Re: Social Network Link Prediction in Mahout
Thanks Sean, I'm just looking at section 3.3 Coping without preference values of Mahout in Action book, that explains how to work with GenericBooleanPrefDataModel. On 8 June 2013 14:20, Sean Owen sro...@gmail.com wrote: Use an implementation that doesn't expect a rating. These are so-called 'boolean' implementations, like GenericBooleanPrefDataModel. For example you can build and item-based recommender with the boolean version of item based recommender and a log-likelihood similarity. Or, yes you can calculate some meaningful edge weight to add more info to your model. Maybe the number of times the two users interacted? the resulting number can be used as a 'rating' although I don't know if you will get great results since it doesn't act a lot like a rating. Instead, use the log of this number. Or, use an algorithm that is comfortable with count-like input, like ALS with the implicit data option turned on. Sean On Sat, Jun 8, 2013 at 2:15 PM, Peter Holland d1...@mydit.ie wrote: Hi All, I am trying to use Mahout for Link Prediction in a Social Network. The data I have is an edges list with 9.4 million rows. The edge list is a csv vile where each node is an integer value and a row represents a edge between two nodes. For example; 3432, 5098 3423, 6710 4490, 5843 4490, 2039 . This is a directed graph so row 1 means that node 3432 follows node 5098. I would like to build a recommender to calculate the top 10 nodes a user might like to connect to next. The problem I have is that the recommender classes needs input in the form (user, item, value). So, how can I first calculate a value to represent the 'weight' of an edge? For example EdgeRank? Any help would be greatly appreciated. Thank you, Peter
Social Network Link Prediction in Mahout
Hi All, I am trying to use Mahout for Link Prediction in a Social Network. The data I have is an edges list with 9.4 million rows. The edge list is a csv vile where each node is an integer value and a row represents a edge between two nodes. For example; 3432, 5098 3423, 6710 4490, 5843 4490, 2039 . This is a directed graph so row 1 means that node 3432 follows node 5098. I would like to build a recommender to calculate the top 10 nodes a user might like to connect to next. The problem I have is that the recommender classes needs input in the form (user, item, value). So, how can I first calculate a value to represent the 'weight' of an edge? For example EdgeRank? Any help would be greatly appreciated. Thank you, Peter
Re: Social Network Link Prediction in Mahout
Use an implementation that doesn't expect a rating. These are so-called 'boolean' implementations, like GenericBooleanPrefDataModel. For example you can build and item-based recommender with the boolean version of item based recommender and a log-likelihood similarity. Or, yes you can calculate some meaningful edge weight to add more info to your model. Maybe the number of times the two users interacted? the resulting number can be used as a 'rating' although I don't know if you will get great results since it doesn't act a lot like a rating. Instead, use the log of this number. Or, use an algorithm that is comfortable with count-like input, like ALS with the implicit data option turned on. Sean On Sat, Jun 8, 2013 at 2:15 PM, Peter Holland d1...@mydit.ie wrote: Hi All, I am trying to use Mahout for Link Prediction in a Social Network. The data I have is an edges list with 9.4 million rows. The edge list is a csv vile where each node is an integer value and a row represents a edge between two nodes. For example; 3432, 5098 3423, 6710 4490, 5843 4490, 2039 . This is a directed graph so row 1 means that node 3432 follows node 5098. I would like to build a recommender to calculate the top 10 nodes a user might like to connect to next. The problem I have is that the recommender classes needs input in the form (user, item, value). So, how can I first calculate a value to represent the 'weight' of an edge? For example EdgeRank? Any help would be greatly appreciated. Thank you, Peter
