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pro vyhledávání: '"Kennedy, William P"'
The integration of unmanned aerial vehicles (UAVs) with mobile edge computing (MEC) and Internet of Things (IoT) technology in smart farms is pivotal for efficient resource management and enhanced agricultural productivity sustainably. This paper add
Externí odkaz:
http://arxiv.org/abs/2407.19657
In this paper, we address the problem of fair sharing of the total value of a crowd-sourced network system between major participants (founders) and minor participants (crowd) using cooperative game theory. Shapley allocation is regarded as a fair wa
Externí odkaz:
http://arxiv.org/abs/2305.12756
Autor:
Leung, John Kalung, Griva, Igor, Kennedy, William G., Kinser, Jason M., Park, Sohyun, Lee, Seo Young
This paper presents an innovative approach to address the problems researchers face in Emotion Aware Recommender Systems (EARS): the difficulty and cumbersome collecting voluminously good quality emotion-tagged datasets and an effective way to protec
Externí odkaz:
http://arxiv.org/abs/2305.04796
Publikováno v:
International Journal on Natural Language Computing (IJNLC) Vol. 9, No. 4, August 2020
We derive a method to enhance the evaluation for a text-based Emotion Aware Recommender that we have developed. However, we did not implement a suitable way to assess the top-N recommendations subjectively. In this study, we introduce an emotion-awar
Externí odkaz:
http://arxiv.org/abs/2102.05719
Publikováno v:
International Journal on Natural Language Computing (IJNLC) Vol. 10, No. 1, February 2021
Recommender Systems are a subclass of information retrieval systems, or more succinctly, a class of information filtering systems that seeks to predict how close is the match of the user's preference to a recommended item. A common approach for makin
Externí odkaz:
http://arxiv.org/abs/2102.04447
Publikováno v:
David C. Wyld et al. (Eds): AIAP, SIGML, CNSA, NIAI - 2021 pp. 113-129, 2021. CS & IT - CSCP 2021
This paper utilizes an ingenious text-based affective aware pseudo association method (AAPAM) to link disjoint users and items across different information domains and leverage them to make cross-domain content-based and collaborative filtering recom
Externí odkaz:
http://arxiv.org/abs/2012.05982
Publikováno v:
David C. Wyld et al. (Eds): CCSEA, BIoT, DKMP, CLOUD, NLCAI, SIPRO - 2020 pp. 101-114, 2020
We apply the concept of users' emotion vectors (UVECs) and movies' emotion vectors (MVECs) as building components of Emotion Aware Recommender System. We built a comparative platform that consists of five recommenders based on content-based and colla
Externí odkaz:
http://arxiv.org/abs/2007.01455
Publikováno v:
In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, 161-168, 2020
This paper investigates the causality in the decision making of movie recommendations through the users' affective profiles. We advocate a method of assigning emotional tags to a movie by the auto-detection of the affective features in the movie's ov
Externí odkaz:
http://arxiv.org/abs/2007.00636
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