Semantic Recommender System for Touristic Context Based on Linked Data

被引：5

作者：

Cabrera Rivera, Luis ^{[1
]}

Vilches-Blazquez, Luis M. ^{[2
]}

Torres-Ruiz, Miguel ^{[1
]}

Moreno Ibarra, Marco Antonio ^{[1
]}

机构：

[1] Inst Politecn Nacl UPALM Zacatenco, Ctr Invest Comp, Mexico City 07320, DF, Mexico

[2] Univ Nacl Colombia, Bogota, DC, Colombia

来源：

INFORMATION FUSION AND GEOGRAPHIC INFORMATION SYSTEMS (IF&GIS' 2015): DEEP VIRTUALIZATION FOR MOBILE GIS | 2015年

关键词：

OF-THE-ART;

D O I：

10.1007/978-3-319-16667-4_5

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The lack of personalization presented in touristic itineraries that are offered by travel agencies involve a little flexibility. Basically, they are designed with the points of interest (POIs) that have more relevance in the area. On the other hand, there are POIs that have agreements with the agencies, which originate a excluding POIs that could be interesting for the tourist. In this work, a method capable to use the user preferences, like POIs and activities that user wants to realize during their vacations is proposed. Moreover, some weighted features such as the max distance that user wants to walk between POIs, and opinions of other users, coming from the web 2.0 by means of social media are taken into account. As result, a personalized route, which is composed of recommended POIs for the user and satisfied the user profile is provided.

引用

页码：77 / 89

页数：13

共 50 条

[1] Microblog semantic context retrieval system based on linked open data and graph-based theory
Kalloubi, Fahd
Nfaoui, El Habib
El Beqqali, Omar
EXPERT SYSTEMS WITH APPLICATIONS, 2016, 53 : 138 - 148
[2] PLDSD: Personalized Linked Data Semantic Distance for LOD-Based Recommender Systems
Mota da Silva, Gabriela Oliveira
Durao, Frederico Araujo
Capretz, Miriam
IIWAS2019: THE 21ST INTERNATIONAL CONFERENCE ON INFORMATION INTEGRATION AND WEB-BASED APPLICATIONS & SERVICES, 2019, : 294 - 303
[3] A hybrid recommender system based on description/dialetheic logic and linked data
Dos Santos, Ricardo
Aguilar, Jose
EXPERT SYSTEMS, 2023, 40 (02)
[4] Trust based Recommender System for the Semantic Web
Bedi, Punam
Kaur, Harmeet
Marwaha, Sudeep
20TH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2007, : 2677 - 2682
[5] A Linked Data Recommender System Using a Neighborhood-Based Graph Kernel
Ostuni, Vito Claudio
Di Noia, Tommaso
Mirizzi, Roberto
Di Sciascio, Eugenio
E-COMMERCE AND WEBTECHNOLOGIES, 2014, 188 : 89 - 100
[6] A hybrid semantic recommender system based on an improved clustering
Bahrani, Payam
Minaei-Bidgoli, Behrouz
Parvin, Hamid
Mirzarezaee, Mitra
Keshavarz, Ahmad
JOURNAL OF SUPERCOMPUTING, 2024, 80 (09): : 13341 - 13385
[7] A Semantic Recommender System for iDTV Based on Educational Competencies
Duran, Diego
Chanchi, Gabriel
Luis Arciniegas, Jose
Baldassarri, Sandra
APPLICATIONS AND USABILITY OF INTERACTIVE TV, JAUTI 2016, 2017, 689 : 47 - 61
[8] A Social Cultural Recommender based on Linked Open Data
De Angelis, Alessio
Gasparetti, Fabio
Micarelli, Alessandro
Sansonetti, Giuseppe
ADJUNCT PUBLICATION OF THE 25TH CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION (UMAP'17), 2017, : 329 - 332
[9] A semantic recommender system based on frequent tag pattern
Movahedian, Hamed
Khayyambashi, Mohammad Reza
INTELLIGENT DATA ANALYSIS, 2015, 19 (01) : 109 - 126
[10] Recommender system based on semantic similarity and collaborative filtering
Liu Pingfeng
Nie Guihua
Chen Donglin
PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON INNOVATION & MANAGEMENT, VOLS 1 AND 2, 2006, : 1112 - 1117

← 1 2 3 4 5 →