Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Extracting Semantic Location from Outdoor Positioning Systems
MDM '06 Proceedings of the 7th International Conference on Mobile Data Management
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In this paper, we propose a novel similarity measure between trajectory data and geometry data using textual information retrieval techniques. Currently, many trajectory data are generated and used for sightseeing. When users search trajectory data at sightseeing, if a user's current position is similar to a retrieval target trajectory datum, this trajectory datum should be useful. However, even if the euclidean distances between the moving points in trajectory data and the user's position have small values, these trajectory data are not always relevant to the user's interests. In this paper, we deal with textual information retrieval method to measure the similarity values between retrieval target trajectory data and user's current position. Using our proposed method, users can gain relevant sightseeing spots as retrieval results. In our experimental evaluation, we confirmed that our proposed method can retrieve intuitively relevant trajectory data.