資料探勘是為了萃取出隱含的、之前未知的、還有潛藏在資料庫中有用的資訊，許多方法已被建議用來取出資訊，最重要的一種便是找出關聯法則，雖然已經有大部分的研究都投入這項議題中，但就我們所知，之前的研究尚未從生物遺傳資料中找出關聯法則。在本論文中，我們用親子樹(Parent Tree)結構來表示家族的遺傳資料，其中的節點被視為家族樹中的成員，有關節點的特徵即為對應的人的特徵，邊(arcs)則為成員間父母的關聯性。在親子樹結構中，我們會指出祖先的特徵如何向下傳給子孫的遺傳規則，並且利用關聯規則的相關技術，來輔助探勘這些有趣的關聯規則。 Data mining is to extract implicit, previously unknown and potentially useful information from databases. Many approaches have been proposed to extract information, and one of the most important ones is finding association rules. Although a large number of researches have been devoted to this subject, to the best of our knowledge, no previous researches find association rules from genealogical data. In this paper, we use a PT (parent tree) to represent the genealogical data of families, where a node can be viewed as a member in the family tree, the features associated with a node as the characteristics of the corresponding person and the arcs as the parental relationships between members. And we will indicate how the characteristics of ancestors are passed down to descendants, and an algorithm containing four stages is proposed to discover the inheritance rules.
