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Recent years have witnessed the fast development of multimedia platforms in China, such as Youku, LeTV and Weibo. Images and videos are usually uploaded with textual descriptions, such as titles and introductions of these media. These texts are the key to multimedia content understanding, and this paper is dedicated to multimedia understanding with visual content entailment via recognizing semantic entailment in these texts. In fact, the natural language processing community has been manifesting increasing interest in semantic entailment recognition in English texts. Yet, so far not much attention has been paid to semantic entailment recognition in Chinese texts. Therefore, this paper investigates on multimedia semantic entailment with Chinese texts. Recognizing semantic entailment in Chinese texts can be cast as a classification problem. In this paper, a classification model is constructed based on support vector machine to detect high-level semantic entailment relations in Chinese text pair, including entailment and non-entailment for the Binary-Class and forward entailment, reverse entailment, bidirectional entailment, contradiction and independence for the Multi-Class. We explore different semantic feature combinations based on three kinds of Chinese textual features, including Chinese surface textual, Chinese lexical semantic and Chinese syntactic features, and utilize them to feed our classification model. The experiment results show that the accuracy of our classification model for semantic entailment recognition with the feature combination using all the three kinds of Chinese textual features achieves a much better performance than the baseline in Multi-Class and slightly better results than the baseline in the Binary-Class. [ABSTRACT FROM AUTHOR]

Wechat has become a popular way in China for users to connect and share information with their friends. In particular, Wechat Friends Circle is a popular platform for users to express themselves. It is useful in many real applications, such as personalized recommendations, to calculate the relationship strength between Friends Circle users. However, most existed researches do not apply to the Wechat Friends Circle due to the uniqueness that users can only see a common friend's comments or point praise, which is quite different from the general social network. To meet this need, in this paper we propose a general framework to measure the relationship strengths between different users in Wechat Friends Circle, considering not only the similarity of users’ profile information, but also the interaction between users. We conduct a set of experiments on Friends Circle dataset, from which we learn that the proposed framework is efficient and promising on improving the performances of relationship strength calculation. [ABSTRACT FROM AUTHOR]