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A language modeling approach for the recommendation of tourism-related services

Published: 03 April 2017 Publication History

Abstract

In a ubiquitous scenario, people are typically confronted with context evolution and changing influences. This may create new needs and may condition the user perception of what is relevant information. Over the years, different approaches have been proposed to design personalized Recommender Systems (RS), but state-of-the-art approaches mostly assume a fixed representation of a user profile; the dynamicity of the user's interests (and the way of expressing them) while interacting with the environment is not considered. Aim of this work is to predict a user's preferences in the tourism domain, to provide personalized and context-aware recommendations. Therefore, we define a user profile model which expresses in a formal way the user's opinions with respect to a particular entity. In particular, the proposed approach formally models the user generated content (UGC) connected to a group of reviews (written by expert users) for each entity, and compares it with a (positive and negative) statistical language model representing the target user profile associated with that entity. The effectiveness of the approach is illustrated on a real-case scenario.

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Cited By

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  • (2024)Experience Economy Perspective on Recreational Fishing Tourism Travelers’ Reviews: A Data Science ApproachTourism and Hospitality10.3390/tourhosp50200235:2(354-380)Online publication date: 28-Apr-2024
  • (2020)A context‐aware recommender method based on text and opinion miningExpert Systems10.1111/exsy.1261837:6Online publication date: 10-Aug-2020
  • (2019)Using Opinion Mining in Context-Aware Recommender Systems: A Systematic ReviewInformation10.3390/info1002004210:2(42)Online publication date: 28-Jan-2019
  • Show More Cited By

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  1. A language modeling approach for the recommendation of tourism-related services

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    cover image ACM Conferences
    SAC '17: Proceedings of the Symposium on Applied Computing
    April 2017
    2004 pages
    ISBN:9781450344869
    DOI:10.1145/3019612
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 03 April 2017

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    Author Tags

    1. content-based filtering
    2. information filtering
    3. language models
    4. tourism service recommendation
    5. user profiling

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    • Research-article

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    • TUNAV
    • European Union

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    SAC 2017
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    SAC 2017: Symposium on Applied Computing
    April 3 - 7, 2017
    Marrakech, Morocco

    Acceptance Rates

    Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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    SAC '25
    The 40th ACM/SIGAPP Symposium on Applied Computing
    March 31 - April 4, 2025
    Catania , Italy

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    Cited By

    View all
    • (2024)Experience Economy Perspective on Recreational Fishing Tourism Travelers’ Reviews: A Data Science ApproachTourism and Hospitality10.3390/tourhosp50200235:2(354-380)Online publication date: 28-Apr-2024
    • (2020)A context‐aware recommender method based on text and opinion miningExpert Systems10.1111/exsy.1261837:6Online publication date: 10-Aug-2020
    • (2019)Using Opinion Mining in Context-Aware Recommender Systems: A Systematic ReviewInformation10.3390/info1002004210:2(42)Online publication date: 28-Jan-2019
    • (2019)Tourism Recommendation System Based on User Reviews2019 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)10.1109/3ICT.2019.8910312(1-5)Online publication date: Sep-2019
    • (2019)LOOKERPersonal and Ubiquitous Computing10.1007/s00779-018-01194-w23:2(181-197)Online publication date: 4-Aug-2019
    • (2017)A language modelling approach for discovering novel labour market occupations from the webProceedings of the International Conference on Web Intelligence10.1145/3106426.3109035(1026-1034)Online publication date: 23-Aug-2017

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