%0 Conference Proceedings
%T Full Text Search Engine as Scalable k-Nearest Neighbor Recommendation System
%+ Faculty of Informatics and Information Technologies
%A Suchal, Ján
%A Návrat, Pavol
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B Third IFIP TC12 International Conference on Artificial Intelligence (AI) / Held as Part of World Computer Congress (WCC)
%C Brisbane, Australia
%Y Max Bramer
%I Springer
%3 Artificial Intelligence in Theory and Practice III
%V AICT-331
%P 165-173
%8 2010-09-20
%D 2010
%R 10.1007/978-3-642-15286-3_16
%K full text search
%K recommendation systems
%Z Computer Science [cs]/Digital Libraries [cs.DL]Conference papers
%X In this paper we present a method that allows us to use a generic full text engine as a k-nearest neighbor-based recommendation system. Experiments on two real world datasets show that accuracy of recommendations yielded by such system are comparable to existing spreading activation recommendation techniques. Furthermore, our approach maintains linear scalability relative to dataset size. We also analyze scalability and quality properties of our proposed method for different parameters on two open-source full text engines (MySQL and SphinxSearch) used as recommendation engine back ends.
%G English
%2 https://inria.hal.science/hal-01054596/document
%2 https://inria.hal.science/hal-01054596/file/wcc-final.pdf
%L hal-01054596
%U https://inria.hal.science/hal-01054596
%~ IFIP
%~ IFIP-AICT
%~ IFIP-AICT-331
%~ IFIP-TC
%~ IFIP-TC12
%~ IFIP-AI
%~ IFIP-WCC
%~ IFIP-2010