Publication Date

2008

Degree Type

Master's Project

Degree Name

Master of Science (MS)

Department

Computer Science

Abstract

Visualization is a concept where we can represent some raw data in the form of graphs, images, charts, etc. which will be very helpful for the end-user to correlate and be able to understand the relationships between the data elements in a single screen. Representing the bibliographic information of the computer science journals and proceedings using Visualization technique would help user choose a particular author and navigate through the hierarchy and find out what papers the author has published, the keywords of the papers, what papers cite them, the co-authors along with the main author, and how many papers are published by the author selected by the user and so on in a single page. These information is right now present in a scattered manner and the user has to search on websites like Google Scholar [1], Cite Seer [2] to get these bibliographic records. By the use of visualization techniques, all the information can be accessed on a single page by having a graph like points on the page, where the user can search for a particular author and the author and its co-authors are represented in the form of points. The goal of this project is to enhance current bibliography web services with an intuitive interactive visualization interface and to improve user understanding and conceptualization. In this project, we develop a simple web-interface which will take a search query from the user and find the related information like author's name, the co-authors, number of papers published by him, related keywords, citations referred etc. The project uses the bibliographic records which are available as XML files from the Citeseer database[2], extracts the data into the database and then queries the database for the results using a web service. The data which is extracted is then presented visually to allow the user to conceptualize the results in a better way and help him/her find the articles of interest with utmost ease. In addition the user can interactively navigate the visual results to get more information about any of the article or the author displayed. So here we present both paper centric view and author centric view to the user by representing data in terms of graphs. The nodes in the graphs obtained for paper centric views and author centric views are color coded based on the paper’s weight parameter ( popularity of the paper ). For the paper centric view, the papers which are referring other papers are represented by providing a directed arrow from referred paper to referenced paper. Overall the idea here was to represent this related data in the form of a tree, so that the user can correlate all the data and get the relationships between them.

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