Identifying and Analyzing User Model Information from Collaborative Filtering Datasets

Josephine Griffith

Identifying and Analyzing User Model Information from Collaborative Filtering Datasets

Research output: Chapter in Book or Conference Publication/Proceeding › Conference Publication › peer-review

Abstract

This paper considers the information that can be captured about users from a collaborative filtering dataset. The aims of the paper are to create a user model and to use this model to explain the performance of a collaborative filtering approach. A number of user features are defined and the performance of a collaborative filtering system in producing recommendations for users with different feature values is tested. Graph-based representations of the collaborative filtering space are presented and these are used to define some of the user features as well as being used in a recommendation task.

Original language	English (Ireland)
Title of host publication	PERSONALIZATION TECHNIQUES AND RECOMMENDER SYSTEMS
Publisher	WORLD SCIENTIFIC PUBL CO PTE LTD
Publication status	Published - 1 Jan 2008

Authors (Note for portal: view the doc link for the full list of authors)

Authors
Griffith, J;O'Riordan, C;Sorensen, H

Cite this

@inproceedings{30be93f13b114e39a28357ae53c0aded,

title = "Identifying and Analyzing User Model Information from Collaborative Filtering Datasets",

abstract = "This paper considers the information that can be captured about users from a collaborative filtering dataset. The aims of the paper are to create a user model and to use this model to explain the performance of a collaborative filtering approach. A number of user features are defined and the performance of a collaborative filtering system in producing recommendations for users with different feature values is tested. Graph-based representations of the collaborative filtering space are presented and these are used to define some of the user features as well as being used in a recommendation task.",

author = "Josephine Griffith",

year = "2008",

month = jan,

day = "1",

language = "English (Ireland)",

booktitle = "PERSONALIZATION TECHNIQUES AND RECOMMENDER SYSTEMS",

publisher = "WORLD SCIENTIFIC PUBL CO PTE LTD",

}

TY - GEN

T1 - Identifying and Analyzing User Model Information from Collaborative Filtering Datasets

AU - Griffith, Josephine

PY - 2008/1/1

Y1 - 2008/1/1

N2 - This paper considers the information that can be captured about users from a collaborative filtering dataset. The aims of the paper are to create a user model and to use this model to explain the performance of a collaborative filtering approach. A number of user features are defined and the performance of a collaborative filtering system in producing recommendations for users with different feature values is tested. Graph-based representations of the collaborative filtering space are presented and these are used to define some of the user features as well as being used in a recommendation task.

AB - This paper considers the information that can be captured about users from a collaborative filtering dataset. The aims of the paper are to create a user model and to use this model to explain the performance of a collaborative filtering approach. A number of user features are defined and the performance of a collaborative filtering system in producing recommendations for users with different feature values is tested. Graph-based representations of the collaborative filtering space are presented and these are used to define some of the user features as well as being used in a recommendation task.

M3 - Conference Publication

BT - PERSONALIZATION TECHNIQUES AND RECOMMENDER SYSTEMS

PB - WORLD SCIENTIFIC PUBL CO PTE LTD

ER -

Identifying and Analyzing User Model Information from Collaborative Filtering Datasets

Abstract

Authors (Note for portal: view the doc link for the full list of authors)

Fingerprint

Cite this