{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T17:08:08Z","timestamp":1769188088894,"version":"3.49.0"},"reference-count":37,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2022,6,10]],"date-time":"2022-06-10T00:00:00Z","timestamp":1654819200000},"content-version":"vor","delay-in-days":160,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2022,1]]},"abstract":"<jats:p>\n                    In this paper, we study the path based continuous spatial keyword queries, which find the answer set continuously when the query point moves on a given path. Under this setting, we explore two primitive spatial keyword queries, namely\n                    <jats:italic>k<\/jats:italic>\n                    nearest neighbor query and range query. The technical challenges lie in that: (1) retrieving qualified vertices in large road networks efficiently, and (2) issuing the query continuously for points on the path, which turns out to be inapplicable. To overcome the above challenges, we first propose a backbone road network index structure (BNI), which supports the distance computation efficiently and offers a global insights of the whole road network. Motivated by the safe zone technique, we then transform our queries to the issue of finding event points, which capture the changes of answer set. By this transformation, our queries are to be simple and feasible. To answer the queries, we propose a Two\u2010Phase Progressive (TPP) computing framework, which first computes the answer sets for some crucial vertices on the path, and then identifies the event points by the retrieved answer sets. Extensive experiments on both real and synthetic data sets are conducted to evaluate the performance of our proposed algorithms, and the results show that our algorithms outperform competitors by several orders of magnitude.\n                  <\/jats:p>","DOI":"10.1155\/2022\/4091245","type":"journal-article","created":{"date-parts":[[2022,6,10]],"date-time":"2022-06-10T14:05:41Z","timestamp":1654869941000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Path\u2013Based Continuous Spatial Keyword Queries"],"prefix":"10.1155","volume":"2022","author":[{"given":"Fangshu","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengfei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9486-1247","authenticated-orcid":false,"given":"Chengcheng","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huaizhong","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shan","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoming","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,6,10]]},"reference":[{"key":"e_1_2_12_1_2","doi-asserted-by":"publisher","DOI":"10.14778\/2735471.2735473"},{"key":"e_1_2_12_2_2","doi-asserted-by":"crossref","unstructured":"MouratidisK. PapadiasD. andHadjieleftheriouM. Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring Proceedings of the 2005 ACM SIGMOD international conference on Management of data June 2005 Baltimore MD USA ACM 634\u2013645.","DOI":"10.1145\/1066157.1066230"},{"key":"e_1_2_12_3_2","unstructured":"MouratidisK. YiuM. L. PapadiasD. andMamoulisN. Continuous nearest neighbor monitoring in road networks 43\u201354 Proceedings of the 32nd international conference on Very large data bases September 2006 Seoul Korea VLDB Endowment."},{"key":"e_1_2_12_4_2","doi-asserted-by":"publisher","DOI":"10.14778\/1453856.1453973"},{"key":"e_1_2_12_5_2","doi-asserted-by":"crossref","unstructured":"WuY. JinR. andZhangX. 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