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Questions tagged [recommender-system]

The tag has no usage guidance, but it has a tag wiki.

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Can a recommendation system be built without any user ratings?

I was planning to make an artwork recommendation system as a project by using the WikiArt open source dataset available on kaggle, I'm still looking for datasets which might already have user ratings ...
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How do I perform Leave One Out Cross Validation For Top n Recommendation Sytems?

I am new in making recommendation systems . I am using the surpriselib library to evaluate my recommendations. All the Accuracy Metrics are well supported in this library. But I also want to compute ...
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1answer
29 views

recommender systems : how to deal with items that change over time?

Let's say I am building a recommender system where items change through time. We suppose that each transaction is composed of : an item $i$ in list of items $(i_1, i_2, i_3, .., i_m)$. a user $u$ in ...
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What are some limitations of using Collaborative Deep learning for Recommender systems?

Recently I worked on a paper by Hao Wang- Collaborative Deep learning for Recommender Systems which uses a two way tightly coupled method, Collaborative filtering for Item correlation and Stacked ...
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How can I build a recommender system that accepts data of varying granularity?

I'm tasked with building a recommender system that can make recommendations based on input data of varying levels of granularity. To explain what I mean, let's use a running example of a Movie Title ...
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34 views

cosine similarity between items (purchase data) and normalisation

I'm using IndexedRowMatrix which represents the products's user purchase behaviours and in order to build product recommendations, I use cosine similarity to calculate similarities between products. ...
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10 views

Poor performance of Collaborative Filtering using Matrix Factorization

I am trying to train a collaborative filtering model using embeddings (or matrix factorization) as described here on the movielens dataset. Here is the Keras implementation: ...
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15 views

Recommendation system for implicit rating

I have a dataset that gives an information about user, item and number of time the user has bought the items(counts). i.e. I have 3 columns : user, item and counts. I want to make a recommendor that ...
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How do I store/model data needed for my recommendation module?

I'm reading data from a store's product catalog, a 100mb xml file which contains product-wise attributes like prices, categories, etc. Given a product_id, my job ...
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1answer
39 views

Does a matrix factorization recommendation engine use user/item related features?

All the tutorials I can find about matrix factorization recommendation systems start with importing users, items, and user-item-ratings, but then only use the rating matrix to train the recommender (...
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18 views

User-Item recommendation system

I have a set of users, U and a set of items, I. For each item, I have its embedding, a numerical vector projecting it a dense space. Also, I have for each user, several(say k) |I| sized vectors, each ...
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1answer
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Evaluating recommendations quality and accuracy

I'm developing a recommendation system, that should provide my clients what actions they should take in order to hit certain targets. The underlying mechanics of the process is physical - where both ...
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1answer
29 views

Recommender system for next carrer step

I want to build a recommender system that suggests the next step in your career. About the dataset. About 50'000 Users with following informations: Skills (tags, string value) every job they did (...
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1answer
44 views

Neural network model for sparse multi-class classifier on Tensorflow

The problem I'm trying to solve is the following: the data is Movielens with N_users=6041 and N_movies=3953, ~1 million ratings. For each user, a vector of size N_movies is defined, and the values ...
1
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1answer
29 views

Recommender system that connect users with each other , should I go for content based or collaborative filtering?

I am trying to build a system where user come on the platform and he chooses a topic(predefined few topics) and then we connect him with any random online user who chooses the same topic. Then they ...
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24 views

Matrix of purchases for recommender system

I am trying to build a Top-N recommender system for unauthorized users. I have data about previous orders of authorized clients. I have calculated the item-item similarity matrix (based on cosine ...
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1answer
19 views

Building Recommender for book paragraphs

I have some application which are offering a book to read. Users normally read some paragraphs of it only (it contains +6000 paragraphs). Looking at scatter for ...
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1answer
22 views

Data model and algorithm for recommending “related” interests

On my app, when a user selects an interest (example: ios), I'd like to show related interests (swift, xcode, apple, etc). I have a list of around 700 interests/tags (about 300 of them can be ...
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1answer
17 views

Collaborative filtering with human-adjusted latent factors

Having tried some of movie recommendation engines available on the web I have the feeling they are not satisfactory. I just fail to get movies similar to those I like based on traits interested for me ...
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1answer
37 views

How to create user and item profile in an item to item collaborative filtering? (Non-rating case)

I want to build a recommender system for a coupons website which should do the following: Given the past purchase behaviour of a user, recommend coupons which the user is likely to buy. The data does ...
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0answers
35 views

SVD++ vs wALS: Which is the more effective for implicit feedback in Recommendation system

As SVD++ can be used for implicit feedback, I would like to know whether SVD++ can gives better results than the wALS algorithm (paper: Collaborative Filtering for Implicit Feedback Datasets ). I can'...
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Recommending top answerers for a Question on Quora/Stackexchange sites

I want to make a tool that will tell me who can potentially answer a question on Quora or StackExchange. The tool will take input the text of a question, and output a sorted list of users who can ...
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2answers
51 views

Which recommender system: Content based or Collaborative filtering?

I want to build a recommender system for a coupons website which should do the following: Given the past purchase behaviour of a user, recommend coupons which the user is likely to buy. The data does ...
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0answers
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Can I sum up feature vectors of a user‘s collection?

I want to find items that are similar to items users already have in their collection. Every item has attributes, so I created feature vectors where every element of the vector represents an attribute ...
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0answers
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How to choose negative examples for recommendation system?

I am building a search recommendation system for e-commerce which generates most relevant results given an input query. I have framed it as a classification problem (learning to rank) and using ...
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1answer
52 views

What model can I build with a limited dataset?

I have a dataset consisting of purchasing history from an e-commerce website. The columns consist of customer id, product id, <...
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1answer
29 views

Problem in Recommendation for categorical data?

I have been building a recommendation model to recommend certain questions in an interaction platform to users to help each other. I have calculated an affinity score between categories to find which ...
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1answer
29 views

How to recommend items after finding similar users in recommendation system

As the title explains my problem, I'm done with creating a recommendation system that can give me similar users for any given new user. The problem I face is, If I extract the list of products that ...
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2answers
103 views

Taking Neural Network's false positives as the recommendation system result?

I am creating a recommendation system and considering two parallel ways of formalizing the problem. One classical, using proximity (recommend the product to the customer if a majority vote of 2k+1 ...
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1answer
27 views

Two definitions of DCG measure

I wanted to check the definition of Discounted Cumulative Gain (DCG) measure in the original paper Jarvelin and it seems it differs from the one given in the later literature Wang. Originally, for $n$ ...
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7 views

Handling Error for Continuous Features in a Content-Based Filtering Recommender System

I've got a content-based recommender that works... fine. I was fairly certain it was the right approach to take for this problem (matching established "users" with "items" that are virtually always ...
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1answer
55 views

Skills based recommendation system

Assuming that I have a list of Users with a list of skills: (each value is a different skill) And a list of Tasks with a list of demanded skills: Based on a manual classification that returned: (...
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0answers
39 views

Streaming Recommender System using Spark

I have trained a recommender model using ALS from spark.mlib. Now I want to consider the incoming ratings to my model. My data is in form of spark's DataFrame. The idea is to use spark streaming, so I ...
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0answers
12 views

Examples of time scale aware recommender engine?

I was wondering if anyone has heard of any research into time scale-aware recommender engines? What I mean by that is a recommender engine that "knows" that different items are bought on different ...
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1answer
23 views

How to implement a basic query management and recommendation system

I'm trying to prototype a system where given a textual query (e.g. a question), I get a list of most relevant documents/questions among a pool of available documents/questions (similar to what we see ...
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13 views

Which curve comparison should I use to evaluate the performance of a recommender?

I am building a recommender system on the Last.FM dataset (link here) (1,892 users and 17,632 artists and the number of times a particular artist was listened to by a user). Next, the raw dataset was ...
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1answer
69 views

How to factorize the Matrix in TensorFlow? (Recommender System)

Given a user ratings matrix which is $n \times p$, where $n$ users rate $p$ movies, I already have a row matrix $n \times 10$ which characterises the user. I ideally wanted to use the TF was method ...
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1answer
110 views

How can we define missing rating in recommender system?

I was reading about collaborative filtering where we need to pass (user, item and rating) in case of matrix factorisation (SVD). Now, my question is given data of ...
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2answers
63 views

Learning to Rank Application

If there's a website/app that sells products and my job is to determine the order/ranking in which the products should be displayed. For example : I click on restaurants and a list of restaurants ...
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0answers
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Recommendation: Similar Users

I am working on a project that needs me to identify similar users based on their reviews (domain can be food, fashion etc.) and form groups. This would allow me to suggest a prospective user to look ...
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11 views

Any paper dealing with temporally related items suggestions for recommender systems?

I have trouble finding papers that deal with such a problem of temporally related items. An example is worth a thousand words: I just bought an HDMI cable on Amazon. It would be weird to ...
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1answer
31 views

Is is possible to build a recommender system with this dataset? [closed]

I have an extremely sparse user items ratings matrix with 0.018 % non NA values. Correct me if I am wrong but I think we need a lot of products compared to number of users to build a recommender ...
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1answer
43 views

Predict ratings for Item Based Collaborative Filtering

Given the (cosine) similarity score of top 100 neighbors of every item, how do I predict ratings for unrated items? Please explain in simple terms. Item 1 260 0.577305 780 0.5655413 1210 0....
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66 views

Advantages of Binary Rating System for Collaborative Filtering Recommender Systems

I notice that Netflix, which I think used to use a five-star scale for rating content and give predicted ratings for unrated content on the same scale, now just has basic like/dislike buttons. Music ...
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1answer
48 views

How can I minimize features of the trainded model?

I have real technological process, that explained with complex model (xgboost). I.e. current mass of a product (y) depends on current temperature (x1), pressure (x2) and so on. I would like to solve ...
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64 views

Clustering of devices in locations?

My question is about using some sort of AI to assess if devices are located in any of a list of venues. I'd ask of machine learning, but so far we're doing this with an expert system, and we are ...
2
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1answer
52 views

How can I estimate user-item purchase probabilities of a e-commerce website?

I am writing my Master thesis, where the goal is to estimate user-item purchase probabilities. In other words, for a given user, what is the probability he/she will buy a certain item. I have session ...
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0answers
22 views

How to measure model improvement for Recommender Systems in real applications?

In the academia, model 'goodness' for recommendation systems are typically in terms of a loss or metric (i.e. MSE loss, Mean Average Precision). In real world applications, companies would deploy A/B ...
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How do we create the graph structure required for unimodal bandits

Some of the papers describing Unimodal bandits are [1], [2] and [3]. The common factor in all these algorithms is that they require a graph as input whose nodes are arms (actions) and an edge exists ...
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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 ...