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This paper presents a SMS-based recommendation system for campus recruitment in China, which can help college placement office to match the companies and students with higher precision and lower cost. We are mainly focusing on profile matching and preference-list-based two-sided matching for further recommendation. With regard to profile matching, three kinds of matching methods (i.e., semantic matching, tree-based knowledge matching and SMS-based query matching) are integrated according to representations of attributes of students and companies, and then the profile similarity degree is acquired. Another focus is to provide two-sided matching from the perspective of central bureau (college placement office). Based on profile similarity degree, the preference lists of companies and students are calculated, which serves as the input of two-sided matching. With the loop matching triggered by the information of SMS-based query interaction, the matching results would be further optimized and provide more effective guidance for recommendation. The new system embedding SMS-based interaction can raise the matching degree, shorten recruiting period and reduce cost. Furthermore, this recommendation service not only is applicable in the field of campus recruitment, but also can provide a framework for the field of mobile business with the extension to other domains such as hospital-intern and college-student matching and recommendation.