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Lulu Hypothesis-Based Collaborative Filtering

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£91.46 £86.89 £88.72 £90.55 £92.37 £94.20 £96.03 26 July 2026 06 August 2026 18 August 2026 29 August 2026 10 September 2026
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Description

Recommender systems have emerged to help individuals with finding interesting products. As a result, the consumer welfare enhances due to the increased product variety. In other words, recommender systems are essential for increasing consumers welfare, which ultimately leads to an increase of economic and social welfare. Typically, recommender systems use the collective wisdom of individuals for exposing individuals to products which best fits their preferences. More precisely, the most like-minded individuals are considered by the recommender system to provide individuals recommendations. This is commonly referred to as collaborative filtering. In this dissertation, we present hypothesis-based collaborative filtering (HCF) to expose individuals to products which best fits their preferences. HCF retrieves like-minded individuals based on the similarity of their hypothesized preferences by means of machine learning algorithms hypothesizing individuals’ preferences.

Product Specifications

Brand
Lulu
Format
paperback
Domain
Amazon UK
Release Date
16 April 2012
Listed Since
05 June 2012

Barcode

No barcode data available

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