Smartphone help contents re-organization considering user specification via conditional GAN

There are various help systems embedded in smartphones that are intended to provide assistance to users. These systems should be conveniently accessible in locations where users may need assistance. Moreover, when help contents are provided without regard to the users interest, it makes it difficult for the user to find relevant content. Thus, the present study provides a new method of re-organizing help content by considering each users interests and preferences using their app usage sequence. Based on the user specification derived from the app usage sequence, help contents usage prediction is generated for each of them with conditional generative adversarial network (GAN) architecture in a new way. Further, another method to pre-process data in applying conditional GAN, originally devised to generate image data, is proposed in our problem. The experiment result showed a higher absolute performance level of help contents usage prediction and better performance of effectiveness in re-organization of top-k contents compared to the existing benchmark method. Thus, the proposed method reflects the users interest and provides appropriate help contents for each user effectively.