For similarity search in high-dimensional vector spaces (or `HDVSs'), researchers have proposed a number of new methods (or adaptations of existing methods) based, in the main, on data-space partitioning. However, the performance of these methods generally degrades as dimensionality increases. Although this phenomenon---known as the `dimensional curse'---is well known, little or no quantitative analysis of the phenomenon is available. In this paper, we provide a detailed analysis of partitioning and clustering techniques for similarity search in HDVSs. We show formally that these methods exhibit linear complexity at high dimensionality, and that existing methods are outperformed on average by a simple sequential scan if the number of dimensions exceeds around 10. Consequently, we come up with an alternative organization based on approximations to make the unavoidable sequential scan as fast as possible. We describe a simple vector approximation scheme, called VA-file, and report on an ...

The increasing performance and decreasing cost of processors and memory are causing system intelligence to move into peripherals from the CPU. Storage system designers are using this trend toward "excess" compute power to perform more complex processing and optimizations inside storage devices. To date, such optimizations have been at relatively low levels of the storage protocol. At the same time, trends in storage density, mechanics, and electronics are eliminating the bottleneck in moving data off the media and putting pressure on interconnects and host processors to move data more efficiently. We propose a system called Active Disks that takes advantage of processing power on individual disk drives to run application-level code. Moving portions of an application's processing to execute directly at disk drives can dramatically reduce data traffic and take advantage of the storage parallelism already present in large systems today. We discuss several types of appl...

Ad hoc querying is difficult on very large datasets, since it is usually not possible to have the entire dataset on disk. While compression can be used to decrease the size of the dataset, compressed data is notoriously difficult to index or access. In this paper we consider a very large dataset comprising multiple distinct time sequences. Each point in the sequence is a numerical value. We show how to compress such a dataset into a format that supports ad hoc querying, provided that a small error can be tolerated when the data is uncompressed. Experiments on large, real world datasets (AT&T customer calling patterns) show that the proposed method achieves an average of less than 5% error in any data value after compressing to a mere 2.5% of the original space (i.e., a 40:1 compression ratio), with these numbers not very sensitive to dataset size. Experiments on aggregate queries achieved a 0.5% reconstruction error with a space requirement under 2%. 1 Introduction The bulk of the data...

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We consider the problem of indexing general database workloads (combinations of data sets and sets of potential queries). We define a framework for measuring the efficiency of an indexing scheme for a workload based on two characterizations: storage redundancy (how many times each item in the data set is stored), and access overhead (how many times more blocks than necessary does a query retrieve). Using this framework we present some initial results, showing upper and lower bounds and trade-offs between them in the case of multi-dimensional range queries and set queries. 1 Introduction The success and ubiquity of the relational data model arguably owes much to the B-tree, the access method breakthrough that accompanied it with superb timing [2]. It seems likely that access methods will continue to play an important role in, and largely determine the viability of, the novel data models currently under intense scrutiny in the database research community. The B-tree is widely recognized...

Given an image (or video clip, or audio song), how do we automatically assign keywords to it? The general problem is to find correlations across the media in a collection of multimedia objects like video clips, with colors, and/or motion, and/or audio, and/or text scripts. We propose a novel, graph-based approach, "MMG", to discover such cross-modal correlations. Our

In this paper we review studies of the growth of the Internet and technologies that are useful for information search and retrieval on the Web. We present data on the Internet from several different sources, e.g., current as well as projected number of users, hosts, and Web sites. Although numerical figures vary, overall trends cited

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The principal trend in the design of computer systems is the expectation of much greater computational power in future generations of microprocessors. This trend applies to embedded systems as well as host processors. As a result, devices such as storage controllers have excess capacity and growing computational capabilities. Storage system designers are exploiting this trend with higher-level interfaces to storage and increased intelligence inside storage devices. One development in this direction is Network-Attached Secure Disks (NASD) which attaches storage devices directly to the network and raises the storage interface above the simple (fixed-size block) memory abstraction of SCSI. This allows devices more freedom to provide efficient operations; promises more scalable subsystems by offloading file system and storage management functionality from dedicated servers; and reduces latency by executing common case requests directly at storage devices. In this paper, we push this increa...

p, leaving sufficient area to include a 200-MHz ARM core or similar embedded microprocessor. Disk drive and chip manufacturers are already pursuing this processor-in-ASIC technology. Infineon (formerly Siemens Microelectronics) markets a chip called the TriCore that includes a 100-MHz 32-bit microcontroller, up to 2 Mbytes of on-chip RAM, and customer -specific logic---such as the disk functions of Figure 1, upper right---in a .35 micron process. Cirrus Logic offers an integrated system-on-chip hard disk drive controller called 3Ci that includes a 25-MHz ARM core in the first generation, with promise of 200 MHz in the next generation. Taking a larger system view, Table 1 shows details of several large database systems that manage transaction and data mining workloads. These trends and ratios in CPU versus aggregate processing power have remained roughly steady since we compiled this data in 1998 using information from the Transaction Processing Performance Council,