Questions tagged [learning-to-rank]

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Learning to Rank vs Reinforcement Learning in Information Retrieval - which one is preferable and why?

I am trying to create an information retrieval system which can benefit from user feedback (either implicit, through e.g., click-through data) or explicit (e.g., binary feedback on irrelevant ...
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8 views

Visual/intuitive comparisons between various pairwise loss functions for learning-to-rank tasks

In learning-to-rank, There are various pairwise loss functions such as Bayesian Personalised Ranking (BPR) or Weighted Approximate-Rank Pairwise (WARP), etc. I know that these aim at different ...
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12 views

Solving Feature Distribution variance between Training and Prediction for Ranking models

I am building a linear regression model to improve ranking of documents. And trying to identify problems due to which model performance estimates don't match actual impact One major problem is ...
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14 views

Listwise ranking for query with thousands of docs

Typical listwise ranking model will predict a complete permutation of all docs corresponding to a query q. If the number of docs to one query are large, for example,...
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19 views

Listwise learning to rank with negative sample relevance

Typical listwise learning to rank (L2R) algorithm tries to learn the rank of docs $\{x_i\}_{i=1}^m$ corresponding to a query $q$. If we use correlation efficient to label the relevance between docs ...
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13 views

Ranking based on graph neural network

Can anything point to an example for an implementation of a ranking system which is based on a graph neural network?
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1answer
162 views

How to use ndcg metric for binary relevance

I am working on a ranking problem to predict the right single document based on the user query and use the NDCG metric to measure the model. Given the details : Queries ( Q ), Result Document ( D ),...
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1answer
45 views

Multilabel classification for a learning to rank application

I am looking for some suggestions on Learning to Rank method for search engines. I created a dataset with the following data: ...
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60 views

How to perform Learning to Rank for a small dataset

I am very interested in applying Learning to rank to my problem doamin. When I read through the literature of Learning to rank I ...
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88 views

Learning to rank: how is the label calculated?

I am studying learning to rank and not sure I understand how the train sample and final label (relevance score) is constructed. Lets assume we sell furniture online. We have logged customer's query, ...
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2answers
2k views

Why does it not need to set test group when using 'rank:pairwise' in xgboost?

I'm new for learning-to-rank. I'm trying to learn the Learning to rank example provided by xgboost. I found that the core code is as follows in rank.py. ...
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1answer
120 views

What is the difference between nDCG and rank correlation methods?

When do we use one or the other? My use case: I want to evaluate a linear space to see how good retrieval results are. I have a set of data X (m x n) and some weights W (m x 1). I want to measure ...
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247 views

NDCG score is greater than 1

I'm solving a problem of ranking classes for each unique id based on the utilization quantity. I have 6 unique classes in the training and test data. My neural net mode predicts the utilization ...
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1answer
198 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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2answers
143 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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29 views

Search Query Sample Size Determination for validation set

While designing a search system, which searches in N identifiable categories, how many search queries does one need in each category to validate the target metric (DCG) scores accurately (balanced ...
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2answers
697 views

Rank terms in a bag -of-words model

I have a set of documents where I need to extract important keywords in the document and then rank those keywords. The ranking should be done based on relevance and/or other metrics. Are there any ...