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» Learning to rank for information retrieval
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ICMCS
2006
IEEE
139views Multimedia» more  ICMCS 2006»
16 years 11 days ago
A Measure for Evaluating Retrieval Techniques based on Partially Ordered Ground Truth Lists
For the RISM A/II collection of musical incipits (short extracts of scores, taken from the beginning), we have established a ground truth based on the opinions of human experts. I...
Rainer Typke, Remco C. Veltkamp, Frans Wiering
SIGIR
2009
ACM
16 years 25 days ago
Personalized tag recommendation using graph-based ranking on multi-type interrelated objects
Social tagging is becoming increasingly popular in many Web 2.0 applications where users can annotate resources (e.g. Web pages) with arbitrary keywords (i.e. tags). A tag recomme...
Ziyu Guan, Jiajun Bu, Qiaozhu Mei, Chun Chen, Can ...
RECSYS
2009
ACM
16 years 25 days ago
Rating aggregation in collaborative filtering systems
Recommender systems based on user feedback rank items by aggregating users’ ratings in order to select those that are ranked highest. Ratings are usually aggregated using a weig...
Florent Garcin, Boi Faltings, Radu Jurca, Nadine J...
ISMIR
2005
Springer
179views Music» more  ISMIR 2005»
15 years 12 months ago
Discovering and Visualizing Prototypical Artists by Web-Based Co-Occurrence Analysis
Detecting artists that can be considered as prototypes for particular genres or styles of music is an interesting task. In this paper, we present an approach that ranks artists ac...
Markus Schedl, Peter Knees, Gerhard Widmer
ANLP
2000
127views more  ANLP 2000»
15 years 7 months ago
Answer Extraction
Information retrieval systems have typically concentrated on retrieving a set of documents which are relevant to a user's query. This paper describes a system that attempts t...
Steven P. Abney, Michael Collins, Amit Singhal