{
  "abstract": "Scheduled public transit constrains both when a traveler can reach a point of interest and whether enough time remains to visit it. We study the Keyword-Coverage Optimal Route Search on Temporal Transportation Networks problem, which returns the top-k distinct routes that maximize weighted keyword coverage subject to timetable, time-window, and budget constraints. We define keyword coverage using feasible point-of-interest visits and prove the problem NP-hard by a polynomial-time reduction from Budgeted Maximum Coverage. To solve the problem, we first filter trips and stations using temporal reachability and a time-dependent minimum-budget profile. We then develop an exact best-first search that uses the minimum-budget profile and an admissible keyword-coverage upper bound to prune route prefixes safely. For faster candidate generation, we propose a bounded greedy search that maintains a certified feasible continuation. Every route returned by this heuristic satisfies the query constraints, although it has no proven coverage approximation ratio and may return fewer than k routes. After finalizing the revised algorithms and dwell-time scoring rule, we reran the evaluation on the Austin and Houston transit networks. The main study contains 3600 runtime measurements, and a separate route-level study independently checks 22,775 A*/AP route records from 1260 queries. AP returns the requested k routes on 874 queries. On 240 tractable queries with a positive exact reference, its mean best-score ratio relative to A* is 0.94, and it matches the exact best score on 224 queries. A* also matches the complete ordered top-k output of exhaustive enumeration on all 20 small instances.",
  "abstract_shown": true,
  "affiliations": [
    "School of Information Engineering, Henan University of Science and Technology, Luoyang 471023, China"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Youming Ge"
    },
    {
      "affs": [
        0
      ],
      "name": "Zhihang Ji",
      "orcid": "0000-0002-3143-1677"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/42sgjqcfd4tpw.bib",
  "cited_by": 0,
  "doi": "10.3390/math14213927",
  "fulltext_url": null,
  "id": "42sgjqcfd4tpw",
  "issns": [
    "2227-7390"
  ],
  "landing_url": "https://www.mdpi.com/2227-7390/14/21/3927",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "3313|Transportation Planning and Optimization"
    ]
  ],
  "openalex": "W7223846692",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-27",
  "publisher": "MDPI AG",
  "ris": "https://research.draconitic.com/paper/42sgjqcfd4tpw.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:29Z",
      "native_id": "10.3390/math14213927",
      "source": "crossref",
      "url": "https://www.mdpi.com/2227-7390/14/21/3927"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "issn:2227-7390",
      "subfield": "general"
    }
  ],
  "title": "Keyword-Coverage Optimal Route Search on Temporal Transportation Networks",
  "title_text": "Keyword-Coverage Optimal Route Search on Temporal Transportation Networks",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:29Z",
  "url": "https://research.draconitic.com/paper/42sgjqcfd4tpw",
  "venue": "Mathematics",
  "versions": []
}