NDLI: Learning to rank for information retrieval using layered multi-population genetic programming

Content Provider	IEEE Xplore Digital Library
Author	Jung Yi Lin Jen-Yuan Yeh Chao Chung Liu
Copyright Year	2012
Description	Author affiliation: Information Department, National Museum of Natural Science, Taichung 404, TAIWAN (Jen-Yuan Yeh) \|\| Dept. of Computer Science and Information Engineering, Ching-Yun University, Jhongli 320, TAIWAN (Jung Yi Lin; Chao Chung Liu)
Abstract	To determine which documents are relevant and which are not to the user query is one central problem broadly studied in the field of information retrieval (IR). Learning to rank for information retrieval (LR4IR), which leverages supervised learning-based methods to address the problem, aims to produce a ranking model automatically for defining a proper sequential order of related documents according to the given query. The ranking model is employed to determine the relationship degree between one document and the user query, based on which a ranking of query-related documents could be produced. In this paper we proposed an improved RankGP algorithm using multi-layered multi-population genetic programming to obtain a ranking function, trained from collections of IR results with relevance judgments. In essence, the generated ranking function is consisted of a set of IR evidences (or features) and particular predefined GP operators. The proposed method is capable of generating complex functions through evolving small populations. LETOR 4.0 was used to evaluate the effectiveness of the proposed method and the results showed that the method is competitive with RankSVM and AdaRank.
Starting Page	45
Ending Page	49
File Size	3345408
Page Count	5
File Format	PDF
ISBN	9781467308915
e-ISBN	9781467308922
DOI	10.1109/CyberneticsCom.2012.6381614
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-12
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Sociology Genetic programming Machine learning Evolutionary computation Information retrieval Feature extraction Vectors Ranking function Learning to rank for Information Retrieval Statistics
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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