Ontological recommendation multi-agent for Tainan City travel
Ontological recommendation multi-agent for Tainan City travel
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DOI：
10.1016/j.eswa.2008.08.016
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发表时间：
2009-04
期刊：
影响因子：
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通讯作者：
Chang-Shing Lee;Young-Chung Chang;Mei-Hui Wang
中科院分区：
文献类型：
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作者：
Chang-Shing Lee;Young-Chung Chang;Mei-Hui Wang
由于旅游的逐渐增加，旅行社在规划和推荐个性化旅游路线方面发挥着重要作用。台南市位于台湾南部，以其丰富的历史遗迹和美味的小吃而闻名，多年来一直是台湾最受欢迎的旅游景点之一。本文提出台南市旅游的本体推荐多智能体。智能体的核心技术包括本体模型、模糊推理机制和蚁群优化。建议的旅行社可以根据游客的要求，为游客推荐个性化的旅游路线来享受台南市。它包括一个上下文决策代理和一个旅行路线推荐代理。首先，情境决策代理根据游客需求和台南市旅游本体，找出合适的位置距离，统计情境关系，推断情境信息。接下来，旅行路线推荐代理负责寻找个性化的旅行，并将此旅行路线绘制在谷歌地图上。最后，游客可以按照个性化的旅游路线，在台南市逗留期间，享受当地的文化遗产和美食。实验结果表明，该方法可以有效地推荐符合游客需求的旅游路线。
Due to the gradual increase in travel, the travel agent plays an important role in both planning and recommending a personalized travel route. Tainan City, located in the southern Taiwan, is famous for its abundant historic sites and delicious snack food, and it has been one of the top tourist attractions in Taiwan for years. In this paper, we propose an ontological recommendation multi-agent for Tainan City travel. The core technologies of the agent contain the ontology model, fuzzy inference mechanism, and ant colony optimization. The proposed agent can recommend the tourist a personalized travel route to enjoy Tainan City according to the tourist’s requirements. It includes a context decision agent and a travel route recommendation agent. First, the context decision agent finds a suitable location distance, counts the context relation, and infers the context information based on the tourist’s requirements and Tainan City travel ontology. Next, the travel route recommendation agent is responsible for finding a personalized tour and plotting this travel route on the Google Map. Finally, the tourist can follow the personalized travel route to enjoy the cultural heritage and the local gourmet food during his stay at Tainan City. The experimental results show that the proposed approach can effectively recommend a travel route matched with the tourist’s requirements.