Jianxing Zheng

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Online social network has obtained a significant increase in recent years. Making friends is an ordinary way of establishing social relationships with others in online social network. Therefore friend recommendation is becoming a very important aspect and attracting extensive attention in visual communities and social network. Among various online social(More)
The situations of context absence and sparse feature in short texts present a challenge to effective personalized service, especially in the recommend short texts, widened semantic gap between low-level text features representation and high-level interpretation. Meanwhile, the propagation characteristics of short texts also have an effect on the results of(More)
The traditional personalized recommendation system supplies the target user with top k items in fixed interest subject. However, the recommended items cover the coarse subject level and the accuracy performance is poor. Taking into account ontology structure of subject, user's actual interests can distribute in multiple sub-subject structures. In this(More)
In recent years, cloud computing is gradually evolving as a popular computing paradigm, which offers a uniform platform for service providers to publish their applications as cloud services. In many cases, however, single cloud service cannot satisfy a service request due to its simple functionality. Furthermore, current service composition systems have(More)
In the micro-blog scenario, personal user profiling relying on content is limited for recommending desired diverse subjects due to its shortcomings of short text, often leading to a poor recall. Currently, many methods only utilized the personal knowledge from each individual user to represent user profile without considering the neighborhood information.(More)
The traditional personalized recommendation system measures the quality of recommendation performance by the indicators of precision and recall. User model based on user browsing behavior plays an increasingly important role in personalized recommendation systems. The evaluation of user model is significant for personalized recommendation systems, which(More)
“U-Business” is a novel type business environment, which can provide various services via many mobile devices. In order to provide personalized service to different users, user model (UM) can play an important role in U-Business. UM reflects some characteristics of users to a certain degree, which is used widely in U-Business, like personalized(More)
In recent years, there has been an increasing interest in user modeling, because of its extremely wide usage in real world applications, such as recommendation systems and personalized services. However, a large number of researchers have been devoted to focusing on developing a user model that can only facilitate their own applications, which has limited(More)
With the explosive development of Internet and Social Networking Services (SNS), more and more people begin to get information from others. So how to find users, which have similar interests, is becoming an important issue. The traditional method is using a vector to calculate the similarities between user models. The similarities between user models are(More)
Sentiment analysis is widely applied in product reviews, movie reviews, Twitter and Microblog. In this paper, we throw light on sentiment classification of topical Chinese Microblog, namely, analysis sentiment express style of Microblog, and then classify Microblog to positive, negative or neutral according to sentiment of Microblog. Moreover, the(More)