Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/72689
Title: Latent representation models for user sequential mobility and social influence propagation
Authors: Feng, Shanshan
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2017
Source: Feng, S. (2017). Latent representation models for user sequential mobility and social influence propagation. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: With the increasing popularity of online social media applications, a large amount of data has been generated by users. Based on the user generated data, many research problems have been studied, such as the location-based recommendation and social influence analysis. In this thesis, we investigate the problem of user sequential mobility and the problem of social influence propagation. The main challenge of both problems lies in the difficulty to effectively learn the sequential transition. However, due to the data sparsity, it is hard to model the sequential information by conventional methods. To this end, we resort to the latent representation approach, which is to represent items in a low-dimensional latent space, such that the relations between items are captured by their representations. In addition, based on the social influence propagation in social networks, we study the problem of finding a set of influential users.
URI: http://hdl.handle.net/10356/72689
DOI: 10.32657/10356/72689
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:IGS Theses

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