Integrating user reviews and risk factors from social networks in a multi-objective recommender system DOI

Ali Noorian

Electronic Commerce Research, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 26, 2024

Language: Английский

Use Cases of ChatGPT and Other AI Tools With Security Concerns DOI
Ayushi Agarwal,

Aaditya Trivedi,

Priyanka Sharma

et al.

Advances in computational intelligence and robotics book series, Journal Year: 2024, Volume and Issue: unknown, P. 216 - 225

Published: May 28, 2024

The text explores the impact of large language models (LLMs), such as ChatGPT, on various industries, emphasizing their accessibility and efficiency. However, it highlights limitations LLMs, including token constraints, unexpected threat posed to creative jobs AI like DALL-E replicate art styles. Companies face a choice between AI-driven solutions human consultants, with importance crafting effective prompts for LLMs emphasized. To adapt, startups established companies must consider utilizing even if lacking in-house expertise, navigate evolving landscape effectively, continues reshape industries professional roles.

Language: Английский

Citations

8
Potential applications of innovative AI-based tools in hydrogen energy development: Leveraging large language model technologies DOI
Matin Shahin, Mohammad Simjoo

International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: 102, P. 918 - 936

Published: Jan. 12, 2025

Language: Английский

Citations

1
Detecting fake review intentions in the review context: A multimodal deep learning approach DOI
Jingrui Hou, Z. Q. Tan, Shitou Zhang

et al.

Electronic Commerce Research and Applications, Journal Year: 2025, Volume and Issue: unknown, P. 101485 - 101485

Published: Feb. 1, 2025

Language: Английский

Citations

1
Mirror, Mirror: Exploring Stereotype Presence Among Top-N Recommendations That May Reach Children DOI Creative Commons
Robin Ungruh, Murtadha Al Nahadi, Maria Soledad Pera

et al.

ACM Transactions on Recommender Systems, Journal Year: 2025, Volume and Issue: unknown

Published: March 6, 2025

Children form stereotypes by observing stereotypical expressions during childhood, influencing their future beliefs, attitudes, and behavior. These perceptions, often negative, can surface across the many online media platforms that children access, like streaming services social media. Given of items displayed on these are commonly selected recommendation algorithms ( RAs ), it becomes critical to investigate role in suggesting could negatively impact this vulnerable population. We address concern conducting an empirical evaluation gauge presence Gender, Race, Religion among top-10 recommendations generated a wide range two well-known datasets different domains: Movielens (movies) GoodReads (books). Results analyses reveal all frequently recommend items. Gender particularly prevalent, appearing almost every list emerging as most common stereotype. Our results indicate no algorithm has consistent tendency towards recommending more content; instead, high stereotype be found strategies. Outcomes from work underscore potential risks pose perpetuating reinforcing harmful stereotypes—this prompts reflections implications for design recommender systems.

Language: Английский

Citations

0
Prioritizing App Reviews for Developer Responses on Google Play DOI

Mohsen Jafari,

Abbas Heydarnoori,

Forough Majidi

et al.

SSRN Electronic Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

0
Navigating the future of sexuality education in the USA: applying technology mediation theory to AI-Facilitated Sexuality Education DOI
Kirsten M. Greer, Shahzarin Khan,

Dechen Sangmo

et al.

Sex Education, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 15

Published: Sept. 20, 2024

Language: Английский

Citations

1
Design and Realization of Database System for Judgement Documents Based on Natural Language Processing DOI Open Access

Yanqing Fang

The Frontiers of Society Science and Technology, Journal Year: 2024, Volume and Issue: 6(1)

Published: Jan. 1, 2024

In this paper, based on natural language processing technology, we designed and realized a database system of judgement instruments. By analyzing the instruments crimes, have used technology to classify instruments, extract keywords information, realize rapid retrieval accurate analysis instrument database. design process, adopted reasonable method for ensure stability scalability system. realization scheme, made full use existing technical resources algorithmic models efficiency accuracy Through study, come conclusion that job-related crime can effectively improve quality provide strong support research practice in related fields.

Language: Английский

Citations

0
Integrating user reviews and risk factors from social networks in a multi-objective recommender system DOI

Ali Noorian

Electronic Commerce Research, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 26, 2024

Language: Английский

Citations

0