Inductive database languages: requirements and examples

Author:

Romei Andrea,Turini Franco

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software

Reference48 articles.

1. Agrawal R, Methta M, Shafer J, Srikant R (1994) Fast Algorithms for Mining Association Rules in Large Databases. In Jorge B, Bocca JB, Jarke M, Zaniolo C (eds) Proceeding of the 20th International Conference on very large databases (VLDB), Santiago de Chile, Chile, 12–15 September, pp 478–499

2. Arni N, Ong K, Zaniolo C (1993) Negation and Aggregates in Recursive Rules: the $${\mathcal{LDL}++}$$ Approach. In Ceri S, Tanaka K, Tsur S (eds) Proceeding of the Third International Conference on deductive and object-oriented databases (DOOD), Phoenix, Arizona, USA, 6–8 December, pp 204–221

3. Baglioni M, Ferrara U, Romei A, Ruggieri R, Turini F (2003) Preprocessing and Mining Web Log Data for Web Personalization. In Cappelli A, Turini F (eds) Proceeding of the 8th Congress of the Italian Association for artificial intelligence (AI*IA), Pisa, Italy, 23–26 September, pp 237–249

4. Baralis E, Cerquitelli T, Chiusano S (2005) Index support for frequent itemset mining in a relational DBMS. In: Proceedings of the 21st International Conference on data engineering (ICDE 2005), IEEE Computer Society, Tokyo, Japan, 5–8 April, pp 754–765

5. Baralis E, Garza P, Quintarelli E, Tanca L (2007) Answering XML queries by means of data summaries. ACM Trans Info Syst 25(3): 1–10

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