Options
On the Evaluation of Data Fusion for Information Retrieval
Author(s)
Date Issued
2020-12-20
Date Available
2024-05-02T15:34:09Z
Abstract
Data Fusion combines document rankings from multiple systems into one, in order to improve retrieval effectiveness. Many approaches to this task have been proposed in the literature, and these have been evaluated in various ways. This paper examines a number of such evaluations, to extract commonalities between approaches. Some drawbacks of the prevailing evaluation strategies are then identified, and suggestions made for more appropriate evaluation of data fusion.
Type of Material
Conference Publication
Publisher
ACM
Copyright (Published Version)
2020 the Authors
Web versions
Language
English
Status of Item
Peer reviewed
Journal
FIRE 2020: Forum for Information Retrieval Evaluation
Conference Details
The 12th meeting of Forum for Information Retrieval Evaluation (FIRE 2020), Hyderabad, India, 16-20 December 2020
ISBN
978-1-4503-8978-5
This item is made available under a Creative Commons License
File(s)
Loading...
Name
Lillis2020(5).pdf
Size
516.72 KB
Format
Adobe PDF
Checksum (MD5)
947c399d1115a9d2e2911fa65c095c6d
Owning collection