A CBR Based Prediction Method for Web Aquatic Products Prices
Hongchun Yuan1, Ying Chen, Jinling Ju
1College of Information Technology, Shanghai Fisheries University
Available Online October 2007.
- 10.2991/iske.2007.34How to use a DOI?
- Aquatic products prices, Forecasting, Attribute-oriented induction, Case-based reasoning
The ability to scientifically forecast the price of aquatic products plays an important role in the healthy and sustainable development of aquaculture. This paper presents a method for forecasting aquatic product prices using Case-Based Reasoning. Some key processes include automatic extraction of web data, attribute-oriented induction based on concept hierarchy, generation and representation of cases, cases matching and similarity calculation, case evaluation and revision. An application has been implemented using these processes. Experiments have shown that the system can automatically extract web data from multiple websites with information on aquatic product prices and can effectively analyze and forecast prices accordingly.
- © 2007, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Hongchun Yuan AU - Ying Chen AU - Jinling Ju PY - 2007/10 DA - 2007/10 TI - A CBR Based Prediction Method for Web Aquatic Products Prices BT - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007) PB - Atlantis Press SP - 195 EP - 200 SN - 1951-6851 UR - https://doi.org/10.2991/iske.2007.34 DO - 10.2991/iske.2007.34 ID - Yuan2007/10 ER -