caa a22 4500 463207165 CHVBK 20180405153129.0 cr unu---uuuuu 170326e20070601xx s 000 0 eng 10.1007/s10462-008-9074-5 doi (NATIONALLICENCE)springer-10.1007/s10462-008-9074-5 An axiomatic comparison of learned term-weighting schemes in information retrieval: clarifications and extensions [Elektronische Daten] [Ronan Cummins, Colm O'Riordan] Machine learning approaches to information retrieval are becoming increasingly widespread. In this paper, we present term-weighting functions reported in the literature that were developed by four separate approaches using genetic programming. Recently, a number of axioms (constraints), from which all good term-weighting schemes should be deduced, have been developed and shown to be theoretically and empirically sound. We introduce a new axiom and empirically validate it by modifying the standard BM25 scheme. Furthermore, we analyse the BM25 scheme and the four learned schemes presented to determine if the schemes are consistent with the axioms. We find that one learned term-weighting approach is consistent with more axioms than any of the other schemes. An empirical evaluation of the schemes on various test collections and query lengths shows that the scheme that is consistent with more of the axioms outperforms the other schemes. Springer Science+Business Media B.V., 2008 Information retrieval nationallicence Genetic programming nationallicence Axiomatic constraints nationallicence Cummins Ronan Department of Information Technology, National University of Ireland, Galway, Ireland aut O'Riordan Colm Department of Information Technology, National University of Ireland, Galway, Ireland aut Artificial Intelligence Review Springer Netherlands 28/1(2007-06-01), 51-68 0269-2821 28:1<51 2007 28 10462 https://doi.org/10.1007/s10462-008-9074-5 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10462-008-9074-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Cummins Ronan Department of Information Technology, National University of Ireland, Galway, Ireland aut NATIONALLICENCE 700 1- O'Riordan Colm Department of Information Technology, National University of Ireland, Galway, Ireland aut NATIONALLICENCE 773 0- Artificial Intelligence Review Springer Netherlands 28/1(2007-06-01), 51-68 0269-2821 28:1<51 2007 28 10462 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer