Database Reference
In-Depth Information
REFERENCES
Agrawal, R., Rantzau, R., & Terzi, E. (2006). Context-sensitive ranking.
Proceedings of the ACM SIG-
MOD International Conference on Management of Data
, (pp. 383-394).
Agrawal, S., Chaudhuri, S., Das, G., & Gionis, A. (2003). Automated ranking of database query results.
ACM Transactions on Database Systems
,
28
(2), 140-174.
Ahlberg, C., & Shneiderman, B. (1994).
Visual information seeking: tight coupling of dynamic query
filters with starfield displays
(pp. 313-317). Proceedings on Human Factors in Computing Systems.
Breiman, L., Friedman, J., Stone, C. J., & Olshen, R. (1984).
Classification and regression trees
. Boca
Raton, FL: CRC Press.
Bruno, N., Gravano, L., & Marian, A. (2002). Evaluating top-k queries over Web-accessible databases.
Proceedings of the 18th International Conference on Data Engineering
, (pp. 369-380).
Card, S., MacKinlay, J., & Shneiderman, B. (1999).
Readings in information visualization: using vision
to think
. Morgan Kaufmann.
Chakrabarti, K., Chaudhuri, S., & Hwang, S. (2004). Automatic categorization of query results.
Proceed-
ings of the ACM SIGMOD International Conference on Management of Data
, (pp. 755-766).
Chaudhuri, S., Das, G., Hristidis, V., & Weikum, G. (2004). Probabilistic ranking of database query
results.
Proceedings of the 30th International Conference on Very Large Data Base
, (pp. 888-899).
Chen, Z. Y., & Li, T. (2007). Addressing diverse user preferences in SQL-Query-Result navigation.
Proceedings of the ACM SIGMOD International Conference on Management of Data
, (pp. 641-652).
Chrobak, M., Keynon, C., & Young, N. (2005). The reverse greedy algorithm for the metric k-median
problem.
Information Processing Letters
,
97
, 68-72. doi:10.1016/j.ipl.2005.09.009
Das, G., Hristidis, V., Kapoor, N., & Sudarshan, S. (2006). Ordering the attributes of query results.
Proceedings of the ACM SIGMOD International Conference on Management of Data
, (pp. 395-406).
Dhillon, I. S., Mallela, S., & Kumar, R. (2002). Enhanced word clustering for hierarchical text classifica-
tion.
Proceedings of the 8th ACM SIGKDD International Conference
, (pp. 191-200).
Finkelstein, L., Gabrilovich, E., Matias, Y., Rivlin, E., Solan, Z., Wolfman, G., et al. (2001). Placing
search in context: The concept revisited.
Proceedings of the 9th International World Wide Web Confer-
ence,
(pp. 406-414).
Geerts, F., Mannila, H., & Terzim, E. (2004). Relational link-based ranking.
Proceedings of the 30th
International Conference on Very Large Data Base
, (pp. 552-563).
Joachims, T. (1998). Text categorization with support vector machines: Learning with many relevant
features.
Proceedings of the European Conference on Machine Learning
, (pp. 137-142).
Joachims, T. (2002). Optimizing search engines using clickthrough data.
Proceedings of the ACM Con-
ference on Knowledge Discovery and Data Mining
, (pp. 133-142).
