A CBR Based Prediction Method for Web Aquatic Products Prices

DOI

10.2991/iske.2007.34How to use a DOI?

Keywords

Aquatic products prices, Forecasting, Attribute-oriented induction, Case-based reasoning

Abstract

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.

Copyright

© 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/).

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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  -