PERSIA, Fabio, Giovanni PILATO, Mouzhi GE, Paolo BOLZONI, Daniela D'AURIA and Helmer SVEN. Improving Orienteering-based Tourist Trip Planning with Social Sensing. Future Generation Computer Systems. Elsevier, 2020, vol. 110, No 1, p. 931-945. ISSN 0167-739X. Available from: https://dx.doi.org/10.1016/j.future.2019.10.028.
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Basic information
Original name Improving Orienteering-based Tourist Trip Planning with Social Sensing
Authors PERSIA, Fabio (380 Italy), Giovanni PILATO (380 Italy), Mouzhi GE (156 China, guarantor, belonging to the institution), Paolo BOLZONI (380 Italy), Daniela D'AURIA (380 Italy) and Helmer SVEN (276 Germany).
Edition Future Generation Computer Systems, Elsevier, 2020, 0167-739X.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Netherlands
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 7.187
RIV identification code RIV/00216224:14330/20:00115119
Organization unit Faculty of Informatics
Doi http://dx.doi.org/10.1016/j.future.2019.10.028
UT WoS 000541153400078
Keywords in English Social sensing;Orienteering;Semantic mapping;Semantic similarity
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 10/5/2021 05:01.
Abstract
We enhance a tourist trip planning framework based on orienteering with category constraints by adding social sensing. This allows us to customize a user’s experience without putting the burden of preference elicitation on the user. We identify the interests of a user by analyzing their Tweets and then match these interests to descriptions of points of interests. For this analysis we adapt different schemes for social sensing to the needs of our orienteering context and compare them to find the most suitable approach. We show that our technique is fast enough for use in real-time dynamic settings and also has a higher accuracy compared to previous approaches. Additionally, we integrate a more efficient algorithm for solving the orienteering problem, boosting the overall performance and utility of our framework further, as demonstrated by the positive user satisfaction received by real users.
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