Travel Intention-Based Attraction Network for Recommending Travel Destinations

被引：0

作者：

Oh, Kyo-Joong ^{[1
]}

Kim, Zaemyung ^{[1
]}

Oh, Hyungrai ^{[3
]}

Lim, Chae-Gyun ^{[1
]}

Gweon, Gahgene ^{[2
]}

机构：

[1] Korea Adv Inst Sci & Technol, Sch Comp, Daejeon, South Korea

[2] Korea Adv Inst Sci & Technol, Dept Knowledge Serv Engn, Daejeon, South Korea

[3] Samsung Elect Inc, Software Ctr, Suwon, Gyeonggi Do, South Korea

来源：

2016 INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP) | 2016年

关键词：

opinion mining; intention analysis; attraction network; destination prediction;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Recommending travel destinations on the basis of users' travel intentions is a research topic being studied recently in the field of intention analysis. This study considers travel intentions from a large number of travel-related reviews containing the reviewers' purpose for visiting the points of interest (POIs). We analyze travel intentions of 83,207 POIs using 6,791,427 reviews in www.TripAdvisor.com with domain-tailored word embedding model. Building an attraction network based on travel intentions helps to recommend travel destinations to travelers and reviewers. We present three prediction methods to recommend travel destinations with an attraction network and description logic. We also present the evaluation results of recommendations from some prediction scenarios. Consequently, the travel intention classification is commensurate with an analysis of intentions from textual data, and the attraction network is useful for recommending travel destinations on the basis of short- and long-term user preferences.

引用

页码：277 / 280

页数：4

共 50 条

[1] On Recommending Safe Travel Periods to High Attack Risk Destinations
Spiliotopoulos, Dimitris
Vassilakis, Costas
Margaris, Dionisis
[J]. 2020 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM), 2020, : 854 - 861
[2] TRAVEL DESTINATIONS AND PERSONALITY IN TRAVEL AGENTS
HOXTER, AL
LESTER, D
KULAK, Y
MOLL, JK
[J]. PSYCHOLOGICAL REPORTS, 1987, 61 (03) : 886 - 886
[3] Modelling the attraction of travel to shopping destinations in large-scale modelling
Kristoffersson, Ida
Daly, Andrew
Algers, Staffan
[J]. TRANSPORT POLICY, 2018, 68 : 52 - 62
[4] Travel Intention to Visit Tourism Destinations: A Perspective of Generation Z in Vietnam
Viet Hoang Nguyen
Thi Xuan Dao Truong
Huong Trang Pham
Duc Thanh Tran
Pham Hung Nguyen
[J]. JOURNAL OF ASIAN FINANCE ECONOMICS AND BUSINESS, 2021, 8 (02): : 1043 - 1053
[5] The impact of travel constraints on travel intention
Andreani, F.
Njo, A.
[J]. PROMOTING CREATIVE TOURISM: CURRENT ISSUES INTOURISM RESEARCH, 2021, : 652 - 658
[6] Recommending Travel Packages Based on Mobile Crowdsourced Data
Yu, Zhiwen
Feng, Yun
Xu, Huang
Zhou, Xingshe
[J]. IEEE COMMUNICATIONS MAGAZINE, 2014, 52 (08) : 56 - 62
[7] A Web-based Application for Recommending Travel Regions
Woerndl, Wolfgang
[J]. ADJUNCT PUBLICATION OF THE 25TH CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION (UMAP'17), 2017, : 105 - 106
[8] Travel influencer credibility on Instagram affecting traveler's choosing destinations intention
Silva, Ayslane
Mendes-Filho, Luiz
[J]. REVISTA BRASILEIRA DE PESQUISA EM TURISMO, 2023, 17
[9] A Framework for Understanding Travel Intention Post-Pandemic to International Tourist Destinations
Mheidat, Mohammad Zain
Marzuki, Azizan
[J]. TOURISM, 2023, 71 (02): : 388 - 397
[10] Adoption intention of virtual reality in choosing travel destinations in the context of a developing economy
Rasul, Tareq
[J]. TOURISM RECREATION RESEARCH, 2022, 47 (04) : 448 - 452

← 1 2 3 4 5 →