Research on User Requirements Elicitation Using Text Association Rule
Lili Dong, Xiang Zhang, Na Ye, Xiaoge Wan · 2010
User requirements obtained through text data mining are very important to improve the competitiveness of enterprises. In this paper an algorithm of acquiring user requirements in machinery products by using text association rule is proposed. In the algorithm, the user requirement documents are represented by vector space model. The feature words matrix is obtained by transposing the documents matrix. An improved text association rule theory based on gray association rule is used to calculate the correlation degree between feature words and proper nouns of machinery industry. Then the matrix of candidates for proper noun is constructed by selecting a higher correlation degree word as a threshold. Finally, user requirements are obtained by using the weighted matrix. The experimental results suggest that the proposed method is feasible for user requirement elicitation.