Similarity for News Recommender Systems

Nava Tintarev; Judith Masthoff

Similarity for News Recommender Systems

Nava Tintarev, Judith Masthoff

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

Abstract

The accuracy of content-based recommender systems tends to depend on the way similarity is defined. In this paper, we will explore different ways to measure similarity for a news recommender system based on news headlines. We will compare human judgements of similarity with Lin’s taxonomy-based measure and the WASP measure that uses annotated corpus data. The main aim of this work is to better understand similarity, so that it can be used to explain recommendations to users.

Original language	English
Title of host publication	Workshop on Recommender Systems and Intelligent User Interfaces
Subtitle of host publication	2nd international workshop on web personalisation,recommender iystems and intelligent iser interfaces
Editors	Gulden Uchyigit
Publication status	Published - 2006

Bibliographical note

In conjunction with the International Conference on Adaptive Hypermedia and
Adaptive Web-Based Systems, AH 2006, Dublin, Ireland, June 20-23, 2006

Keywords

similarity
recommender systems

Access to Document

http://www.doc.ic.ac.uk/~gu1/WPRSIUI/WPRSIUI06.html

Cite this

Similarity for News Recommender Systems. / Tintarev, Nava; Masthoff, Judith.
Workshop on Recommender Systems and Intelligent User Interfaces: 2nd international workshop on web personalisation,recommender iystems and intelligent iser interfaces. ed. / Gulden Uchyigit. 2006.

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

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title = "Similarity for News Recommender Systems",

abstract = "The accuracy of content-based recommender systems tends to depend on the way similarity is defined. In this paper, we will explore different ways to measure similarity for a news recommender system based on news headlines. We will compare human judgements of similarity with Lin{\textquoteright}s taxonomy-based measure and the WASP measure that uses annotated corpus data. The main aim of this work is to better understand similarity, so that it can be used to explain recommendations to users.",

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PY - 2006

Y1 - 2006

N2 - The accuracy of content-based recommender systems tends to depend on the way similarity is defined. In this paper, we will explore different ways to measure similarity for a news recommender system based on news headlines. We will compare human judgements of similarity with Lin’s taxonomy-based measure and the WASP measure that uses annotated corpus data. The main aim of this work is to better understand similarity, so that it can be used to explain recommendations to users.

AB - The accuracy of content-based recommender systems tends to depend on the way similarity is defined. In this paper, we will explore different ways to measure similarity for a news recommender system based on news headlines. We will compare human judgements of similarity with Lin’s taxonomy-based measure and the WASP measure that uses annotated corpus data. The main aim of this work is to better understand similarity, so that it can be used to explain recommendations to users.

KW - similarity

KW - recommender systems

M3 - Published conference contribution

BT - Workshop on Recommender Systems and Intelligent User Interfaces

A2 - Uchyigit, Gulden

ER -

Similarity for News Recommender Systems

Abstract

Bibliographical note

Keywords

Access to Document

Fingerprint

Cite this