Estimating a latent-class user model for travel recommender systems
نویسندگان
چکیده
منابع مشابه
Feature-Weighted User Model for Recommender Systems
Recommender systems are gaining widespread acceptance in e-commerce applications to confront the “information overload” problem. Collaborative Filtering (CF) is a successful recommendation technique, which is based on past ratings of users with similar preferences. In contrast, Content-Based filtering (CB) assumes that each user operates independently. As a result, it exploits only information ...
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Recommender systems are commonly defined as applications that e-commerce sites exploit to suggest products and provide consumers with information to facilitate their decision-making processes.1 They implicitly assume that we can map user needs and constraints, through appropriate recommendation algorithms, and convert them into product selections using knowledge compiled into the intelligent re...
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Conversational recommender systems have been introduced in Travel and Tourism applications in order to support interactive dialogues which assist users in acquiring their goals, e.g., travel planning in a dynamic packaging system. Notwithstanding this increased interactivity, these systems employ an interaction strategy that is specified a priori (at design time) and is followed quite rigidly d...
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Recommender systems are a recent but increasingly widely used resource. Yet most, if not all of them suffer from serious deficiencies. Recommender systems often require first time users to enter ratings for a large number of items — a tedious process that often deters users. Thus, this thesis investigated whether useful recommendations could be made without requiring users to explicitly rate it...
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ژورنال
عنوان ژورنال: Information Technology & Tourism
سال: 2018
ISSN: 1098-3058,1943-4294
DOI: 10.1007/s40558-018-0105-z