The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Analyst-Ready Large Scale Real Time Information Retrieval Tool for E-Governance
|
|
Author(s): Eugene Santos Jr. (Dartmouth College, USA), Eunice E. Santos (Virginia Polytechnic Institute & State University, USA), Hien Nguyen (University of Wisconsin, Whitewater, USA), Long Pan (Virginia Polytechnic Institute & State University, USA)and John Korah (Virginia Polytechnic Institute & State University, USA)
Copyright: 2009
Pages: 27
Source title:
E-Government Diffusion, Policy, and Impact: Advanced Issues and Practices
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-60566-130-8.ch016
Purchase
|
Abstract
With the proliferation of the Internet and rapid development of information and communication infrastructure, E-governance has become a viable option for effective deployment of government services and programs. Areas of E-governance such as Homeland security and disaster relief have to deal with vast amounts of dynamic heterogeneous data. Providing rapid real-time search capabilities for such databases/sources is a challenge. Intelligent Foraging, Gathering, and Matching (I-FGM) is an established framework developed to assist analysts to find information quickly and effectively by incrementally collecting, processing and matching information nuggets. This framework has previously been used to develop a distributed, free text information retrieval application. In this chapter, we provide a comprehensive solution for the E-GOV analyst by extending the I-FGM framework to image collections and creating a “live” version of I-FGM deployable for real-world use. We present a Content Based Image Retrieval (CBIR) technique that incrementally processes the images, extracts low-level features and map them to higher level concepts. Our empirical evaluation of the algorithm shows that our approach performs competitively compared to some existing approaches in terms of retrieving relevant images while offering the speed advantages of a distributed and incremental process, and unified framework for both text and images. We describe our production level prototype that has a sophisticated user interface which can also deal with multiple queries from multiple users. The interface provides real-time updating of the search results and provides “under the hood” details of I-FGM processes as the queries are being processed.
Related Content
|
Serpil Kır Elitaş.
© 2023.
11 pages.
|
|
Sami Kiraz.
© 2023.
14 pages.
|
|
Kadir Bendaş.
© 2023.
10 pages.
|
|
Fatih Değirmenci.
© 2023.
15 pages.
|
|
Elifnur Terzioğlu.
© 2023.
14 pages.
|
|
Türker Elitaş.
© 2023.
16 pages.
|
|
Sudeep Uprety.
© 2023.
14 pages.
|
|
|