TRUMIT: A tool to support large-scale mining of text association rules

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

Volumn 6913 LNAI, Issue PART 3, 2011, Pages 646-649

  Neumayer, Robert ^a   Tsatsaronis, George ^b   Nørvåg, Kjetil ^a  

^a NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

^b DRESDEN UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATION RULE MINING; EVALUATION MEASURES; LARGE-SCALE MINING; MINE ASSOCIATION RULES; SCIENTIFIC COMMUNITY; TEXT COLLECTION; TEXT CORPORA; TEXTUAL DATA;

LEARNING SYSTEMS;

ASSOCIATION RULES;

EID: 80052396601     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23808-6_48     Document Type: Conference Paper

References (4)

1. Agrawal, R., Imieliński, T., Swami, A.:Mining association rules between sets of items in large databases. SIGMOD Record 22, 207-216 (1993)
2. Amir, A., Aumann, Y., Feldman, R., Fresko, M.: Maximal association rules: A tool for mining associations in text. Journal of Int. Inf. Systems 25(3), 333-345 (2005)
3. Kurashima, T., Fujimura, K., Okuda, H.: Discovering association rules on experiences from large-scale blog entries. In: Boughanem, M., Berrut, C., Mothe, J., Soule-Dupuy, C. (eds.) ECIR 2009. LNCS, vol. 5478, pp. 546-553. Springer, Heidelberg (2009)
4. Nørvåg, K., Fivelstad, O.K.: Semantic-based temporal text-rule mining. In: Gelbukh, A. (ed.) CICLing 2009. LNCS, vol. 5449, pp. 442-455. Springer, Heidelberg (2009)