MeTeoR: practical reasoning in datalog with metric temporal operators
DatalogMTL is an extension of Datalog with operators from metric temporal logic which has received significant attention in recent years. It is a highly expressive knowledge representation language that is well-suited for applications in temporal ontology-based query answering and stream processing....
| 主要な著者: | , , , |
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| フォーマット: | Conference item |
| 言語: | English |
| 出版事項: |
Association for the Advancement of Artificial Intelligence
2022
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| _version_ | 1826310937153372160 |
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| author | Wang, D Hu, P Walega, P Cuenca Grau, B |
| author_facet | Wang, D Hu, P Walega, P Cuenca Grau, B |
| author_sort | Wang, D |
| collection | OXFORD |
| description | DatalogMTL is an extension of Datalog with operators from metric temporal logic which has received significant attention in recent years. It is a highly expressive knowledge representation language that is well-suited for applications in temporal ontology-based query answering and stream processing. Reasoning in DatalogMTL is, however, of high computational complexity, making implementation challenging and hindering its adoption in applications. In this paper, we present a novel approach for practical reasoning in DatalogMTL which combines materialisation (a.k.a. forward chaining) with automata-based techniques. We have implemented this approach in a reasoner called MeTeoR and evaluated its performance using a temporal extension of the Lehigh University Benchmark and a benchmark based on real-world meteorological data. Our experiments show that MeTeoR is a scalable system which enables reasoning over complex temporal rules and datasets involving tens of millions of temporal facts. |
| first_indexed | 2024-03-07T07:59:26Z |
| format | Conference item |
| id | oxford-uuid:bae8f48d-0cd5-45c5-80f9-a4a2f45bb81b |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:59:26Z |
| publishDate | 2022 |
| publisher | Association for the Advancement of Artificial Intelligence |
| record_format | dspace |
| spelling | oxford-uuid:bae8f48d-0cd5-45c5-80f9-a4a2f45bb81b2023-09-15T12:33:43ZMeTeoR: practical reasoning in datalog with metric temporal operatorsConference itemhttp://purl.org/coar/resource_type/c_5794uuid:bae8f48d-0cd5-45c5-80f9-a4a2f45bb81bEnglishSymplectic ElementsAssociation for the Advancement of Artificial Intelligence2022Wang, DHu, PWalega, PCuenca Grau, BDatalogMTL is an extension of Datalog with operators from metric temporal logic which has received significant attention in recent years. It is a highly expressive knowledge representation language that is well-suited for applications in temporal ontology-based query answering and stream processing. Reasoning in DatalogMTL is, however, of high computational complexity, making implementation challenging and hindering its adoption in applications. In this paper, we present a novel approach for practical reasoning in DatalogMTL which combines materialisation (a.k.a. forward chaining) with automata-based techniques. We have implemented this approach in a reasoner called MeTeoR and evaluated its performance using a temporal extension of the Lehigh University Benchmark and a benchmark based on real-world meteorological data. Our experiments show that MeTeoR is a scalable system which enables reasoning over complex temporal rules and datasets involving tens of millions of temporal facts. |
| spellingShingle | Wang, D Hu, P Walega, P Cuenca Grau, B MeTeoR: practical reasoning in datalog with metric temporal operators |
| title | MeTeoR: practical reasoning in datalog with metric temporal operators |
| title_full | MeTeoR: practical reasoning in datalog with metric temporal operators |
| title_fullStr | MeTeoR: practical reasoning in datalog with metric temporal operators |
| title_full_unstemmed | MeTeoR: practical reasoning in datalog with metric temporal operators |
| title_short | MeTeoR: practical reasoning in datalog with metric temporal operators |
| title_sort | meteor practical reasoning in datalog with metric temporal operators |
| work_keys_str_mv | AT wangd meteorpracticalreasoningindatalogwithmetrictemporaloperators AT hup meteorpracticalreasoningindatalogwithmetrictemporaloperators AT walegap meteorpracticalreasoningindatalogwithmetrictemporaloperators AT cuencagraub meteorpracticalreasoningindatalogwithmetrictemporaloperators |