
## 5.3 Referencing Module

It will be impossible for one group of localised individuals to have exhaustive list of publication that can be used in characterizing the criteria or describing the characteristics of individual species properties. The internet can be used to gather broad-based, multi-lingua, multi-regional and all-encompassing references. In a nutshell, an intelligent agent will improve system referencing. 

## 6.0 Conclusion And Recommendations

It is believed that this work should provide (particularly for LEXSYS) insight for improved system development based on 
- **the power of internet** - **collaborative system development facilities** - **the power of distributed information gathering** - **the power of intelligent agency** 
This paper can be a launch pad for future development not only in LEXSYS but for projects in information system development or even in agricultural projects. It can also be a motivation for greater collaborative work in general. 

## 7.0 Future Possible Research

Most of the contributing authors/researcher involved in the development of LEXYS is biased. 

Their field of research is related to agriculture, they may not provide accepted view for a generalised audience. It will be interesting if LEXSYS can incorporate other disciplines such as pharmacy, medicine, chemistry and biology. This will greatly enhance the its credibility and the usability. 

## Bibliography

Carsky R.J., Weber, G., Robert A.B.C., LEXSYS: a computerized decision-support tool for selecting herbaceous legumes for improved tropical farming systems, http://www.spipm.cgiar.org/news/ccropmgt/results/ccgerm2.htm Hayes C., 1999, Agents in Nutshell-A Very Brief Introduction, *IEEE Transactions on Knowledge and Data* Engineering, **Vol. 11, NO 1., January/February 1999, http://citeseer.nj.nec.com/hayes99agents.html** 
Jagtap, S.S., Ong, C., 1997. Perspectives on issues, needs, and opportunities for agroforestry models. Agroforestry Forum, 8(2):2-4, http://www.nbu.ac.uk/hypar/documents/11ong.pdf Kurt Steiner, GTZ, 2002, Conservation Tillage- Gateway to Food Security and Sustainable Rural Development Crop Residue Management and Cover Crops, In African Conservation Tillage Network, Information Series No. 3, http://www.fao.org/act-network/docs/actis03.pdf Lewis D.D., Schapira R.E., Callan J.P. and Papka R., 1999, Training Algorithms for Linear Text Classifiers, http://citeseer.nj.nec.com/cs?q=%22Training+Algorithms+for+Linear+Text+Classifiers%22&cs=1 Mladenic, D., 1999, Text-Learning and Related Intelligent Agents, IEEE Expert special issues on Application of Intelligent Information Retrieval, July-August 1999, Mohammadian M., 1999, Intelligent Data Mining and Information retrieval from World Wide Web http://citeseer.nj.nec.com/mohammadian02intelligent.html Ramin M, 2000, Agents on the Loose: An Overview of Agent Technologies Sargent, P., 1992. Back to School for a brand new ABC, in Oren Etzioni et al, 1995*, Intelligent Agents on the* Internet: Fact, Fiction, and Forecast from *The Guardian***, 12 March 1992, page 28** 
Weber G.K., Robert A.B.C., Carsky R.J., 1997, Handbook for use of LEXSYS (Legume Expert System): Decision support for integrating herbaceous legumes into farming systems. International Institute of Tropical Agriculture, Ibadan, Nigeria, 31p Wolfgang. P., Achim. N., Machine Learning and Knowledge Representation in the LaboUr Approach to User Modeling, http://www.cs.usask.ca/um99/proc/pohl.pdf 