By Noureddine Mouaddib, Guillaume Raschia (auth.), Yahiko Kambayashi, Dik-Lun Lee, Ee-peng Lim, Mukesh Mohania, Yoshifumi Masunaga (eds.)
This ebook offers the completely refereed joint post-proceedings of 3 workshops held in the course of the seventeenth overseas convention on Conceptual Modeling, ER '98, in Singapore in November 1998. The 50 revised papers awarded have passed through rounds of reviewing and revision. The e-book is split in sections on wisdom discovery, info mining, info and internet warehousing, multidimensional databases, facts warehouse layout, caching, information dissemination, replication, cellular networks, cellular systems, monitoring and tracking, collaborative paintings aid, temporal information modelling, relocating items and spatial indexing, spatio-temporal databases, and video database contents.
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Extra resources for Advances in Database Technologies: ER ’98 Workshops on Data Warehousing and Data Mining, Mobile Data Access, and Collaborative Work Support and Spatio-Temporal Data Management, Singapore, November 19-20, 1998. Proceedings
We call a sampling method using the lemma magic sampling. Lemma 1 ∀x, x ∈ magic(a) ⇒ magic(x) ⊆ magic(a); a is a constant and magic(a) is the magic set of a. Proof sketch. A linear recursive rule has the following form. , Pm , P0 . · · · · · (1) For simplicity, variables have been omitted. Each literal may have diﬀerent arities  but P0 at the head and P0 in the body must have the same arity. From rule (1), adorned rules where only one variable is bound have the form shown below. f f bf f.. f f bf f..
Selected tuplek Masako YAMADA Toru YAMADA Fig. 14. Selected patients and their selected ancestors. Patient Ancestor Taro YAMADA Keiko YAMADA Masako YAMADA Toru YAMADA Hiroaki Suzuki Jiro Suzuki .. . Tadashi IZUMI Jun IZUMI Fig. 15. A sample obtained after stage 2. Suppose we are short of m tuples to form a sample. At stage 3, m patients are selected using the same method as in stage 1 using variables selected tuple1 to selected tuplel where l is equal to m × r. In order to be statistically correct, the total number of ancestors of each patient, t, is reduced by the total number of Patient-Ancestor relations that are already in the sample and involve the patient being examined.
5). After that, for each person x in magic(Masako YAMADA), we use magic(Masako YAMADA) to ﬁnd the number of ancestors of x. Each x is checked against the aggregate relation to see whether he or she has appeared in it or not before we ﬁnd the number of ancestors of x. If he or she has already appeared, we skip and go to the next x. After ﬁnding the number of ancestors of each x, we may obtain something like Fig. 6. Then we go to the second patient, Taro YAMADA, in the extensional database. By checking the aggregate relation, we know that his total number of ancestors has been calculated.