article

Generating semantically enriched user profiles for Web personalization

Authors:

Sarabjot Singh Anand,

Patricia Kearney,

Mary ShapcottAuthors Info & Claims

ACM Transactions on Internet Technology (TOIT), Volume 7, Issue 4

Pages 22 - es

https://doi.org/10.1145/1278366.1278371

Published: 01 October 2007 Publication History

Abstract

Traditional collaborative filtering generates recommendations for the active user based solely on ratings of items by other users. However, most businesses today have item ontologies that provide a useful source of content descriptors that can be used to enhance the quality of recommendations generated. In this article, we present a novel approach to integrating user rating vectors with an item ontology to generate recommendations. The approach is novel in measuring similarity between users in that it first derives factors, referred to as impacts, driving the observed user behavior and then uses these factors within the similarity computation. In doing so, a more comprehensive user model is learned that is sensitive to the context of the user visit.

An evaluation of our recommendation algorithm was carried out using data from an online retailer of movies with over 94,000 movies, 44,000 actors, and 10,000 directors within the item knowledge base. The evaluation showed a statistically significant improvement in the prediction accuracy over traditional collaborative filtering. Additionally, the algorithm was shown to generate recommendations for visitors that belong to sparse sections of the user space, areas where traditional collaborative filtering would generally fail to generate accurate recommendations.

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Cited By

Cuzzocrea AFadda E(2024)Modeling and supporting adaptive Complex Data-Intensive Web Systems via XML and the O-O paradigm: The OO-XAHM modelArray10.1016/j.array.2024.10036323(100363)Online publication date: Sep-2024
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Bahrani PMinaei-Bidgoli BParvin HMirzarezaee MKeshavarz A(2024)A hybrid semantic recommender system based on an improved clusteringThe Journal of Supercomputing10.1007/s11227-024-05950-z80:9(13341-13385)Online publication date: 1-Jun-2024
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Bahrani PMinaei Bidgoli BParvin HMirzarzaei MKeshavarz A(2023)A Content-Collaborative Recommender System based on clustering and ontologySignal and Data Processing10.61186/jsdp.20.3.19720:3(197-224)Online publication date: 1-Dec-2023
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Index Terms

Generating semantically enriched user profiles for Web personalization
1. Computing methodologies
  1. Machine learning
    1. Learning settings
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction

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cover image ACM Transactions on Internet Technology

ACM Transactions on Internet Technology Volume 7, Issue 4

October 2007

153 pages

ISSN:1533-5399

EISSN:1557-6051

DOI:10.1145/1278366

Issue’s Table of Contents

Copyright © 2007 ACM.

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Publication History

Published: 01 October 2007

Published in TOIT Volume 7, Issue 4

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