The effects of controllability and explainability in a social recommender system

CH Tsai, P Brusilovsky - User Modeling and User-Adapted Interaction, 2021 - Springer
In recent years, researchers in the field of recommender systems have explored a range of
advanced interfaces to improve user interactions with recommender systems. Some of the …

Toward personalized answer generation in e-commerce via multi-perspective preference modeling

Y Deng, Y Li, W Zhang, B Ding, W Lam - ACM Transactions on …, 2022 - dl.acm.org
Recently, Product Question Answering (PQA) on E-Commerce platforms has attracted
increasing attention as it can act as an intelligent online shopping assistant and improve the …

A topic modeling‐based bibliometric exploration of automatic summarization research

X Chen, H Xie, X Tao, L Xu, J Wang… - … : Data Mining and …, 2024 - Wiley Online Library
The surge in text data has driven extensive research into developing diverse automatic
summarization approaches to effectively handle vast textual information. There are several …

Unsupervised semantic approach of aspect-based sentiment analysis for large-scale user reviews

SM Al-Ghuribi, SAM Noah, S Tiun - IEEE Access, 2020 - ieeexplore.ieee.org
Aspect-based sentiment analysis (ABSA) has recently attracted increasing attention due to
its extensive applications. Most of the existing ABSA methods been applied on small-sized …

Generating post hoc review-based natural language justifications for recommender systems

C Musto, M de Gemmis, P Lops, G Semeraro - User Modeling and User …, 2021 - Springer
In this article, we present a framework to build post hoc natural language justifications that
supports the suggestions generated by a recommendation algorithm. Our methodology is …

Attribute-sentiment-guided summarization of user opinions from online reviews

Y Han, G Nanda… - Journal of …, 2023 - asmedigitalcollection.asme.org
Eliciting informative user opinions from online reviews is a key success factor for innovative
product design and development. The unstructured, noisy, and verbose nature of user …

Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data

AL Zanon, LCD da Rocha, MG Manzato - Knowledge-Based Systems, 2022 - Elsevier
Collaborative filtering recommendation algorithms generate suggestions based on similar
interactions between users. Although it provides accurate recommendations, the approach …

Examining the effects of power status of an explainable artificial intelligence system on users' perceptions

T Ha, YJ Sah, Y Park, S Lee - Behaviour & Information Technology, 2022 - Taylor & Francis
Contrary to the traditional concept of artificial intelligence, explainable artificial intelligence
(XAI) aims to provide explanations for the prediction results and make users perceive the …

A unified dual-view model for review summarization and sentiment classification with inconsistency loss

HP Chan, W Chen, I King - Proceedings of the 43rd international ACM …, 2020 - dl.acm.org
Acquiring accurate summarization and sentiment from user reviews is an essential
component of modern e-commerce platforms. Review summarization aims at generating a …

Extracting and ranking product features in consumer reviews based on evidence theory

L Zhou, L Tang, Z Zhang - Journal of Ambient Intelligence and Humanized …, 2023 - Springer
Online consumer product reviews have been the primary source for manufacturers and
consumers to obtain consumer knowledge and product information. However, the explosion …