Zobrazeno 1 - 10
of 569
pro vyhledávání: '"aspect extraction"'
Autor:
Mikail Muhammad Azman Busst, Kalaiarasi Sonai Muthu Anbananthen, Subarmaniam Kannan, Rajkumar Kannan
Publikováno v:
Emerging Science Journal, Vol 8, Iss 1, Pp 61-76 (2024)
The proliferation of user-generated content on social networks and websites has heightened the significance of sentiment analysis, also known as opinion mining, as a critical tool for comprehending people’s attitudes toward various topics. Aspect-l
Externí odkaz:
https://doaj.org/article/e0ef7309f0b641fabad844f3042968d1
Autor:
Satarupa Biswas, G. Poornalatha
Publikováno v:
IEEE Access, Vol 12, Pp 169606-169613 (2024)
Aspect-based opinion mining has become a significant information extraction technique based on natural language processing, driven by the growing volume of online user-generated content. This approach aims to determine the opinion polarity of specifi
Externí odkaz:
https://doaj.org/article/1816d38939db48269e4eb8bfafb165ce
Publikováno v:
IEEE Access, Vol 12, Pp 72361-72373 (2024)
Aspect extraction is the most important factor influencing the quality of Aspect-Based Sentiment Analysis (ABSA). Aspect extractions are divided into three approaches: supervised, unsupervised, and hybrid methods. Most previous aspect extraction algo
Externí odkaz:
https://doaj.org/article/d2ea2a77741143f691653cbd8c3f8396
Autor:
Mikail Muhammad Azman Busst, Kalaiarasi Sonai Muthu Anbananthen, Subarmaniam Kannan, Jayakumar Krishnan, Sridevi Subbiah
Publikováno v:
IEEE Access, Vol 12, Pp 3528-3539 (2024)
Aspect extraction poses a significant challenge in Natural Language Processing (NLP). Extracting explicit and implicit aspects from online text data remains an ongoing challenge despite significant research efforts. Enhancing the accuracy and effecti
Externí odkaz:
https://doaj.org/article/9028d506298247e39ff5764755df5978
Publikováno v:
IEEE Access, Vol 12, Pp 2288-2302 (2024)
Educational institutions typically gather feedback from beneficiaries through formal surveys. Offering open-ended questions allows students to express their opinions about matters that may not have been measured directly in closed-ended questions. Ho
Externí odkaz:
https://doaj.org/article/e62a71c1aa334b72aae78036940454f3
Publikováno v:
Applied Computing and Informatics, Vol 20, Iss 1/2, Pp 142-161 (2024)
Digital resources such as smart applications reviews and online feedback information are important sources to seek customers’ feedback and input. This paper aims to help government entities gain insights on the needs and expectations of their custo
Externí odkaz:
https://doaj.org/article/112ef5c73c04491dbe2e8c811fb9403b
Publikováno v:
IJAIN (International Journal of Advances in Intelligent Informatics), Vol 9, Iss 2, Pp 273-285 (2023)
Feedback and comments on mobile commerce applications are extremely useful and valuable information sources that reflect the quality of products or services to determine whether data is positive or negative and help businesses monitor brand and produ
Externí odkaz:
https://doaj.org/article/825761d886694e9a8b6a54f47f5a7080
Publikováno v:
PeerJ Computer Science, Vol 10, p e1821 (2024)
Opinion mining is gaining significant research interest, as it directly and indirectly provides a better avenue for understanding customers, their sentiments toward a service or product, and their purchasing decisions. However, extracting every opini
Externí odkaz:
https://doaj.org/article/8a75b697f9cf41beb19e6f6f184b7b43
Publikováno v:
Jisuanji kexue, Vol 50, Iss 4, Pp 188-195 (2023)
Extractive automatic text summarization aims to extract the sentences that can best express the semantics of the full text from the original text to form a summary.It is widely used and studied due to its simplicity and efficiency.Currently,extractiv
Externí odkaz:
https://doaj.org/article/bf9c4c309b264daab77f4fa6704d25e4
Autor:
Worku Abebe Degife, Bor-Shen Lin
Publikováno v:
Applied Sciences, Vol 14, Iss 10, p 4221 (2024)
This paper presents an advanced method for forecasting flight fares that combines aspect-based sentiment analysis (ABSA) with deep learning techniques, particularly the gated recurrent unit (GRU) model. This approach leverages historical airline tick
Externí odkaz:
https://doaj.org/article/da8e4dba56b7437abb9efd28edf5f561