By Akito Sakurai, Koiti Hasida, Katsumi Nitta
This ebook constitutes the completely refereed joint post-proceedings of the seventeenth and 18th annual meetings of the japanese Society for synthetic Intelligence, JSAI 2003 and JSAI 2004, and colocated overseas workshops, held in Niigata, Japan in June 2003 and in Kanazawa, Japan, in May/June 2004 respectively. the amount begins with five award successful papers of the JSAI 2003 major convention which are awarded in addition to 10 revised complete workshop papers, conscientiously reviewed and chosen from the 2 co-located overseas workshops on Agent-Based Modeling (WABM 2003) and the Semantic net workshop (SWSW 2003). the amount is concluded by means of eight award profitable papers from the JSAI 2004 major convention in addition to 28 revised complete workshop papers of the 1st overseas Workshop on Emergence and Evolution of Linguistic communique (EELC 2004), the foreign Workshop on Agent-Based Modeling (WABM 2004), and the Workshop on common sense and Engineering of traditional Language Semantics (LENLS 2004).
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Then, a data tree D is encoded as the sequence π = ((d1 , 1 ), (d2 , 2 ), . ) of depth-label pairs corresponding to the nodes on the pre-order traversal of T . This depth-label representation π also linearly related to the open-close parentheses representation as in XML [20]. Conversely, we can uniquely decode a depth-label representation π into a labeled ordered tree as follows. Definition 1. ([4,17,23]) Let S be a tree of size k ≥ 1. Then, a rightmost expansion of S is any tree T of size k + 1 obtained from S by (i) attaching a new node w with a label in L as a child of a parent node p on the rightmost branch of S so that (ii) w is the rightmost sibling of p.
J. , Efficiently Mining Long Patterns from Databases, In Proc. SIGMOD98, 85–93, 1998. 8. M. de Berg, M. van Kreveld, M. Overmars, O. Schwarzkopf, Computational Geometry, Algorithms and Applications, Springer, 2000. 9. L. Dehaspe, H. Toivonen, R. D. King, Finding Frequent Substructures in Chemical Compounds, In Proc. KDD-98, 30–36, 1998. Efficient Algorithms for Finding Frequent Substructures 45 10. P. B. Gibbons and Y. Matias, Synopsis Data Structures for Massive Data Sets, In External Memory Algorithms, DIMACS Series in Discr.
The number of candidate and frequent patterns computed by LB and EB 44 T. Asai et al. can see that the algorithm with the eager management computes more patterns than the algorithm with the lazy management. 7 Conclusion In this paper, we studied an online data mining problem from unbounded semistructured data stream. We presented efficient online algorithms that are continuously working on an unbounded stream of semi-structured data with bounded resources, and find a set of frequent ordered tree patterns from the stream on request at any time.