Location and activity recommendation by using consecutive itinerary matching model

Jiun Shian Liu; Wen Hsiang Lu

Location and activity recommendation by using consecutive itinerary matching model

Department of Computer Science and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In fact, most people have had the experience that they haven't made detailed itinerary in advance before a journey, and as a result they don't know what place or what kind of activity is suitable as the next visit location and activity after they engage in an activity in a certain place. To alleviate such problem, in this paper, we proposed the Consecutive Itinerary Matching Model to help mobile users find next locations and activities in line with their leisure needs. This model effectively utilizes time, location, user, and activity as features to find the most possible “Consecutive Itinerary” and then recommend mobile users next locations and activities. In this preliminary study, although our approach achieved only about 30% top-1 inclusion rate, however, to our knowledge, this work is novel for the recommendation of location and activity based on consecutive itinerary discovery from check-in data.

Original language	English
Title of host publication	Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013
Publisher	The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
Pages	288-301
Number of pages	14
ISBN (Electronic)	9789573079262
Publication status	Published - 2013 Oct 1
Event	25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013 - Kaohsiung, Taiwan Duration: 2013 Oct 4 → 2013 Oct 5

Publication series

Name	Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013

Conference

Conference	25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013
Country/Territory	Taiwan
City	Kaohsiung
Period	13-10-04 → 13-10-05

All Science Journal Classification (ASJC) codes

Speech and Hearing
Language and Linguistics

Cite this

Liu, J. S., & Lu, W. H. (2013). Location and activity recommendation by using consecutive itinerary matching model. In Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013 (pp. 288-301). (Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013). The Association for Computational Linguistics and Chinese Language Processing (ACLCLP).

Liu, Jiun Shian ; Lu, Wen Hsiang. / Location and activity recommendation by using consecutive itinerary matching model. Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP), 2013. pp. 288-301 (Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013).

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abstract = "In fact, most people have had the experience that they haven't made detailed itinerary in advance before a journey, and as a result they don't know what place or what kind of activity is suitable as the next visit location and activity after they engage in an activity in a certain place. To alleviate such problem, in this paper, we proposed the Consecutive Itinerary Matching Model to help mobile users find next locations and activities in line with their leisure needs. This model effectively utilizes time, location, user, and activity as features to find the most possible “Consecutive Itinerary” and then recommend mobile users next locations and activities. In this preliminary study, although our approach achieved only about 30% top-1 inclusion rate, however, to our knowledge, this work is novel for the recommendation of location and activity based on consecutive itinerary discovery from check-in data.",

author = "Liu, {Jiun Shian} and Lu, {Wen Hsiang}",

note = "Publisher Copyright: {\textcopyright} ROCLING 2013.All rights reserved. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013 ; Conference date: 04-10-2013 Through 05-10-2013",

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language = "English",

series = "Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013",

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Liu, JS & Lu, WH 2013, Location and activity recommendation by using consecutive itinerary matching model. in Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013. Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013, The Association for Computational Linguistics and Chinese Language Processing (ACLCLP), pp. 288-301, 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013, Kaohsiung, Taiwan, 13-10-04.

Location and activity recommendation by using consecutive itinerary matching model. / Liu, Jiun Shian; Lu, Wen Hsiang.
Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP), 2013. p. 288-301 (Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Location and activity recommendation by using consecutive itinerary matching model

AU - Liu, Jiun Shian

AU - Lu, Wen Hsiang

PY - 2013/10/1

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N2 - In fact, most people have had the experience that they haven't made detailed itinerary in advance before a journey, and as a result they don't know what place or what kind of activity is suitable as the next visit location and activity after they engage in an activity in a certain place. To alleviate such problem, in this paper, we proposed the Consecutive Itinerary Matching Model to help mobile users find next locations and activities in line with their leisure needs. This model effectively utilizes time, location, user, and activity as features to find the most possible “Consecutive Itinerary” and then recommend mobile users next locations and activities. In this preliminary study, although our approach achieved only about 30% top-1 inclusion rate, however, to our knowledge, this work is novel for the recommendation of location and activity based on consecutive itinerary discovery from check-in data.

AB - In fact, most people have had the experience that they haven't made detailed itinerary in advance before a journey, and as a result they don't know what place or what kind of activity is suitable as the next visit location and activity after they engage in an activity in a certain place. To alleviate such problem, in this paper, we proposed the Consecutive Itinerary Matching Model to help mobile users find next locations and activities in line with their leisure needs. This model effectively utilizes time, location, user, and activity as features to find the most possible “Consecutive Itinerary” and then recommend mobile users next locations and activities. In this preliminary study, although our approach achieved only about 30% top-1 inclusion rate, however, to our knowledge, this work is novel for the recommendation of location and activity based on consecutive itinerary discovery from check-in data.

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BT - Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013

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Liu JS, Lu WH. Location and activity recommendation by using consecutive itinerary matching model. In Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP). 2013. p. 288-301. (Proceedings of the 25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013).

Location and activity recommendation by using consecutive itinerary matching model

Abstract

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Conference

All Science Journal Classification (ASJC) codes

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