Will We Connect Again? Machine Learning For Link Prediction In Mobile Social Networks, Ole J. Mengshoel, Raj Desai, Andrew Chen, Brian Tran
Jul 2013
Will We Connect Again? Machine Learning For Link Prediction In Mobile Social Networks, Ole J. Mengshoel, Raj Desai, Andrew Chen, Brian Tran
Ole J Mengshoel
In this paper we examine link prediction for two types of data sets with mobility data, namely call data records (from the MIT Reality Mining project) and location-based social networking data (from the companies Gowalla and Brightkite). These data sets contain location information, which we incorporate in the features used for prediction. We also examine different strategies for data cleaning, in particular thresholding based on the amount of social interaction. We investigate the machine learning algorithms Decision Tree, Naïve Bayes, Support Vector Machine, and Logistic Regression. Generally, we find that our feature selection and filtering of the data sets have …
Latent Topic Analysis For Predicting Group Purchasing Behavior On The Social Web, Feng-Tso Sun, Martin Griss, Ole J. Mengshoel, Yi-Ting Yeh
Jun 2013
Latent Topic Analysis For Predicting Group Purchasing Behavior On The Social Web, Feng-Tso Sun, Martin Griss, Ole J. Mengshoel, Yi-Ting Yeh
Ole J Mengshoel
Group-deal websites, where customers purchase products or services in groups, are an interesting phenomenon on the Web. Each purchase is kicked o#11;ff by a group initiator, and other customers can join in. Customers form communities with people with similar interests and preferences (as in a social network), and this drives bulk purchasing (similar to online stores, but in larger quantities per order, thus customers get a better deal). In this work, we aim to better understand what factors in influence customers' purchasing behavior for such social group-deal websites. We propose two probabilistic graphical models, i.e., a product-centric inference model (PCIM) …
Multi-Focus And Multi-Level Techniques For Visualization And Analysis Of Networks With Thematic Data, Michele Cossalter, Ole J. Mengshoel, Ted Selker
Jan 2013
Multi-Focus And Multi-Level Techniques For Visualization And Analysis Of Networks With Thematic Data, Michele Cossalter, Ole J. Mengshoel, Ted Selker
Ole J Mengshoel
Information-rich data sets bring several challenges in the areas of visualization and analysis, even when associated with node-link network visualizations. This paper presents an integration of multi-focus and multi-level techniques that enable interactive, multi-step comparisons in node-link networks. We describe NetEx, a visualization tool that enables users to simultaneously explore different parts of a network and its thematic data, such as time series or conditional probability tables. NetEx, implemented as a Cytoscape plug-in, has been applied to the analysis of electrical power networks, Bayesian networks, and the Enron e-mail repository. In this paper we briefly discuss visualization and analysis of …