18690541
Real-time author co-citation mapping for online searching
Author searching is traditionally based on the matching of name strings. Special characteristics of authors as personal names and subject indicators are not considered. This makes it difficult to identify a set of related authors or to group authors by subjects in retrieval systems. In this paper, we describe the design and implementation of a prototype visualization system to enhance author searching. The system, called AuthorLink, is based on author co-citation analysis and visualization mapping algorithms such as Kohonen's feature maps and Pathfinder networks. AuthorLink produces interactive author maps in real time from a database of 1.26 million records supplied by the Institute for Scientific Information. The maps show subject groupings and more fine-grained intellectual connections among authors. Through the interactive interface the user can take advantage of such information to refine queries and retrieve documents through point-and-click manipulation of the authors' names.
21113165
Graphical representations of electronic search patterns
Increasing numbers of researchers and developers are collecting data that trace the processes of humancomputer interactions. Although a variety of methods are used to collect such data, all researchers share common problems in representing and analyzing continuous streams of data. A set of methods and tools for graphically representing the search patterns of users interacting with a variety of databases and hypertexts is under development as part of ongoing research in electronic information seeking. The methodology described in this article involves defining state spaces of user options within a system, capturing keystrokes or mouse moves as raw data, coding these data into the state spaces, and analyzing user moves through the state space as evidence of goal-directed informationseeking strategies and patterns. A tool for displaying user moves through a state space has been developed and is described. The tool graphically represents data in a variety of formats, allowing human pattern recognition capabilities to be applied for data analysis. Graphs can be represented for individual searches or for multiple searches done by either a single searcher or by several searchers working on the same search task.
18241581
An Associative Information Visualizer
The following item is made available as a courtesy to scholars by the author(s) and Drexel University Library and may contain materials and content, including computer code and tags, artwork, text, graphics, images, and illustrations (Material) which may be protected by copyright law. Unless otherwise noted, the Material is made available for non profit and educational purposes, such as research, teaching and private study. For these limited purposes, you may reproduce (print, download or make copies) the Material without prior permission. All copies must include any copyright notice originally included with the Material. You must seek permission from the authors or copyright owners for all uses that are not allowed by fair use and other provisions of the U.S. Copyright Law. The responsibility for making an independent legal assessment and securing any necessary permission rests with persons desiring to reproduce or use the Material.
2535403
Visualization for the document space
An information retrieval frame work that promotes graphical displays, and that will make documents in the computer visualizable to the searcher, is described. As examples of such graphical displays, two simulation results of using a Kohonen feature map to generate map displays for information retrieval are presented and discussed. The map displays are a mapping from a high-dimensional document space to a two-dimensional space. They show document relationships by various visual cues, such as dots, links, clusters, and areas, as well as their measurement and spatial arrangement. Using the map displays as an interface for document retrieval systems, the user is provided with richer visual information to support browsing and searching.<<ETX>>
207195547
Graphical table of contents
This paper proposes a graphical table of contents (GTOC) that is functionally analogous to the table of contents. The proposed GTOC can be generated automatically from the text of documents. It visualizes document contents and relationships to allow easy access of underlying documents. It also provides various interactive tools to let the user explore the documents. Issues of how to generate such GTOC include how documents are indexed and organized, how the organized documents are visualized, and what interactive means are needed to provide necessary functionality of GTOC. These issues are discussed in this paper with a GTOC prototype based on Kohonen’s selforganizing featore map algorithm.
32681772
Visual MeSH
Visual MeSH is a graphical interface developed to interact with real world databases such as the National Library of Medicine’s MetaThesaurus and MEDLINE. Visual MeSH makes it easy for the user to browse complex relationships through visual representation of thesaurus structures. It helps the user to select controlled vocabulary terms for online searching in the click-andchoose environment.
4018890
Clustering Moving Objects for Spatio-temporal Selectivity Estimation
Many spatio-temporal applications involve managing and querying moving objects. In such an environment, predictive spatio-temporal queries become an important query class to be processed to capture the nature of moving objects. In this paper, we investigated the problem of selectivity estimation for predictive spatio-temporal queries. We propose a novel histogram technique based on a clustering paradigm. To avoid expensive computation costs, we developed linear time heuristics to construct such a histogram. Our performance study indicated that the new techniques improve the accuracy of the existing techniques by one order of magnitude.
2200679
A Distributed Joint Channel-Assignment, Scheduling and Routing Algorithm for Multi-Channel Ad-hoc Wireless Networks
The capacity of ad hoc wireless networks can be substantially increased by equipping each network node with multiple radio interfaces that can operate on multiple non-overlapping channels. However, new scheduling, channel-assignment, and routing algorithms are required to fully utilize the increased bandwidth in multi-channel multi-radio ad hoc networks. In this paper, we develop a fully distributed algorithm that jointly solves the channel-assignment, scheduling and routing problem. Our algorithm is an online algorithm, i.e., it does not require prior information on the offered load to the network, and can adapt automatically to the changes in the network topology and offered load. We show that our algorithm is provably efficient. That is, even compared with the optimal centralized and offline algorithm, our proposed distributed algorithm can achieve a provable fraction of the maximum system capacity. Further, the achievable fraction that we can guarantee is larger than that of some other comparable algorithms in the literature.
14249190
Text-mining based journal splitting
This paper introduces a novel journal splittingalgorithm. It takes full advantage of various kinds ofinformation such as text match, layout and page numbers.The core procedure is a highly efficient text-miningalgorithm, which detects the matched phrases between thecontent pages and the title pages of individual articles.Experiments show that this algorithm is robust and ableto split a wide range of journals, magazines and books.
6221918
Efficiently Matching Proximity Relationships in Spatial Databases
Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. In this paper, we investigate a proximity matching problem among clusters and features. The investigation involves proximity relationship measurement between clusters and features. We measure proximity in an average fashion to address possible nonuniform data distribution in a cluster. An efficient algorithm, for solving the problem, is proposed and evaluated. The algorithm applies a standard multistep paradigm in combining with novel lower and upper proximity bounds. The algorithm is implemented in several different modes. Our experiment results do not only give a comparison among them but also illustrate the efficiency of the algorithm.
6238577
Labeling Scheme and Structural Joins for Graph-Structured XML Data
When XML documents are modeled as graphs, many challenging research issues arise. In particular, query processing for graph-structured XML data brings new challenges because traditional structural join methods cannot be directly applied. In this paper, we propose a labeling scheme for graph-structured XML data. With this labeling scheme, the reachability relationship of two nodes can be judged efficiently without accessing other nodes. Based on this labeling scheme, we design efficient structural join algorithms to evaluate reachability queries. Experiments show that our algorithms have high efficiency and good scalability.