Accessing Touristic Knowledge Bases through a Natural Language Interface

2013 Second IIAI International Conference on Advanced Applied Informatics

2013

Blog articles by tourists contain interesting and personal experiences of where and how they have gone, what they have done and what they thought. Such individual experiences are helpful in many cases compared to the general and official information about the tourist resort by tourist agents. However, it is not easy to choose related articles and to extract still more nearly required information from these unsorted blog articles. We have proposed a method of feature extraction by dependency analysis of those sentences that describe tourist behavior. This paper apply the proposed method to 7,917,385 blog articles on Kyushu area and shows the evaluation about the obtained resources for tourism.

Section: Related Workmentioning

confidence: 99%

Evaluation of Tourism Resources Extraction Based on Japanese Dependency Analysis

2013 Second IIAI International Conference on Advanced Applied Informatics

2013

“…Ruiz‐Martinez et al . proposed a natural language interface for the search engine on tourism. Saito et al .…”

Section: Related Workmentioning

confidence: 99%

Text mining of tourism preference in a multilingual site

Zeng

IEEJ Transactions Elec Engng

et al. 2018

There is a huge demand on multilingual tourism information of Japan because of the increasing number of tourists from foreign countries. Most of them may expect typical and stereotyped culture, nature, and modern society of Japan. However, people from different backgrounds, cultures, and languages might expect different aspects of Japan, as well. In this paper, we analyze these kinds of differences as the cultural tourism preference for Japan. We propose a machine-learning-based method to figure out the cultural tourism preference of people of different countries based on comparing the access logs to a multilingual tourism information site in different languages. We focus our discussion on the pages accessed in Thai and Vietnamese languages. Our research result shows that for Thai tourists the characteristic features are the famous places in an area and local specialties, but Vietnamese tourists pay much more attention to facilities and location of hotels. This difference was not observable by naive extraction of keywords and their visualization. This result has been used as a guide to the further creation of content in the tourism information site.

“…Esparcia et al [2] proposed a recommendation and a clustering system, and showed their effectiveness for tourism portals. Ruiz-Martinez et al [10] developed a natural language interface for tourism search engine. Saito and Ohuchi [11] proposed "keymaps" that visualizes co-occurrences of keywords in tourism documents.…”

Section: Related Workmentioning

confidence: 99%

Extraction of Tourist Behavior Contexts from Blog by Verbs and Their Objects

2012 IIAI International Conference on Advanced Applied Informatics

2012

Blog articles by tourists contain interesting and personal experiences of where and how they have gone, what they have done and what they thought. Such individual experiences are helpful in many cases compared to the general and official information about the tourist resort by tourist agents. However, it is not easy to choose related articles and to extract still more nearly required information from these unsorted blog articles. This paper proposes a technique of feature extraction by dependency analysis of verbs and objects in those sentences that describe tourist's behavior. This paper applied the method to 7,917,385 blog articles on Kyushu area and reports some analysis on "where and what did they eat" as case studies.