Questions tagged [recommender-system]

Everything related to recommender systems

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29 views

How to preprocess raw data in the form RDF triples to perform Information Gain and Principal Component Analysis? [closed]

I have my dataset in the form RDF triples in various domains such as Movie, music etc. Data is in the form of RDF triples (Subject, Property,Object (all uris). A sample input in the movie domain is ...
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38 views

How to match prospective buyers with sellers based on their profile data?

I am working on a problem to match buyers and sellers in a B2B marketplace. The main aim is to provide relevant recommendations to buyers about sellers that they might be interested in. I am planning ...
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1answer
185 views

What's the best classification model for this recommendation engine?

I'm not a data scientist but I'm trying to implement a recommendation engine on my company. My application runs on PHP but I'll use Python to process this data. My company is an online school, with ...
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0answers
33 views

What Algorithm to use for course path

If I want to suggest a course path for a student who wanted to be a chemical engineering where each degree has to go through certain mandatory courses like math ,physics chemistry . Again to complete ...
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1answer
695 views

Best way to extract information from text description and match it with set of words

I have 10k records of data, each record represents a unique product(10k class labels) and its description. For example, "Coffee Maker, this product takes coffee beans and brew it, to make tasty cofe". ...
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1answer
272 views

Is this the correct way to apply a recommender system based on KNN and cosine similarity to predict continuous values?

My data is: userID, gameID, rating (1.0 through 10.0) First, I normalize the values the ratings of each row. I use cosine similarity to create a similarity matrix where each cell represents similarity ...
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2answers
81 views

Matrix Factorisation Improvement

I am using SGD matrix factorisation (python) using the movielens dataset to make recommendations. I have a website which allows users to give feedback which is positive or negative to whether an item ...
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0answers
132 views

Binary (Unary) Recommendation System with Biased Views

I would like to create a content recommendation system based on binary click data that also takes views into account. What content a user has been exposed to, and therefore has the chance to click ...
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0answers
59 views

How to build a proper Source Code dataset for Machine Learning?

I have been given a project in which my goal is to create a Machine Learning Recommender system that makes Source Code Recommendations(in Python Code) for lets say 10 basic statements (for, if, with, ...
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2answers
65 views

Recommending college degrees based on high school subjects

I have a list of our college students' high school courses. I want to recommend college degrees to current high school students based on their courses - that is, predict a class based on a vector. ...
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1answer
24 views

Data normalisation and recommendation based on skillset

Given the job title return the skillset required for the job If a user is lacking some skills required for the job, we have to suggest the courses the user has to take to bridge the gap. Problem ...
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0answers
31 views

Multiple Seeds Content Based filtering Recommender System

I want to create a content based filtering recommender system which has multiple seeds. All that I have read about is having an initial seed from which the recommendations should be similar to. This ...
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1answer
857 views

benchmark Result for MovieLens dataset?

I am looking for a benchmark result or any kaggle competition held using MovieLens(20M or latest) dataset. Similar question has been asked here but, provided links are dead so re-raising the question.
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2answers
89 views

Is there any standard pattern recognition algorithm in predicting an item which a user will be buying next, given I have the history of the purchases

I am having a list of 10 different items a user has bought in the past. Each item has been bought multiple times. I would like to find a pattern in which the user buys a particular item and predict ...
4
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1answer
234 views

How to deal with position bias in search?

In search, position of the search result affects the click-through rate a great deal. How do people usually deal with this ? In practice how to remove such bias to create unbiased training data for ...
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0answers
19 views

Recommender system: Give a feature more significance than another

I am trying to build a recommender system that predicts hotel prices based on a great number of features. I have a column representing the hotel rating out of 5 and another column indicating the ...
2
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2answers
47 views

distinguish users for recommender system

How can you calculate better video recommendations for a SmartTV app which is used by multiple users in a household. I don't know which user is currently watching the video because the account for the ...
2
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1answer
187 views

How does a Recommender System recommend movies to a New User?

Consider a New user which has never rated any movie on the Website or the System has never seen the user. How does the System recommend Movies to the User and based on what ? How will we evaluate ...
2
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2answers
77 views

Predict the next player's option for betting based on playing history?

I have a project which is to predict in next time, which option player will select for betting. This prediction based on his history. For example, the player have time series data, the last options ...
1
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1answer
213 views

Which algorithm should be used for an accurate job recommendation system

I'm building a testing project to get an introduction to DS & ML. As a person part of the working force, sometimes finding a job is harder than it should be. I thought I could built a testing ...
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2answers
1k views

ROC-AUC loss for GRU Model: Cannot use tflearn's loss in keras

I am trying to use tflearn.objectives.roc_auc_score as a loss function for a GRU network in Keras but I get the following error: ...
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0answers
116 views

Milestones of data science project [closed]

I'm looking at working on a machine learning project for a company, where they are interested in paying in instalments at certain milestones in the project. My initial thoughts are that how to define ...
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1answer
481 views

Visualizing item similarities [closed]

I have an implicit dataset. It contains which user click which item. I'm doing collaborative filtering and finally i get the item similarites. So now i have data like; ...
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0answers
58 views

Initialize a recommender system with no dataset

Consider a platform for content recommendation based on the user history. The contents are books and articles and by history I mean what the user has read, what he has shared and so on. I know that ...
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0answers
48 views

How does SVD actually provide the recommendations? I seem to get conflicting answers

I am reading a text book that basically says the following: Given a matrix A where A is USERS x ITEMS we can use SVD to decompose the matrix into: $$A = U \times \Sigma \times V^T$$ Then we can take ...
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1answer
496 views

How exactly does matrix factorization help with collaborative filtering

We start with a matrix of user ratings for different movies with some elements unknow i.e the rating of a yet to be seen movie by an user. We need to fill in this gap. So How can you decompose or ...
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1answer
51 views

I have 50 videos. I ask a customer 10 questions. Based on their answers, I send them a set of videos. How do I do it?

This might make you feel like I am looking for a recommender engine, but I am not. A recommender engine works well if accuracy isn't an issue, but in my case, it is. What I have proposed is to ...
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0answers
33 views

How does a feature learning component work [closed]

I've been studying a paper on Recommender systems using collaborative deep learning where in a hierarchical bayesian model called collaborative deep learning is developed. Stacked denoising ...
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2answers
5k views

Can I use cosine similarity as a distance metric in a KNN algorithm

Most discussions of KNN mention Euclidean,Manhattan and Hamming distances, but they dont mention cosine similarity metric. Is there a reason for this?
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1answer
103 views

What is local-NMF? How is it better than original NMF?

I am reading this paper, but don't really understand. Do the words "part-based" or "local" for non-negative matrix factorization (NMF) mean that the algorithm aims to factorize some specific parts ...
1
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1answer
477 views

Calculate similarity on boolean data

I am trying to implement simple recommender system and I am trying to understand different approaches to achieve my goal. My dataset consists of users and items that they bought. I have information ...
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1answer
157 views

In a recommender system, how can you normalise the similarity between two arbitrary users?

Consider the following problem: There are 1000 users, 100 items (movies, for example), and 10000 ratings. The probability of a user, $u$, rating a movie, $i$, is $\mathbb{P}(R_{u_i}=\text{yes})=\frac{...
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1answer
225 views

How to build recommendation system that also takes time as a feature

Let's say a User was Interested in football, so we were recommending him posts about football after few days or weeks he starts watching Baseball. How'd we go about building a recommender system that ...
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1answer
49 views

How to develop Top-N recommendation for evaluating my system

I want to evaluate my recommender system with Top-N recommendation method and I have a problem. In some situation, e.g. N = 5, I don't have 5 items for listing and I cannot do that for evaluating. now,...
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1answer
137 views

User based recommendation factoring in user data [closed]

The question is: what algorithms (and libraries) should i use if i want to build a recommender system with the following data in mind representation: ...
0
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1answer
89 views

Modeling Grocery Store Transactions

I'm fiddling around with some data that represent grocery store transactions. The data are in the following form: Each row represents a final transaction by a customer, with a column for user ID, ...
0
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2answers
148 views

recommender system: how to compare different scores when calculated individually?

I am building a small recommender system which aims at recommending ~10 products to customers. Instead of using a multi-label classification model, I have opted to build a separate scoring model for ...
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2answers
122 views

Reduce data length to train effectively

I have customer buying data with each row specifying an item bought by customer. The problem is that even if at the same time customer buys five items then there are five different rows for it and as ...
1
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1answer
173 views

Does anyone know how google play music's recommendation engine works?

What sort of models do they use? Presumably some flavor of neural net. Do they do a lot of feature engineering? Or do they throw in huge raw matrices of oscilloscope output? Given that it must be ...
0
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1answer
849 views

How to calculate coverage in recommender systems?

I am trying to calculate coverage metrics for a recommender system that I have designed. This blog post talks about how to do it. I had some difficulties in understanding the same. It says that These ...
0
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1answer
138 views

Recommend tags for documents

I'm working on a unusual issue (for me) and I need some advice. My goal is to have a recommendation algorithm that propose tags for a document, based on all the previously tagged documents. For ...
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0answers
77 views

Recommender algorithm

We have some skill levels (beginner, advance, expert) which users assign themselves. Then they get some rating (2, 3, 4, 5) stars from others…. So an expert may have 2-star overall rating and an ...
4
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2answers
289 views

Factorization Machine - prevent over fitting

I was recently asked this question in an interview and wondered what the answer would be - "How do Factorization Machines get around the overfitting problem when using second-order interactions?"
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1answer
713 views

Computing Item-to-Item Similarity Using Cosine

I have a "User x Item" matrix as below: user item1 item2 item3 u1 2 0 3 u2 1 2 0 u3 4 3 1 u4 0 2 2 I want to computer the ...
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1answer
362 views

R Recommender System for very sparse matrices required

I am trying to build a recommender system based on a large and very sparse matrix. Dimensions of that matrix would approximately be 12000 x 37000, possibly even more rows up to 100000. However, this ...
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1answer
1k views

Is there an overview over recommender system architectures?

I want to learn more about the recommender system topic. I am very interested in the usage of different database systems for this use case. My problem is that I cannot find a good overview over ...
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1answer
210 views

Which recommender system approach is good with high sparsity in user?

I'm building a recommendation system, but my data has high sparsity. In most of my data, each user gives one feedback, for one item. For example, I have 10 items and 15 users, I have 3 feedbacks, ...
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0answers
133 views

Tensor Decomposition for Higher-Order Context-Aware Recommender Systems

Let me motivate my problem with an example. Let's assume our observations concern ratings a user give to different items, while navigating through item catalog. The user begins rating item1 (may be ...
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1answer
135 views

Data not consistent [closed]

I have data set of client profile and mutual funds , now the problem is there is huge numbers of different mutual funds available and based on history I can see for certain type of client profile more ...
4
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1answer
178 views

Graph-Document-Recommendations

I want to build a Recommendation System to recommend products to users. This is for research purposes. The context-system the engine will be integrated in is also not build yet. So right now I am ...