An evolutionary strategy with machine learning for learning to rank in information retrieval

QR Code

An evolutionary strategy with machine learning for learning to rank in information retrieval

Learning to Rank (LTR) is one of the problems in Information Retrieval (IR) that nowadays attracts attention from researchers. The LTR problem refers to ranking the retrieved documents for users in search engines, question answering and product recommendation systems. There is a number of LTR approa...

Full description

Bibliographic Details
Main Authors:	Ibrahim, Osman Ali Sadek, Landa-Silva, Dario
Format:	Article
Published:	Springer 2018
Subjects:	Learning to rank ; Evolution strategy ; Linear regression ; Support vector machine
Online Access:	https://eprints.nottingham.ac.uk/48943/

Similar Items

ES-Rank: evolution strategy learning to rank approach
by: Ibrahim, Osman Ali Sadek, et al.
Published: (2017)

Evolutionary algorithms and machine learning techniques for information retrieval
by: Ibrahim, Osman Ali Sadek
Published: (2017)

Determining the number of training points required for machine learning of potential energy surfaces.
by: Pearson, Matt
Published: (2021)

Real-time unsupervised incremental support vector machine for oil and gas pipeline NDT system
by: Nik Zulkepeli, Nik Ahmad Akram
Published: (2016)

Improving machine vision crack die detection with multi-kernel learning SVM
by: Abdullah, Mohd Khairi John
Published: (2024)

Improveing Agent-based modelling by using machine learning
by: Shen, Xin
Published: (2022)

Application of machine learning for fuel consumption modelling of trucks
by: Perrotta, Federico, et al.
Published: (2017)

A support vector-based interval type-2 fuzzy system
by: Uslan, V., et al.
Published: (2014)

Using machine learning technique to classify geographic areas with socioeconomic potential for broadband investment in Malaysia
by: Tan, Taik Guan
Published: (2022)

Massively-parallel and concurrent SVM architectures
by: Phear, P. B. A.
Published: (2018)

(1+1)-evolutionary gradient strategy to evolve global term weights in information retrieval
by: Ibrahim, Osman Ali Sadek, et al.
Published: (2016)

A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
by: Mohd Pozi, Muhammad Syafiq
Published: (2016)

Enhanced extreme learning machine for general regression and classification tasks
by: Mahmood, Saif F
Published: (2020)

Mathematical Information Retrieval (MIR) from scanned PDF and MathML conversion
by: Nazemi, Azadeh, et al.
Published: (2014)

Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data
by: Sleabi, Waleed Dhhan
Published: (2016)

Machine learning techniques (support vector machine and artificial neural network) for fundamental and technical analysis: a study on SET and PSEI
by: Chin, Jern Tat
Published: (2021)

Cumulative attributes for pain intensity estimation
by: Joy, Egede, et al.
Published: (2017)

Improving specific class mapping from remotely sensed data by cost-sensitive learning
by: Silva, Joel, et al.
Published: (2017)

Local Linear Spatial Regression
by: Hallin, M., et al.
Published: (2004)

The THES university rankings: are they really world class? / Richard Holmes
by: Holmes, Richard
Published: (2006)

Reduction of power consumption in sensor network applications using machine learning techniques
by: Shafiullah, G., et al.
Published: (2008)

Machine learning and natural language processing to identify falls in electronic patient care records from ambulance attendances
by: Tohira, Hideo, et al.
Published: (2021)

Relevance vector machine and multivariate adaptive regression spline for modelling ultimate capacity of pile foundation
by: Samui, P., et al.
Published: (2014)

Towards uncertainty-aware and label-efficient machine learning of human expressive behaviour
by: Tellamekala, Mani Kumar
Published: (2022)

Evaluation of Three Feature Dimension Reduction Techniques for Machine Learning-Based Crop Yield Prediction Models
by: Pham, Hoa Thi, et al.
Published: (2022)

Incorporating learning how to learn in a Malaysian Lower secondary smart classroom
by: Lau, Bee Yian
Published: (2004)

Link-based spam algorithms in adversarial information retrieval
by: Leng, A., et al.
Published: (2012)

Support vector regression with chaos-based firefly algorithm for stock market price forecasting
by: Kazem, A., et al.
Published: (2012)

The THE-QS world university rankings, 2004 – 2009 / Richard Holmes.
by: Richard, Holmes
Published: (2010)

Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
by: Ali Al-Assadi, Hayder M. A.
Published: (2004)

Improved feature extraction and lexicon reduction methods classified by support vector machine for Farsi handwritten word recognition system
by: Akbarpour, Shahin
Published: (2011)

BioHEL: Bioinformatics-oriented Hierarchical Evolutionary Learning
by: Bacardit, Jaume, et al.
Published: (2006)

Exploring the Morphologies of High-Redshift Galaxies with Deep Learning
by: Tohill, Clár-Bríd
Published: (2024)

Factors influencing the accuracy of remote sensing classifications: a comparative study
by: Pal, Mahesh
Published: (2002)

An uneven playing field: rankings and ratings for economics in ERA 2010
by: Bloch, Harry
Published: (2012)

Football match prediction through the use of statistical analysis and machine learning
by: Duyile, Akintunde
Published: (2017)

The development of a multiple linear regression model for aiding formulation development of solid dispersions
by: Fridgeirsdottir, Gudrun A.
Published: (2018)

SOF: a semi-supervised ontology - learning - based focused crawler
by: Dong, Hai, et al.
Published: (2013)

Of teaching quality and rankings
Published: (2011)

The case against rankings
Published: (2011)