Newness and distinctiveness is claimed in the features of ornamentation as shown inside the broken line circle in the accompanying representation.

Display screen or portion thereof with graphical user interface

Systems and methods for managing data, such as metadata. In one exemplary method, metadata from files created by several different software applications are captured, and the captured metadata is searched. The type of information in metadata for one type of file differs from the type of information in metadata for another type of file. Other methods are described and data processing systems and machine readable media are also described.

Methods And Systems For Managing Data

The Web and especially major Web search engines are essential tools in the quest to locate online information for many people. This paper reports results from research that examines characteristics and changes in Web searching from nine studies of five Web search engines based in the US and Europe. We compare interactions occurring between users and Web search engines from the perspectives of session length, query length, query complexity, and content viewed among the Web search engines. The results of our research shows (1) users are viewing fewer result pages, (2) searchers on US-based Web search engines use more query operators than searchers on European-based search engines, (3) there are statistically significant differences in the use of Boolean operators and result pages viewed, and (4) one cannot necessary apply results from studies of one particular Web search engine to another Web search engine. The wide spread use of Web search engines, employment of simple queries, and decreased viewing of result pages may have resulted from algorithmic enhancements by Web search engine companies. We discuss the implications of the findings for the development of Web search engines and design of online content.

/pdf/how-are-we-searching-the-world-wide-web-a-comparison-of-nine-1vg6xqg009.pdf

How are we searching the world wide web?: a comparison of nine search engine transaction logs

This paper presents asymptotically optimal algorithms for rectangular matrix transpose, FFT, and sorting on computers with multiple levels of caching. Unlike previous optimal algorithms, these algorithms are cache oblivious: no variables dependent on hardware parameters, such as cache size and cache-line length, need to be tuned to achieve optimality. Nevertheless, these algorithms use an optimal amount of work and move data optimally among multiple levels of cache. For a cache with size Z and cache-line length L where Z=/spl Omega/(L/sup 2/) the number of cache misses for an m/spl times/n matrix transpose is /spl Theta/(1+mn/L). The number of cache misses for either an n-point FFT or the sorting of n numbers is /spl Theta/(1+(n/L)(1+log/sub Z/n)). We also give an /spl Theta/(mnp)-work algorithm to multiply an m/spl times/n matrix by an n/spl times/p matrix that incurs /spl Theta/(1+(mn+np+mp)/L+mnp/L/spl radic/Z) cache faults. We introduce an "ideal-cache" model to analyze our algorithms. We prove that an optimal cache-oblivious algorithm designed for two levels of memory is also optimal for multiple levels and that the assumption of optimal replacement in the ideal-cache model. Can be simulated efficiently by LRU replacement. We also provide preliminary empirical results on the effectiveness of cache-oblivious algorithms in practice.

Cache-oblivious algorithms

Data sets in large applications are often too massive to fit completely inside the computers internal memory. The resulting input/output communication (or I/O) between fast internal memory and slower external memory (such as disks) can be a major performance bottleneck. In this article we survey the state of the art in the design and analysis of external memory (or EM) algorithms and data structures, where the goal is to exploit locality in order to reduce the I/O costs. We consider a variety of EM paradigms for solving batched and online problems efficiently in external memory. For the batched problem of sorting and related problems such as permuting and fast Fourier transform, the key paradigms include distribution and merging. The paradigm of disk striping offers an elegant way to use multiple disks in parallel. For sorting, however, disk striping can be nonoptimal with respect to I/O, so to gain further improvements we discuss distribution and merging techniques for using the disks independently. We also consider useful techniques for batched EM problems involving matrices (such as matrix multiplication and transposition), geometric data (such as finding intersections and constructing convex hulls), and graphs (such as list ranking, connected components, topological sorting, and shortest paths). In the online domain, canonical EM applications include dictionary lookup and range searching. The two important classes of indexed data structures are based upon extendible hashing and B-trees. The paradigms of filtering and bootstrapping provide a convenient means in online data structures to make effective use of the data accessed from disk. We also reexamine some of the above EM problems in slightly different settings, such as when the data items are moving, when the data items are variable-length (e.g., text strings), or when the allocated amount of internal memory can change dynamically. Programming tools and environments are available for simplifying the EM programming task. During the course of the survey, we report on some experiments in the domain of spatial databases using the TPIE system (transparent parallel I/O programming environment). The newly developed EM algorithms and data structures that incorporate the paradigms we discuss are significantly faster than methods currently used in practice.

https://users.cs.duke.edu/~reif/courses/alglectures/vitter.papers/Vit.IO_survey.pdf

External memory algorithms and data structures: dealing with massive data

A system and method for information searching comprising determination of, in fine granularity, a Community of Interest (COI), further data mining in search results, using at least one of COI and expert preferences to identify important knowledge, formulation and manipulation of results, and summarization of search results into a document like entity with dynamic attributes described. More particularly, the invention relates to a system and method for providing interactive dialogue and iterative search functions to find information on a large network of servers such as the world wide web.

System and method for providing interactive dialogue and iterative search functions to find information

A method for organizing records of a database by topical relevance generates statistics on relevance by monitoring search terms used and search paths traversed by a database user community. Records reviewed most often in relation to a given search term are assumed to be most relevant to that search term in the eyes of members of the user community. Additionally, a record reviewed in relation to a plurality of search terms is determined to be related by topical relevance to other records reviewed in relation to that plurality of search terms. Again, a probability is calculated, based on a frequency of record review and search terms used, as a measure of this record topical relevance. An embodiment directed toward Internet searches provides for seeding the probability calculations with information from labeled data available from open source Internet directories. The activities of the user community are monitored, for example, at a proxy server, or by reviewing proxy server logs. Other monitoring points are contemplated.

Method for organizing records of database search activity by topical relevance

We provide the first optimal algorithms in terms of the number of input/outputs (I/Os) required between internal memory and multiple secondary storage devices for the problems of sorting, FFT, matrix transposition, standard matrix multiplication, and related problems. Our two-level memory model is new and gives a realistic treatment of {\em parallel block transfer}, in which dureing a single I/O each of the $P$ secondary storage devices can simultaneously transfer a contiguous block of $B$ records. The model pertains to a large-scale uniprocessor system or parallel multiprocessor system with $P$ disks. In addition, the sorting, FFT, permutation network, and standard matrixmultiplication algorithms are typically optimal in terms of the amount of internal processing time. The difficulty in developing optimal algorithms is to cope with the partitioning of memory into $P$ separate physical devices. Our algorithms'' performance can be significantly better than those obtained by the well-known but nonoptimal technique of disk striping. Our optimal sorting algorithm is randomized, but practical; the probability of using more than $\ell$ times the optimal number of I/Os is exponentially small in $\ell$ (log $\ell$)log($M/B$), where $M$ is the internal memory size.

/pdf/algorithms-for-parallel-memory-i-two-level-memories-7exq6np2kq.pdf

Algorithms for parallel memory, I: Two-level memories

Modern disk drives read-ahead data and reorder incoming requests in a workload-dependent fashion. This improves their performance, but makes simple analytical models of them inadequate for performance prediction, capacity planning, workload balancing, and so on. To address this problem we have developed a new analytic model for disk drives that do readahead and request reordering. We did so by developing performance models of the disk drive components (queues, caches, and the disk mechanism) and a workload transformation technique for composing them. Our model includes the effects of workload-specific parameters such as request size and spatial locality. The result is capable of predicting the behavior of a variety of real-world devices to within 17% across a variety of workloads and disk drives.

An analytic behavior model for disk drives with readahead caches and request reordering

In this paper we introduce parallel versions of two hierarchical memory models and give optimal algorithms in these models for sorting, FFT, and matrix multiplication. In our parallel models, there are $P$ memory hierarchies operating simultaneously; communication among the hierarchies takes place at a base memory level. Our optimal sorting algorithm is randomized and is based upon the probabilistic partitioning technique developed in the companion paper for optimal disk sorting is a two-level memory with parallel block transfer. The probability of using $\ell$ times the optimal running time is exponentially small in $\ell$(log $\ell$)log $P$.

/pdf/algorithms-for-parallel-memory-ii-hierarchical-multilevel-2fvnigccfm.pdf

Elizabeth Shriver

Papers

System and method for providing interactive dialogue and iterative search functions to find information

Method for organizing records of database search activity by topical relevance

Algorithms for parallel memory, I: Two-level memories

An analytic behavior model for disk drives with readahead caches and request reordering

Algorithms for Parallel Memory II: Hierarchical Multilevel Memories