Notice of Violation of IEEE Publication Principles: A foundation for knowledge system with application in information retrieval and knowledge acquisition

Notice of Violation of IEEE Publication Principles

"A Foundation for Knowledge System with Application in Information Retrieval and Knowledge Acquisition,"
by Zhi Teng, Ye Liu, Fuji Ren,
in the Proceedings of the International Conference on Natural Language Processing and Knowledge Engineering, 2008. NLP-KE '08, Oct. 2008

After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

This paper contains significant portions of original text from the papers cited below. The original text was copied with insufficient attribution.

"Beyond SumBasic: Task-focused Summarization with Sentence Simplification and Lexical Expansion"
by L. Vanderwende, H. Suzuki, C. Brockett, A. Nenkova
in Information Processing and Management, Vol 43, Elsevier, 2007, pp 1606-1618

"The Use of Domain-specific Concepts in Biomedical Text Summarization"
by L. Reeve, H. Han, A. Brooks,
in Information Processing and Management, Vol 43, Elsevier 2007, pp. 1765-1776

"Sentences Optimum Selection for Multi-document Summarization"
by B. Qin, T. Liu, S. Chen, S. Li
in the Journal of Computer Research and Development, Institute of Computer Technology, Dec 2007, pp. 67-74

"READING: A Self Sufficient Internet News System with Applications in Information and Knowledge Mining"
by D. Bracewell, F. Ren, K. Hisazumi, Z. Teng, Y. Furose
in the Proceedings of the International Conference on Natural Language Processing and Knowledge Engineering, 2007. NLP-KE 2007, Aug. 2007, pp. 190-196

"A Foundation for Japanese-English Cross-lingual Information Retrieval and Knowledge Acquisition from News"
by D. Bracewell
in his Ph.D Thesis, University of Tokushima, 2007


We present a knowledge system, which is a self sufficient system for aggregating, extraction and classifying news from around the world. This paper present some algorithms for monitoring and gathering news from RSS and websites, creating special domain corpora. The system, however, goes beyond the traditional news aggregation sites by mining information and knowledge from the news articles to aid in such tasks as decision making. The system is able to collect, classify and mine knowledge automatically without the need for an editor or intervention by an administrator. As knowledge system, average users, news professionals and researchers alike will find that the system offers something for them. Our work shows that better performance is achieved and the result showed that this method has potential in this field.