A hashtag based method was proposed to solve the problem how to accurately extract keywords from microblog. Hashtag, the social feature of a microblog was used to extract keywords from microblog content. A word-post weighted graph was built firstly, then a random walker was used on the graph by jumping to any hashtag node repeatedly. At last, every word rank was determined by its probability which would not change after walker iteration. The experiments were conducted on real microblogs from Sina platform. The results show that, compared to word-word graph method, the proposed hashtag-based approach gets higher accuracy of keyword extraction by 50%.

Most of the variants of Graph Cut algorithm do not impose any shape constraints on the segmentations, rendering it difficult to obtain semantic valid segmentation results. As for pedestrian segmentation, this difficulty leads to the non-human shape of the segmented object. An improved Graph Cut algorithm combining shape priors and discriminatively learned appearance model was proposed in this paper to segment pedestrians in static images. In this approach, a large number of real pedestrian silhouettes were used to encode the a'priori shape of pedestrians, and a hierarchical model of pedestrian template was built to reduce the matching time, which would hopefully bias the segmentation results to be humanlike. A discriminative appearance model of the pedestrian was also proposed in this paper to better distinguish persons from the background. The experimental results verify the improved performance of this approach.

Feature dependency modeling describes the model of mutual constraints among features. It is an essential activity for development of software product line. This paper introduced local dependency and global dependency of feature. With analyzing relationship of feature dependency, an approach of feature dependency modeling was proposed. It not only provides specification of local dependency such as decomposition and generalization, but also provides global dependency modeling such as configuration dependency, operational dependency and impact dependency. Finally a case study of feature dependency modeling in air-condition controlling software product line is presented to demonstrate our method.

This paper introduced UML to software product line. With analyzing variability of product line, we propose an approach of variability modeling for software product line with UML. It not only provides specification of variability type such as option and alternative, but also provides constrains modeling of software product line variability. Finally a case study of variability modeling in mobile software product line was presented to demonstrate our method.