1605324
Using contextual information to improve retrieval performance
In this paper, we propose a contextual retrieval framework which incorporates the user and global contextual information into the probabilistic retrieval model. We investigate different techniques of using contextual information to improve information retrieval performance in details. In particular, (1) we use the related text contextual information for query expansion; (2) we use the granularity information to construct the document level index and paragraph level index; (3) we use the geographic information for filtering. In addition, a new term weighting function BM5O is proposed based on the global context information. This framework is adaptable and extensible. If there is a new context category, we can extend the existing search system to accommodate it. Finally, we report our experimental findings on TREC data sets.
16574049
Feature Selection with Rough Sets for Web Page Classification
Web page classification is the problem of assigning predefined categories to web pages. A challenge in web page classification is how to deal with the high dimensionality of the feature space. We present a feature reduction method based on the rough set theory and investigate the effectiveness of the rough set feature selection method on web page classification. Our experiments indicate that rough set feature selection can improve the predictive performance when the original feature set for representing web pages is large.
2495453
A dual index model for contextual information retrieval
In this paper, we propose a dual index model for contextual IR. For each query, we search against both document level and passage level indexes, and use the corresponding merge function to update the weights for both documents and paragraphs by combining the results from both indexes according to the granularity information in metadata. Experiments on 2004 TREC data show that a significant improvement can be made by using the dual index model.
31363261
Evaluation of Distance Measures for Partial Image Retrieval Using Self-Organizing Map
Digital image libraries are becoming more common and widely used as more visual information is produced at a rapidly growing rate. With this immense growth, there is a need to organize and index these databases so that we can efficiently retrieve the desired images. In this paper, we evaluate the performance of the self-organising maps (SOMs) with different distance measures in retrieving similar images when a full or a partial query image is presented to the SOM. Our method makes use of RGB colour histograms. As the RGB colour space is very large, another SOM is employed to adaptively quantise the colour space prior to generating the histograms. Some promising results are reported.
5254746
Low-power techniques for network security processors
In this paper, we present several techniques for low-power design, including a descriptor-based low-power scheduling algorithm, design of dynamic voltage generator, and dual threshold voltage assignments, for network security processors. The experiments show that the proposed methods and designs provide the opportunity for network security processors to achieve the goals of both high performance and low power.
3017976
Publish/Subscribe Tree Construction in Wireless Ad-Hoc Networks
Wireless ad-hoc publish/subscribe systems combine a publish/subscribe mechanism with wireless ad-hoc networking. The combination, although very attractive, has not been studied extensively in the literature. This paper addresses an important problem of such systems: how to construct an optimal publish/ subscribe tree for routing information from the source to all interested recipients. First we precisely define the optimality of a publish/subscribe tree by developing a metric to evaluate its "efficiency." The optimality metric takes into account both the goal of a publish/subscribe system (i.e., to route a set of events), and the characteristics of an ad-hoc network (for example, devices are resource limited). We propose a greedy algorithm, SHOPPARENT, which builds the publish/ subscribe tree in a fully distributed fashion. A key feature is that this algorithm can be "subscription-aware", allowing it to use publication/subscription information in order to find a better outcome. Our simulations show that SHOPPARENT's performance is within 15% of optimal under normal configurations. We also study the effect of geographically localized subscriptions.
18171732
Data Placement in Intermittently Available Environments
In this paper, we address the problem of data placement in a grid based multimedia environment, where the resource providers, i.e. servers, are intermittently available. The goal is to optimize the system performance by admitting maximum number of users into the system while ensuring user Quality of Service (QoS). We define and formulate various placement strategies that determine the degree of replication necessary for video objects by using a cost-based optimization procedure based on predictions of expected requests under various time-map scenarios and QoS demands. We also devise methods for dereplication of videos based on changes in popularity and server usage patterns. Our performance results indicate the benefits obtained the judicious use of dynamic placement strategies.
8223639
Assignment-based partitioning in a condition monitoring system
A condition monitoring system tracks real-world variables and alerts users when a predefined condition becomes true, e.g., when enemy planes take off, or when suspicious terrorist activities and communication are detected. However, a monitoring server can easily get overwhelmed by rapid incoming data. To prevent this, we partition the condition being monitored and distribute the workload onto several independent servers. In this paper, we study the problem of how to make a partitioned system behave “equivalently” to a one-server system. We identify and formally define three desirable properties of a partitioned system, namely, orderedness, consistency, and completeness. We propose assignment-based partitioning as a solution that can handle opaque conditions and simplifies load balancing. We also look at a few typical partitioned systems, and discuss their merits using several metrics that we define. Finally, an algorithm is presented to reduce complex system configurations to simpler ones.