@conference {17790,
	title = {RDF aggregate queries and views},
	booktitle = {Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on},
	year = {2005},
	month = {2005/04//},
	pages = {717 - 728},
	abstract = {Resource description framework (RDF) is a rapidly expanding Web standard. RDF databases attempt to track the massive amounts of Web data and services available. In this paper, we study the problem of aggregate queries. We develop an algorithm to compute answers to aggregate queries over RDF databases and algorithms to maintain views involving those aggregates. Though RDF data can be stored in a standard relational DBMS (and hence we can execute standard relational aggregate queries and view maintenance methods on them), we show experimentally that our algorithms that operate directly on the RDF representation exhibit significantly superior performance.},
	keywords = {aggregate, databases;, DBMS;, description, framework;, languages;, Maintenance, methods;, processing;, queries;, query, RDF, relational, resource, standard;, standards;, view, Web},
	doi = {10.1109/ICDE.2005.121},
	author = {Hung,E. and Deng,Yu and V.S. Subrahmanian}
}
@conference {14961,
	title = {Efficient techniques for range search queries on earth science data},
	booktitle = {Scientific and Statistical Database Management, 2002. Proceedings. 14th International Conference on},
	year = {2002},
	month = {2002///},
	pages = {142 - 151},
	abstract = {We consider the problem of organizing large scale earth science raster data to efficiently handle queries for identifying regions whose parameters fall within certain range values specified by the queries. This problem seems to be critical to enabling basic data mining tasks such as determining associations between physical phenomena and spatial factors, detecting changes and trends, and content based retrieval. We assume that the input is too large to fit in internal memory and hence focus on data structures and algorithms that minimize the I/O bounds. A new data structure, called a tree-of-regions (ToR), is introduced and involves a combination of an R-tree and efficient representation of regions. It is shown that such a data structure enables the handling of range queries in an optimal I/O time, under certain reasonable assumptions. We also show that updates to the ToR can be handled efficiently. Experimental results for a variety of multi-valued earth science data illustrate the fast execution times of a wide range of queries, as predicted by our theoretical analysis.},
	keywords = {based, computing;, content, data, data;, databases;, Earth, factors;, large, mining, mining;, natural, processing;, queries;, query, range, raster, retrieval;, scale, Science, sciences, search, spatial, structures;, tasks;, temporal, tree, tree-of-regions;, visual},
	doi = {10.1109/SSDM.2002.1029714},
	author = {Shi,Qingmin and JaJa, Joseph F.}
}
