOLOGY; STATISTICAL MEASURES; SUPPORT AND CONFIDENCE;

WEB CRAWLER;

EID: 82055172940     PISSN: None     EISSN: 21508097     Source Type: Conference Proceeding    
DOI: 10.14778/1920841.1920914     Document Type: Article

References (30)

1. http://en.wikipedia.org/wiki/wikipedia:criteria_for_speedy_deletion.
2. R. Agrawal and R. Srikant. Fast algorithms for mining association rules in large databases. In VLDB 1994.
3. B. Gelfand et. al. Discovering concepts in raw texts: Building semantic relationship graphs. Technical report, 1998.
4. I. Bichindaritz and S. Akkineni. Concept mining for indexing medical literature. LNCS, 3587, 2005.
5. T. Brants and A. Franz. Web 1T 5-gram V1, 2006.
6. E. Brill. A simple rule-based part of speech tagger. In Ap. NLP 1992.
7. S. Brin. Extracting patterns and relations from the world wide web. In WebDB, EDBT 1998.
8. D. Evans and C. Zhai. Noun-phrase analysis in unrestricted text for information retrieval. In ACL 1996.
9. F. De Comit et. al. Positive and unlabeled examples help learning. In Conf. on Alg. Learning Theory 1999.
10. G. Pass et. al. A picture of search. In InfoScale 2006.
11. J. Han, J. Pei, Y. Yin, and R. Mao. Mining frequent patterns without candidate generation. Data Min. Knowl. Discov., 2004.
12. M. A. Hearst. Automatic acquisition of hyponyms from large text corpora. In COLING 1992.
13. P. Heymann, G. Koutrika, and H. Garcia-Molina. Can social bookmarking improve web search? In WSDM 2008.
14. C. Jacquemin and D. Bourigault. Term extraction and automatic indexing. Handbook Of Comp. Linguistics, 2003.
15. K. Frantzi et. al. Automatic recognition of multi-word terms: the c-value/nc-value method. Int. Journal on Digital Libraries 2000.
16. A. Kittur, E. Chi, and B. Suh. Crowdsourcing user studies with mechanical turk. In CHI 2008.
17. K. Kageura and B. Umino. Methods of automatic term recognition: a review. Terminology, 3, 1996.
18. M. Looks et. al. Streaming hierarchical clustering for concept mining. Aerospace Conference, IEEE, 2007.
19. M. T. Castellvi et. al. Automatic term detection: A review of current systems. In Recent Adv. in Comp. Terminology 2001.
20. A. Maedche and S. Staab. Mining ontologies from text. In EKAW 2000, London, UK.
21. C. D. Manning and H. Schutze. Foundations of Statistical NLP. MIT Press, June 1999.
22. N. Dalvi et. al. A web of concepts. In PODS 2009.
23. P. Pantel et. al. A statistical corpus-based term extractor. AI 2001.
24. R. Agrawal et. al. Mining sequential patterns. In ICDE 1995.
25. R. Jones et. al. Generating query substitutions. In WWW 2006.
26. S. Loh et. al. Concept-based knowledge discovery in texts extracted from the web. SIGKDD Explor. Newsl., 2(1), 2000.
27. M. Sanderson and B. Croft. Deriving concept hierarchies from text. In SIGIR 1999.
28. M. Seno and G. Karypis. Finding frequent patterns using length-decreasing support constraints, 2001.
29. K. Wang, Y. He, D. W. Cheung, and Y. L. Chin. Mining confident rules without support requirement. In CIKM 2001.
30. Q. Yang and H. H. Zhang. Web-log mining for predictive web caching. TKDE., 15(4), 2003.