dc.contributor.author | de Souza da Silva, Eliezer | |
dc.contributor.author | Ahlers, Dirk | |
dc.date.accessioned | 2018-04-30T08:58:10Z | |
dc.date.available | 2018-04-30T08:58:10Z | |
dc.date.created | 2017-12-30T20:26:14Z | |
dc.date.issued | 2017 | |
dc.identifier.isbn | 978-1-4503-5338-0 | |
dc.identifier.uri | http://hdl.handle.net/11250/2496482 | |
dc.description.abstract | New retrieval models promise deeper integration of multiple features and sources of information. The inclusion of thematic and location features in a joint factorization model allows location to be modeled as a first-class feature and can improve a range of tasks in geographic information retrieval and recommendation. In this position paper, we describe these factorization models and how they can be useful for corpus and user need understanding and further GIR use cases. We argue that using joint factorization models can be a powerful tool in the integration of complex features and relationships present in many GIR data sources and applications. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Association for Computing Machinery (ACM) | nb_NO |
dc.relation.ispartof | GIR'17 Proceedings of the 11th Workshop on Geographic Information Retrieval | |
dc.title | Poisson Factorization Models for Spatiotemporal Retrieval | nb_NO |
dc.type | Chapter | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.identifier.doi | 10.1145/3155902.3155912 | |
dc.identifier.cristin | 1533096 | |
dc.description.localcode | © 2017 Copyright held by the owner/author(s). Publication rights licensed to Association for Computing Machinery. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive version was published here: https://doi.org/10.1145/3155902.3155912 | nb_NO |
cristin.unitcode | 194,63,10,0 | |
cristin.unitname | Institutt for datateknologi og informatikk | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |