Recommendation System Based on Customer Reviews Using AI and NLP Article Swipe
K. Dhanunjayudu
,
M. Jyothi
,
G. Md Roshan Zameer
,
D. Rameeja
,
G. K. Veeresh
,
C. Surendra
,
Prashanth Reddy
,
Devender Reddy
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.46647/ijetms.2025.v09i02.065
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.46647/ijetms.2025.v09i02.065
In thee-commerce landscape,personalized recommendation significantly enhance customer satisfaction and engagement. This project presents the development of a recommendation system that utilizes Artificial Intelligence (AI) and Natural Language Processing (NLP) to analyze customer reviews for better product or service suggestions. The system processes large volumes of textual data using sentiment analysis, keyword extraction, and topic modeling to identify preferences, needs, and trends. It integrates collaborative and content-based filtering methods to offer relevant and adaptive recommendations based on user feedback. The resulting system demonstrates improved accuracy, user trust, and scalability for real-world applications. The recommendation engine combines collaborative filtering, which analyzes user behavior, with content-based filtering, which considers the product attributes mentioned in reviews. By integrating both methods, the system provides personalized and highly relevant recommendations tailored to individual user profiles. It adapts to evolving preferences by continuously learning from new data and user feedback. This approach ensures that the system not only predicts what users might like but also anticipates needs based on past interactions and review data. The result is an intelligent, scalable system that improves over time and provides an enhanced user experience.
Related Topics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.46647/ijetms.2025.v09i02.065
- https://doi.org/10.46647/ijetms.2025.v09i02.065
- OA Status
- diamond
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409711079
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4409711079Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.46647/ijetms.2025.v09i02.065Digital Object Identifier
- Title
-
Recommendation System Based on Customer Reviews Using AI and NLPWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-01-01Full publication date if available
- Authors
-
K. Dhanunjayudu, M. Jyothi, G. Md Roshan Zameer, D. Rameeja, G. K. Veeresh, C. Surendra, Prashanth Reddy, Devender ReddyList of authors in order
- Landing page
-
https://doi.org/10.46647/ijetms.2025.v09i02.065Publisher landing page
- PDF URL
-
https://doi.org/10.46647/ijetms.2025.v09i02.065Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.46647/ijetms.2025.v09i02.065Direct OA link when available
- Concepts
-
Natural language processing, Artificial intelligence, Computer scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4409711079 |
|---|---|
| doi | https://doi.org/10.46647/ijetms.2025.v09i02.065 |
| ids.doi | https://doi.org/10.46647/ijetms.2025.v09i02.065 |
| ids.openalex | https://openalex.org/W4409711079 |
| fwci | 0.0 |
| type | article |
| title | Recommendation System Based on Customer Reviews Using AI and NLP |
| biblio.issue | 2 |
| biblio.volume | 9 |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T14484 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9247000217437744 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1710 |
| topics[0].subfield.display_name | Information Systems |
| topics[0].display_name | Technology and Data Analysis |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C204321447 |
| concepts[0].level | 1 |
| concepts[0].score | 0.6772972941398621 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q30642 |
| concepts[0].display_name | Natural language processing |
| concepts[1].id | https://openalex.org/C154945302 |
| concepts[1].level | 1 |
| concepts[1].score | 0.6513957977294922 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[1].display_name | Artificial intelligence |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.5511108636856079 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| keywords[0].id | https://openalex.org/keywords/natural-language-processing |
| keywords[0].score | 0.6772972941398621 |
| keywords[0].display_name | Natural language processing |
| keywords[1].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[1].score | 0.6513957977294922 |
| keywords[1].display_name | Artificial intelligence |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.5511108636856079 |
| keywords[2].display_name | Computer science |
| language | en |
| locations[0].id | doi:10.46647/ijetms.2025.v09i02.065 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210180963 |
| locations[0].source.issn | 2581-4621 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2581-4621 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | International Journal of Engineering Technology and Management Sciences |
| locations[0].source.host_organization | |
| locations[0].source.host_organization_name | |
| locations[0].license | |
| locations[0].pdf_url | https://doi.org/10.46647/ijetms.2025.v09i02.065 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | international journal of engineering technology and management sciences |
| locations[0].landing_page_url | https://doi.org/10.46647/ijetms.2025.v09i02.065 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5112911415 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | K. Dhanunjayudu |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | None K. Dhanunjayudu |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5007104793 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | M. Jyothi |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | None M. Nirmala Jyothi |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5117268764 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | G. Md Roshan Zameer |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | None G. Md Roshan Zameer |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5117268765 |
| authorships[3].author.orcid | |
| authorships[3].author.display_name | D. Rameeja |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | None D. Rameeja |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5083675637 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | G. K. Veeresh |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | None G. Veeresh |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5092344333 |
| authorships[5].author.orcid | |
| authorships[5].author.display_name | C. Surendra |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | None C. Surendra |
| authorships[5].is_corresponding | False |
| authorships[6].author.id | https://openalex.org/A5113046318 |
| authorships[6].author.orcid | |
| authorships[6].author.display_name | Prashanth Reddy |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | None P.Raghavendra Reddy |
| authorships[6].is_corresponding | False |
| authorships[7].author.id | https://openalex.org/A5009229277 |
| authorships[7].author.orcid | |
| authorships[7].author.display_name | Devender Reddy |
| authorships[7].author_position | last |
| authorships[7].raw_author_name | None D. Naga Malleshwara Reddy |
| authorships[7].is_corresponding | False |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.46647/ijetms.2025.v09i02.065 |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Recommendation System Based on Customer Reviews Using AI and NLP |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T14484 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9247000217437744 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1710 |
| primary_topic.subfield.display_name | Information Systems |
| primary_topic.display_name | Technology and Data Analysis |
| related_works | https://openalex.org/W4391375266, https://openalex.org/W2899084033, https://openalex.org/W2748952813, https://openalex.org/W2390279801, https://openalex.org/W4391913857, https://openalex.org/W2358668433, https://openalex.org/W4396701345, https://openalex.org/W2376932109, https://openalex.org/W2001405890, https://openalex.org/W3204019825 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.46647/ijetms.2025.v09i02.065 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210180963 |
| best_oa_location.source.issn | 2581-4621 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2581-4621 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | International Journal of Engineering Technology and Management Sciences |
| best_oa_location.source.host_organization | |
| best_oa_location.source.host_organization_name | |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://doi.org/10.46647/ijetms.2025.v09i02.065 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | international journal of engineering technology and management sciences |
| best_oa_location.landing_page_url | https://doi.org/10.46647/ijetms.2025.v09i02.065 |
| primary_location.id | doi:10.46647/ijetms.2025.v09i02.065 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210180963 |
| primary_location.source.issn | 2581-4621 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2581-4621 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | International Journal of Engineering Technology and Management Sciences |
| primary_location.source.host_organization | |
| primary_location.source.host_organization_name | |
| primary_location.license | |
| primary_location.pdf_url | https://doi.org/10.46647/ijetms.2025.v09i02.065 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | international journal of engineering technology and management sciences |
| primary_location.landing_page_url | https://doi.org/10.46647/ijetms.2025.v09i02.065 |
| publication_date | 2025-01-01 |
| publication_year | 2025 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 16 |
| abstract_inverted_index.By | 112 |
| abstract_inverted_index.In | 0 |
| abstract_inverted_index.It | 61, 129 |
| abstract_inverted_index.an | 170, 180 |
| abstract_inverted_index.by | 134 |
| abstract_inverted_index.in | 110 |
| abstract_inverted_index.is | 169 |
| abstract_inverted_index.of | 15, 44 |
| abstract_inverted_index.on | 75, 161 |
| abstract_inverted_index.or | 36 |
| abstract_inverted_index.to | 29, 55, 68, 125, 131 |
| abstract_inverted_index.The | 39, 78, 91, 167 |
| abstract_inverted_index.and | 8, 24, 52, 59, 64, 71, 86, 120, 140, 164, 178 |
| abstract_inverted_index.but | 156 |
| abstract_inverted_index.for | 33, 88 |
| abstract_inverted_index.new | 138 |
| abstract_inverted_index.not | 149 |
| abstract_inverted_index.the | 13, 106, 116, 147 |
| abstract_inverted_index.(AI) | 23 |
| abstract_inverted_index.This | 10, 143 |
| abstract_inverted_index.also | 157 |
| abstract_inverted_index.both | 114 |
| abstract_inverted_index.data | 46, 139 |
| abstract_inverted_index.from | 137 |
| abstract_inverted_index.like | 155 |
| abstract_inverted_index.only | 150 |
| abstract_inverted_index.over | 176 |
| abstract_inverted_index.past | 162 |
| abstract_inverted_index.that | 19, 146, 174 |
| abstract_inverted_index.time | 177 |
| abstract_inverted_index.user | 76, 84, 99, 127, 141, 182 |
| abstract_inverted_index.what | 152 |
| abstract_inverted_index.with | 101 |
| abstract_inverted_index.(NLP) | 28 |
| abstract_inverted_index.based | 74, 160 |
| abstract_inverted_index.data. | 166 |
| abstract_inverted_index.large | 42 |
| abstract_inverted_index.might | 154 |
| abstract_inverted_index.needs | 159 |
| abstract_inverted_index.offer | 69 |
| abstract_inverted_index.topic | 53 |
| abstract_inverted_index.users | 153 |
| abstract_inverted_index.using | 47 |
| abstract_inverted_index.which | 97, 104 |
| abstract_inverted_index.adapts | 130 |
| abstract_inverted_index.better | 34 |
| abstract_inverted_index.engine | 93 |
| abstract_inverted_index.highly | 121 |
| abstract_inverted_index.needs, | 58 |
| abstract_inverted_index.result | 168 |
| abstract_inverted_index.review | 165 |
| abstract_inverted_index.system | 18, 40, 80, 117, 148, 173 |
| abstract_inverted_index.trust, | 85 |
| abstract_inverted_index.Natural | 25 |
| abstract_inverted_index.analyze | 30 |
| abstract_inverted_index.enhance | 5 |
| abstract_inverted_index.ensures | 145 |
| abstract_inverted_index.keyword | 50 |
| abstract_inverted_index.methods | 67 |
| abstract_inverted_index.product | 35, 107 |
| abstract_inverted_index.project | 11 |
| abstract_inverted_index.reviews | 32 |
| abstract_inverted_index.service | 37 |
| abstract_inverted_index.textual | 45 |
| abstract_inverted_index.trends. | 60 |
| abstract_inverted_index.volumes | 43 |
| abstract_inverted_index.Language | 26 |
| abstract_inverted_index.adaptive | 72 |
| abstract_inverted_index.analyzes | 98 |
| abstract_inverted_index.approach | 144 |
| abstract_inverted_index.combines | 94 |
| abstract_inverted_index.customer | 6, 31 |
| abstract_inverted_index.enhanced | 181 |
| abstract_inverted_index.evolving | 132 |
| abstract_inverted_index.identify | 56 |
| abstract_inverted_index.improved | 82 |
| abstract_inverted_index.improves | 175 |
| abstract_inverted_index.learning | 136 |
| abstract_inverted_index.methods, | 115 |
| abstract_inverted_index.modeling | 54 |
| abstract_inverted_index.predicts | 151 |
| abstract_inverted_index.presents | 12 |
| abstract_inverted_index.provides | 118, 179 |
| abstract_inverted_index.relevant | 70, 122 |
| abstract_inverted_index.reviews. | 111 |
| abstract_inverted_index.scalable | 172 |
| abstract_inverted_index.tailored | 124 |
| abstract_inverted_index.utilizes | 20 |
| abstract_inverted_index.accuracy, | 83 |
| abstract_inverted_index.analysis, | 49 |
| abstract_inverted_index.behavior, | 100 |
| abstract_inverted_index.considers | 105 |
| abstract_inverted_index.feedback. | 77, 142 |
| abstract_inverted_index.filtering | 66 |
| abstract_inverted_index.mentioned | 109 |
| abstract_inverted_index.processes | 41 |
| abstract_inverted_index.profiles. | 128 |
| abstract_inverted_index.resulting | 79 |
| abstract_inverted_index.sentiment | 48 |
| abstract_inverted_index.Artificial | 21 |
| abstract_inverted_index.Processing | 27 |
| abstract_inverted_index.attributes | 108 |
| abstract_inverted_index.filtering, | 96, 103 |
| abstract_inverted_index.individual | 126 |
| abstract_inverted_index.integrates | 62 |
| abstract_inverted_index.real-world | 89 |
| abstract_inverted_index.anticipates | 158 |
| abstract_inverted_index.development | 14 |
| abstract_inverted_index.engagement. | 9 |
| abstract_inverted_index.experience. | 183 |
| abstract_inverted_index.extraction, | 51 |
| abstract_inverted_index.integrating | 113 |
| abstract_inverted_index.preferences | 133 |
| abstract_inverted_index.scalability | 87 |
| abstract_inverted_index.Intelligence | 22 |
| abstract_inverted_index.continuously | 135 |
| abstract_inverted_index.demonstrates | 81 |
| abstract_inverted_index.intelligent, | 171 |
| abstract_inverted_index.interactions | 163 |
| abstract_inverted_index.personalized | 119 |
| abstract_inverted_index.preferences, | 57 |
| abstract_inverted_index.satisfaction | 7 |
| abstract_inverted_index.suggestions. | 38 |
| abstract_inverted_index.applications. | 90 |
| abstract_inverted_index.collaborative | 63, 95 |
| abstract_inverted_index.content-based | 65, 102 |
| abstract_inverted_index.significantly | 4 |
| abstract_inverted_index.thee-commerce | 1 |
| abstract_inverted_index.recommendation | 3, 17, 92 |
| abstract_inverted_index.recommendations | 73, 123 |
| abstract_inverted_index.landscape,personalized | 2 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile.value | 0.16212473 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |