Exploiting Web Search to Access IEEE papers
Bidisha Roy, Machado Joy, Melcia Raj and Gnana Sonica. Article: Exploiting Web Search to Access IEEE papers. IJCA Proceedings on International Conference and workshop on Emerging Trends in Technology (ICWET 2012) icwet(12):28-32, March 2012. Full text available. BibTeX
@article{key:article,
author = {Bidisha Roy and Machado Joy and Melcia Raj and Gnana Sonica},
title = {Article: Exploiting Web Search to Access IEEE papers},
journal = {IJCA Proceedings on International Conference and workshop on Emerging Trends in Technology (ICWET 2012)},
year = {2012},
volume = {icwet},
number = {12},
pages = {28-32},
month = {March},
note = {Full text available}
}
Abstract
Web People Search (WePS) is a desktop application which aims to find relevant pages from the web related to a person’s name. The project work is targeted to design an advanced version of the deep extraction tool using Clustering Algorithm. In this research work, the focus is mainly on querying for personal information of scientists and researchers. The user has to set the proper target name for search, which when completed, the user will receive complete PDF files based on the search. Each group of information items (cluster) will be defined by its key and the user make the choice. The result page will be produced from the chosen clusters. For making the search operationally accurate, we will assume the usage of research and conference doc files as they carry a standard format of name, e-mail ID, publication, images, and links to the full images.
References
- Rabia Nuray-Turan, Zhaoqi Chen, Dmitri V. Kalashnikov, Sharad Mehrotra, “Exploiting Web querying for Web People Search in WePS2” : 18th WWW Conference, April 2009.
- Javier Artiles, Julio Gonzalo, Satoshi Sekine, “WePS 2 Evaluation Campaign: Overview of the Web People Search Clustering Task”, Appeared in ACM SIGIR Conference, July 2008.
- Wahiba Ben Abdessalem Karaa, “Named Entity Recognition Using web Document Corpus”, International Journal of Managing Information Technology (IJMIT) Vol.3, No.1, February 2011.
- Wei Lai, Xiaodi Huang, Ronald Wibowo, and Jiro Tanaka, “An On-Line Web Visualization System with Filtering and Clustering Graph Layout”, IEEE Intelligent Informatics Bulletin (2005), Volume: 5.
- Sculley,”Web-Scale K-Means Clustering”, published in WWW '10 Proceedings of the 19th international conference on World Wide Web.