References

1. Background on Datalog, seminaive evaluation, EDB vs. IDB, stratified semantics, logic in general, and models can be found in Ch. 3 of PDKS-I (Volume I of Principles of Database and Knowledge-Base Systems, Ullman, Computer Science Press, 1988).

2. Volume II (PDKS-II) of the same book repeats some of the Datalog material, including the use of function symbols, and also contains material on conjunctive queries.

3. AHV (The book Foundations of Databases, by S. Abiteboul, R. Hull, and V. Vianu, Addison-Wesley, 1996) has material on Datalog, conjunctive queries, and well-founded semantics.

4. Slides on Datalog from CS145

5. M. Gelfond and V. Lifschitz, ``The stable model semantics for logic programming,'' 5th ICLP, pp. 1070-1080. The original paper on stable semantics.

6. A. Van Gelder, K. A. Ross, and J. S. Schlipf,``The well-founded semantics for general logic programs,'' JACM, 1991, pp. 620-650. The original paper on well-founded semantics.

7. A. Van Gelder, ``The alternating fixpoint of logic programs with negation,'' PODS, 1989, pp. 1-10. The paper that showed the alternating fixedpoint was equivalent to the original definition.

8. Sariaya's algorithm is in his thesis, ``Subtree elimination algorithms in deductive databases,'' Dept. of CS, Stanford, 1991.

9. R. Agrawal, T. Imielinski, A. Swami: ``Mining Associations between Sets of Items in Massive Databases'', Proc. of the ACM SIGMOD Int'l Conference on Management of Data, Washington D.C., May 1993, 207-216. Postscript. PDF.

10. R. Agrawal, R. Srikant: ``Fast Algorithms for Mining Association Rules'', Proc. of the 20th Int'l Conference on Very Large Databases, Santiago, Chile, Sept. 1994. Postscript. PDF.

11. E. Cohen et al., ``Finding Interesting Associations without Support Pruning,'' ICDE 2000. Postscript.

12. M. Fang, N. Shivakumar, H. Garcia-Molina, R. Motwani, and J. Ullman, ``Computing Iceberg Queries Efficiently,'' 1998 VLDB. Postscript.

13. H. Toivonen, ``Sampling Large Databases for Association Rules,'' VLDB 1996, pp. 134-145. Postscript.

14. J. S. Park, M.-S. Chen, and P. S. Yu, ``An Effective Hash-Based Algorithm for Mining Association Rules,'' 1995 SIGMOD, pp. 175--186. PDF

15. S. Brin and L. Page, The anatomy of a large-scale hypertextual Web search engine.

16. J. Kleinberg, ``Authoritative sources in a hyperlinked environment,'' J. ACM Sept., 1999, pp. 604-632. PDF.

17. Sepandar D. Kamvar, Taher H. Haveliwala, Christopher D. Manning, and Gene H. Golub. "Exploiting the Block Structure of the Web for Computing PageRank," Stanford University Technical Report, March 2003. (Submitted for publication)
    [ pdf | ps ]
18. Sepandar D. Kamvar, Taher H. Haveliwala, Christopher D. Manning, and Gene H. Golub. "Extrapolation Methods for Accelerating PageRank Computations," In Proceedings of the Twelfth International World Wide Web Conference, May 2003.
    [ pdf | ps ]
19. Conjunctive queries with negation are from a paper by Levy and Sagiv: Queries independent of updates.

20. Klug's method for CQ's with arithmetic is from ``On conjunctive queries containing inequalities,'' JACM 1:35 (1988), pp. 146-160.

21. The Gupta/Zhang/Oszoyoglu test is found in A. Gupta's Stanford thesis ``Partial information based integrity checking,'' 1994, and X. Zhang and M. Z. Ozsoyoglu, ``On efficient reasoning with implication constraints,'' Third DOOD Conf. (Dec., 1993), pp. 236-252.

22. The "LMSS" theorem is from the paper by Levy, Mendelzon, Sagiv, and Srivastava: Answering queries using views.

23. A paper on Maximally Contained Datalog Programs by Duschka and Genesereth.

24. Prasenjit Mitra's CS345 project on The Bucket Algorithm.

25. By coincidence, unification is explained in Section 12.4 of both PDKS-II and AHV.

26. Levy, Rajaraman, and Ordille on The Information-Manifold Query-Processing Algorithm.

27. P. Bradley, U. Fayyad, and C. Reina, ``Scaling Clustering Algorithms to Large Databases,'' 1998 KDD. Postscript.

28. S. Guha, R. Rastogi, and K. Shim, ``CURE: An Efficient Clustering Algorithm for Large Databases,'' SIGMOD 1998. PDF. Note: this PDF file requires a huge amount of temp space (over 200Mb).

29. Venkatesh Ganti, Raghu Ramakrishnan, Johannes Gehrke, Allison L. Powell, and James C. French:, ``Clustering Large Datasets in Arbitrary Metric Spaces,'' ICDE, pp. 502--511, 1999. PDF.