A Collaborative Ranking Model with Multiple Location-based Similarities for Venue Suggestion-Reference-Cited by-同舟云学术

A Collaborative Ranking Model with Multiple Location-based Similarities for Venue Suggestion

Published:2018-09-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 ACM SIGIR International Conference on Theory of Information Retrieval
language:
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Author:

Aliannejadi Mohammad¹,Rafailidis Dimitrios²,Crestani Fabio¹

Affiliation:

1. Università della Svizzera italiana (USI), Lugano, Switzerland

2. University of Mons, Mons, Belgium

Funder

Swiss National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3234944.3234945

Reference41 articles.

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3. Mohammad Aliannejadi Seyed Ali Bahrainian Anastasia Giachanou and Fabio Crestani . 2015. University of Lugano at TREC 2015: Contextual Suggestion and Temporal Summarization Tracks. In TREC. NIST. Mohammad Aliannejadi Seyed Ali Bahrainian Anastasia Giachanou and Fabio Crestani . 2015. University of Lugano at TREC 2015: Contextual Suggestion and Temporal Summarization Tracks. In TREC. NIST.

4. Mohammad Aliannejadi and Fabio Crestani . 2017. Venue Appropriateness Prediction for Personalized Context-Aware Venue Suggestion SIGIR. ACM 1177--1180. 10.1145/3077136.3080754 Mohammad Aliannejadi and Fabio Crestani . 2017. Venue Appropriateness Prediction for Personalized Context-Aware Venue Suggestion SIGIR. ACM 1177--1180. 10.1145/3077136.3080754

5. Mohammad Aliannejadi and Fabio Crestani . 2018 a. Personalized Context-Aware Point of Interest Recommendation. (2018). showeprint{arxiv}abs/1806.05736 Mohammad Aliannejadi and Fabio Crestani . 2018 a. Personalized Context-Aware Point of Interest Recommendation. (2018). showeprint{arxiv}abs/1806.05736

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