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Code review is known to be of paramount importance for software quality assurance. However, finding a reviewer for certain code can be very challenging in Modern Code Review environment due to the difficulty of learning the expertise and availability of candidate reviewers. To tackle this problem, existing efforts mainly concern how to model a reviewer's expertise with the review history, and making...
To reduce the burden on data communication in smart girds, household level distributed energy management systems have become increasingly vital due to their capability of distributed intelligence and scheduling devices. This paper studies the optimal management of storage and electric vehicles at a household level when subject to financial constraints. A model using a real-time pricing structure is...
Twitter has become one of the largest microblogging platforms for users around the world to share anything happening around them with friends and beyond. A bursty topic in Twitter is one that triggers a surge of relevant tweets within a short period of time, which often reflects important events of mass interest. How to leverage Twitter for early detection of bursty topics has therefore become an...
Threaded debate forums have become one of the major social media platforms. Usually people argue with one another using not only claims and evidences about the topic under discussion but also language used to organize them, which we refer to as shell. In this paper, we study how to separate shell from topical contents using unsupervised methods. Along this line, we develop a latent variable model...
This paper analyzes the trustor and trustee factors that lead to inter-personal trust using a well studied Trust Antecedent framework in management science. To apply these factors to trust ranking problem in online rating systems, we derive features that correspond to each factor and develop different trust ranking models. The advantage of this approach is that features relevant to trust can be systematically...
Latent Dirichlet allocation (LDA) is a commonly used topic modeling method for text analysis and mining. Standard LDA treats documents as bags of words, ignoring the syntactic structures of sentences. In this paper, we propose a hybrid model that embeds hidden Markov models (HMMs) within LDA topics to jointly model both the topics and the syntactic structures within each topic. Our model is general...
User behavior models are important for building realistic simulation environment for research on P2P multimedia file-sharing systems. In this paper, we build a user download behavior model and a user removal behavior model, which can describe important user characteristics that are not captured in the existing models. The proposed download behavior model incorporates retry behavior, and the removal...
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