Titlebook: Optimization, Variational Analysis and Applications; IFSOVAA-2020, Varana Vivek Laha,Pierre Maréchal,S. K. Mishra Conference proceedings 20

實(shí)現(xiàn)

J.-P. Dussault,M. Haddou,T. Migotit words in tweets) are greatly affected by the sparsity of the short tweet texts and the low co-occurrence rates of hashtags in tweets. Meanwhile, semantically related hashtags but using different text-expressions may show similar temporal patterns (i.e., the frequencies of hashtag usages changing

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屈尊

Nidhi Sharma,Jaya Bisht,S. K. Mishran (NMF) based methods have been proved to be effective in the task of community detection. However, real-world networks could be noisy and existing NMF based community detection methods are sensitive to the outliers and noise due to the utilization of the squared loss function to measure the quality

adumbrate

thyroid-hormone

Decimate

自傳

熱情贊揚(yáng)

Walter Cedric Simo Tao Lee) within the allocated budget whose initial activation leads to the maximum number of influenced nodes. In reality, the influence probability between two users depends upon the context (i.e., tags). However, existing studies on this problem do not consider the tag specific influence probability. To

拔出

Vivek Laha,Rahul Kumar,Harsh Narayan Singh,S. K. Mishra) within the allocated budget whose initial activation leads to the maximum number of influenced nodes. In reality, the influence probability between two users depends upon the context (i.e., tags). However, existing studies on this problem do not consider the tag specific influence probability. To

ACTIN

Balendu Bhooshan Upadhyay,Priyanka Mishratagged events. These event-traces often manifest in hidden (possibly overlapping) communities of users with similar interests. Inferring these implicit communities is crucial for forming user profiles for improvements in recommendation and prediction tasks. Given only time-stamped geo-tagged traces