在不動產市場中，如何對商品價值正確地評估是一項很重要的課題，舉凡買賣交易、抵押貸款及投資評估等，都有對不動產估價的需求。然而影響不動產價格的因素眾多，同時相關估價技術繁雜，因此實務上常常由專業人員依選定的估價技術，輔以評估類似案例的過去經驗來估價，也就是估價流程中常用的買賣實例法。
案例推理系統（Case-Based Reasoning, CBR）是一種決策領域中廣受重視的推論式系統架構，其作法為將過去的案例儲存起來，當碰到問題時再從案例庫中搜尋相似的案例來提供解決方案，運作方式接近人類處理問題的方式。在概念上也與買賣實例法近似。
根據過去文獻顯示，案例推理系統在決定案例之間的相似度時，屬性權重對案例選擇的結果會有顯著的影響，在傳統的案例推理系統中，屬性權重通常是由問題領域的專家來決定的，在相當程度上可能會有人為判定的錯誤。因此本研究擬採用啟發式技術中常見的基因演算法（Genetic Algorithm）來決定案例間屬性權重，藉由基因演算法快速搜尋空間最佳解的能力，為各屬性提供一個較合理且一致的權重。最後，透過相似度函數轉換為合適的評估價格，作為輔助不動產買賣價格的評估參考。

Accurate measuring of real estate price is a very important issue in housing market. However, there are many dynamic factors that will influence the quality of house-price evaluating. On the other hand, the traditional evaluating tools are often very difficult to learn and use. Therefore, sales comparison approach, using the price of neighboring house to estimate the target value, is often adopted in the evaluating process because of its simplicity and efficiency. CBR (Case-Based Reasoning) is a well-known methodology of inference system in the decision area. CBR stores the historical cases in the case base, and retrieve the similar case to provide the past solution when dealing a new case. The system works quite like the way that human solving new problem and its principle also correspondences to the sales comparison approach. This paper represents an approach that combines the sales comparison approach and CBR system to provide evaluating value of a housing case. According to the past studies, the attribute weight of a case, usually defined by experts’ experience, may affect the result of case selection in a CBR system. In the prototype system of this paper, the heuristic method, genetic algorithm (GA), is adopted to adjust these attribute weights reasonably and consistently. Finally, the system use a similarity function to convert these attributes values to a suitable evaluating price for decision support. In the following experiment with the Taipei housing cases, the system can provide good estimation of these cases.

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