Most conventional query-biased summarization methods generate the summary using extracted sentences based on similarity measure between all sentences in a document and the query. If there are plural sentences having high similarity to the query in the document, these methods cannot decide the sentence which the summary should be from. This paper proposes an algorithm adopting new indicator that shows the difference between one paragraph and the others. In a word space which is composed of all words in the target document, the algorithm determines the axis that maximizes the difference when a paragraph and the others are projected onto it. There are many combinations of a paragraph and a set of other paragraphs. For each combination, the above-mentioned axis that maximizes the difference and gives a conformity degree to the given query is calculated. With these conformities, the algorithm decides one paragraph for generating the summary. To obtain the axis, topic distinctiveness factor analysis is applied. The basic idea for making final summary is concatenating the sentences extracted from the paragraph. The resultant summary is evaluated from the following points of view: readability, understandability and the easiness to judge whether the link works well or not.