Explicit loss minimization in quantification applications (preliminary draft)

Andrea Esuli, Fabrizio Sebastiani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In recent years there has been a growing interest in quantification, a variant of classification in which the final goal is not accurately classifying each unlabelled document but accurately estimating the prevalence (or "relative frequency") of each class c in the unlabelled set. Quantification has several applications in information retrieval, data mining, machine learning, and natural language processing, and is a dominant concern in fields such as market research, epidemiology, and the social sciences. This paper describes recent research in addressing quantification via explicit loss minimization, discussing works that have adopted this approach and some open questions that they raise.

Original languageEnglish
Title of host publicationCEUR Workshop Proceedings
PublisherCEUR-WS
Pages1-11
Number of pages11
Volume1314
Publication statusPublished - 2014
Event8th International Workshop on Information Filtering and Retrieval, DART 2014, Co-located with XIII AI*IA Symposium on Artificial Intelligence, AI*IA 2014 - Pisa, Italy
Duration: 10 Dec 2014 → …

Other

Other8th International Workshop on Information Filtering and Retrieval, DART 2014, Co-located with XIII AI*IA Symposium on Artificial Intelligence, AI*IA 2014
CountryItaly
CityPisa
Period10/12/14 → …

Fingerprint

Epidemiology
Social sciences
Information retrieval
Data mining
Learning systems
Processing

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Esuli, A., & Sebastiani, F. (2014). Explicit loss minimization in quantification applications (preliminary draft). In CEUR Workshop Proceedings (Vol. 1314, pp. 1-11). CEUR-WS.

Explicit loss minimization in quantification applications (preliminary draft). / Esuli, Andrea; Sebastiani, Fabrizio.

CEUR Workshop Proceedings. Vol. 1314 CEUR-WS, 2014. p. 1-11.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Esuli, A & Sebastiani, F 2014, Explicit loss minimization in quantification applications (preliminary draft). in CEUR Workshop Proceedings. vol. 1314, CEUR-WS, pp. 1-11, 8th International Workshop on Information Filtering and Retrieval, DART 2014, Co-located with XIII AI*IA Symposium on Artificial Intelligence, AI*IA 2014, Pisa, Italy, 10/12/14.
Esuli A, Sebastiani F. Explicit loss minimization in quantification applications (preliminary draft). In CEUR Workshop Proceedings. Vol. 1314. CEUR-WS. 2014. p. 1-11
Esuli, Andrea ; Sebastiani, Fabrizio. / Explicit loss minimization in quantification applications (preliminary draft). CEUR Workshop Proceedings. Vol. 1314 CEUR-WS, 2014. pp. 1-11
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