@conference {16836,
	title = {High-Dimensional Similarity Retrieval Using Dimensional Choice},
	booktitle = {Similarity Search and Applications, 2008. SISAP 2008. First International Workshop on},
	year = {2008},
	month = {2008/04//},
	pages = {35 - 42},
	abstract = {There are several pieces of information that can be utilized in order to improve the efficiency of similarity searches on high-dimensional data. The most commonly used information is the distribution of the data itself but the use of dimensional choice based on the information in the query as well as the parameters of the distribution can provide an effective improvement in the query processing speed and storage. The use of this method can produce dimension reduction by as much as a factor of n, the number of data points in the database, over sequential search. We demonstrate that the curse of dimensionality is not based on the dimension of the data itself, but primarily upon the effective dimension of the distance function. We also introduce a new distance function that utilizes fewer dimensions of the higher dimensional space to produce a maximal lower bound distance in order to approximate the full distance function. This work has demonstrated significant dimension reduction, up to 70\% reduction with an improvement in accuracy or over 99\% with only a 6\% loss in accuracy on a prostate cancer data set.},
	keywords = {data, database, function;high-dimensional, management, processing;, processing;sequential, reduction;database, reduction;distance, retrieval;query, search;data, search;similarity, similarity, system;dimension, systems;query},
	doi = {10.1109/SISAP.2008.20},
	author = {Tahmoush,D. and Samet, Hanan}
}
@conference {16201,
	title = {Query previews in networked information systems},
	booktitle = {Research and Technology Advances in Digital Libraries, 1996. ADL {\textquoteright}96., Proceedings of the Third Forum on},
	year = {1996},
	month = {1996/05//},
	pages = {120 - 129},
	abstract = {In a networked information system (such as the NASA Earth Observing System-Data Information System (EOS-DIS)), there are three major obstacles facing users in a querying process: network performance, data volume and data complexity. In order to overcome these obstacles, we propose a two phase approach to query formulation. The two phases are the Query Preview and the Query Refinement. In the Query Preview phase, users formulate an initial query by selecting rough attribute values. The estimated number of matching data sets is shown, graphically on preview bars which allows users to rapidly focus on a manageable number of relevant data sets. Query previews also prevent wasted steps by eliminating zero hit queries. When the estimated number of data sets is long enough, the initial query is submitted to the network which returns the metadata of the data sets for further refinement in the Query Refinement phase. The two phase approach to query formulation overcomes slow network performance, and reduces the data volume and data complexity, problems. This approach is especially appropriate for users who do not have extensive knowledge about the data and who prefer an exploratory method to discover data patterns and exceptions. Using this approach, we have developed dynamic query user interfaces to allow users to formulate their queries across a networked environment},
	keywords = {attribute, complexity;data, data, Earth, environment;networked, EOS-DIS;NASA, formulation;querying, formulation;user, hit, information, interfaces;, interfaces;exploratory, method;matching, networks;information, Observing, patterns;data, performance;networked, Preview;Query, process;rough, queries;computer, query, refinement;data, retrieval;information, services;interactive, sets;network, System-Data, System;Query, systems;query, user, values;zero, volume;dynamic},
	doi = {10.1109/ADL.1996.502522},
	author = {Donn,K. and Plaisant, Catherine and Shneiderman, Ben}
}
