Keyword-aware optimal route search
Identifying a preferable route is an important problem that finds applications in map services. When a user plans a trip within a city, the user may want to find "a most popular route such that it passes by shopping mall, restaurant, and pub, and the travel time to and from his hotel is within...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2014
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/102238 http://hdl.handle.net/10220/18930 http://dl.acm.org.ezlibproxy1.ntu.edu.sg/citation.cfm?id=2350234&dl=ACM&coll=DL |
| _version_ | 1826120352765313024 |
|---|---|
| author | Cao, Xin Chen, Lisi Cong, Gao Xiao, Xiaokui |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Cao, Xin Chen, Lisi Cong, Gao Xiao, Xiaokui |
| author_sort | Cao, Xin |
| collection | NTU |
| description | Identifying a preferable route is an important problem that finds applications in map services. When a user plans a trip within a city, the user may want to find "a most popular route such that it passes by shopping mall, restaurant, and pub, and the travel time to and from his hotel is within 4 hours." However, none of the algorithms in the existing work on route planning can be used to answer such queries. Motivated by this, we define the problem of keyword-aware optimal route query, denoted by KOR, which is to find an optimal route such that it covers a set of user-specified keywords, a specified budget constraint is satisfied, and an objective score of the route is optimal. The problem of answering KOR queries is NP-hard. We devise an approximation algorithm OSScaling with provable approximation bounds. Based on this algorithm, another more efficient approximation algorithm BucketBound is proposed. We also design a greedy approximation algorithm. Results of empirical studies show that all the proposed algorithms are capable of answering KOR queries efficiently, while the BucketBound and Greedy algorithms run faster. The empirical studies also offer insight into the accuracy of the proposed algorithms. |
| first_indexed | 2024-10-01T05:14:47Z |
| format | Journal Article |
| id | ntu-10356/102238 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:14:47Z |
| publishDate | 2014 |
| record_format | dspace |
| spelling | ntu-10356/1022382020-05-28T07:18:03Z Keyword-aware optimal route search Cao, Xin Chen, Lisi Cong, Gao Xiao, Xiaokui School of Computer Engineering Computer Science Engineering Identifying a preferable route is an important problem that finds applications in map services. When a user plans a trip within a city, the user may want to find "a most popular route such that it passes by shopping mall, restaurant, and pub, and the travel time to and from his hotel is within 4 hours." However, none of the algorithms in the existing work on route planning can be used to answer such queries. Motivated by this, we define the problem of keyword-aware optimal route query, denoted by KOR, which is to find an optimal route such that it covers a set of user-specified keywords, a specified budget constraint is satisfied, and an objective score of the route is optimal. The problem of answering KOR queries is NP-hard. We devise an approximation algorithm OSScaling with provable approximation bounds. Based on this algorithm, another more efficient approximation algorithm BucketBound is proposed. We also design a greedy approximation algorithm. Results of empirical studies show that all the proposed algorithms are capable of answering KOR queries efficiently, while the BucketBound and Greedy algorithms run faster. The empirical studies also offer insight into the accuracy of the proposed algorithms. 2014-03-20T09:03:23Z 2019-12-06T20:52:06Z 2014-03-20T09:03:23Z 2019-12-06T20:52:06Z 2012 2012 Journal Article Cao, X., Chen, L., Cong, G., & Xiao, X. (2012). Keyword-aware optimal route search. Proceedings of the VLDB Endowment, 5(11), 1136-1147. https://hdl.handle.net/10356/102238 http://hdl.handle.net/10220/18930 http://dl.acm.org.ezlibproxy1.ntu.edu.sg/citation.cfm?id=2350234&dl=ACM&coll=DL en Proceedings of the VLDB Endowment © 2012 VLDB endowment. |
| spellingShingle | Computer Science Engineering Cao, Xin Chen, Lisi Cong, Gao Xiao, Xiaokui Keyword-aware optimal route search |
| title | Keyword-aware optimal route search |
| title_full | Keyword-aware optimal route search |
| title_fullStr | Keyword-aware optimal route search |
| title_full_unstemmed | Keyword-aware optimal route search |
| title_short | Keyword-aware optimal route search |
| title_sort | keyword aware optimal route search |
| topic | Computer Science Engineering |
| url | https://hdl.handle.net/10356/102238 http://hdl.handle.net/10220/18930 http://dl.acm.org.ezlibproxy1.ntu.edu.sg/citation.cfm?id=2350234&dl=ACM&coll=DL |
| work_keys_str_mv | AT caoxin keywordawareoptimalroutesearch AT chenlisi keywordawareoptimalroutesearch AT conggao keywordawareoptimalroutesearch AT xiaoxiaokui keywordawareoptimalroutesearch |