Developing Tourism Users’ Profiles with Data-Driven Explicit Information

نویسندگان

چکیده

In recommender systems (RSs), explicit information is often preferred over implicit because it much more accurate than or predicted information; for example, the user can enter about his interests directly into system, and system will generate recommendations him. Receiving information, however, may be difficult a system. Explicit demographic might uncomfortable some users, extremely common questions, such as race, gender, income, age, lead to bias unfair recommendations. As result, in this study, we propose method, which collected from new does not contain enquired data driven. Users’ interest tourism activities used identify seven categories of tourism. The mapping between extracted established with multilabel classification (MLC) algorithm. user’s 18 by rating only categories. Common MLC algorithms different classifiers were evaluate proposed method. best result relates binary relevance Naïve Bayes classifier, also outperforms entitled collaborative filtering (CF) baseline models. method capture users’ develop their profiles without receiving information. Also, compared CF, addition slight advantage metrics, requires ratings predict activities. contrast, CF require at least 15 ng records unknown (3-4 activities) achieve performance close

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Data-driven Inverse Optimization with Incomplete Information

In data-driven inverse optimization an observer aims to learn the preferences of an agent who solves a parametric optimization problem depending on an exogenous signal. Thus, the observer seeks the agent’s objective function that best explains a historical sequence of signals and corresponding optimal actions. We formalize this inverse optimization problem as a distributionally robust program m...

متن کامل

Data-driven inverse optimization with imperfect information

In data-driven inverse optimization an observer aims to learn the preferences of an agent who solves a parametric optimization problem depending on an exogenous signal. Thus, the observer seeks the agent’s objective function that best explains a historical sequence of signals and corresponding optimal actions. We focus here on situations where the observer has imperfect information, that is, wh...

متن کامل

Data-driven Speech Denoising Using Noise Profiles

This paper describes a targeted, undemanding data-driven signal processing approach to identify, control, and suppress a specific background noise which is present in a recording together with a spoken utterance. A background noise (like e.g. the sound of an engine onboard a bus) negatively influences the ASR system performance by distorting the speech signal spectrum. Thus it is necessary to p...

متن کامل

Web Users' Cultural Profiles and E-Service Quality: Internationalization Implications for Tourism Web Sites

Although e-service quality (e-SQ) is vital for online purchases and loyalty, and the Internet is globalizing services, limited knowledge exists regarding the impact of Web users’ cultural profiles on their perceptions of e-SQ. Within the tourism industry, this is crucial as Web sites target multicultural users and firms are trying to develop localized Web stores. This study addresses this gap b...

متن کامل

Developing Quantum Annealer Driven Data Discovery

Machine learning applications are limited by computational power. In this paper, we gain novel insights into the application of quantum annealing (QA) to machine learning (ML) through experiments in natural language processing (NLP), seizure prediction, and linear separability testing. These experiments are performed on QA simulators and early-stage commercial QA hardware and compared to an unp...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Mathematical Problems in Engineering

سال: 2022

ISSN: ['1026-7077', '1563-5147', '1024-123X']

DOI: https://doi.org/10.1155/2022/6536908