Tractable Responsibility Measures for Ontology-Mediated Query Answering
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866913967416279040 |
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| author | Bienvenu, Meghyn Figueira, Diego Lafourcade, Pierre |
| author_facet | Bienvenu, Meghyn Figueira, Diego Lafourcade, Pierre |
| contents | Recent work on quantitative approaches to explaining query answers employs responsibility measures to assign scores to facts in order to quantify their respective contributions to obtaining a given answer. In this paper, we study the complexity of computing such responsibility scores in the setting of ontology-mediated query answering, focusing on a very recently introduced family of Shapley-value-based responsibility measures defined in terms of weighted sums of minimal supports (WSMS). By exploiting results from the database setting, we can show that such measures enjoy polynomial data complexity for classes of ontology-mediated queries that are first-order-rewritable, whereas the problem becomes "shP"-hard when the ontology language can encode reachability queries (via axioms like $\exists R. A \sqsubseteq A$). To better understand the tractability frontier, we next explore the combined complexity of WSMS computation. We prove that intractability applies already to atomic queries if the ontology language supports conjunction, as well as to unions of `well-behaved' conjunctive queries, even in the absence of an ontology. By contrast, our study yields positive results for common DL-Lite dialects: by means of careful analysis, we identify classes of structurally restricted conjunctive queries (which intuitively disallow undesirable interactions between query atoms) that admit tractable WSMS computation. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2507_23191 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Tractable Responsibility Measures for Ontology-Mediated Query Answering Bienvenu, Meghyn Figueira, Diego Lafourcade, Pierre Artificial Intelligence Recent work on quantitative approaches to explaining query answers employs responsibility measures to assign scores to facts in order to quantify their respective contributions to obtaining a given answer. In this paper, we study the complexity of computing such responsibility scores in the setting of ontology-mediated query answering, focusing on a very recently introduced family of Shapley-value-based responsibility measures defined in terms of weighted sums of minimal supports (WSMS). By exploiting results from the database setting, we can show that such measures enjoy polynomial data complexity for classes of ontology-mediated queries that are first-order-rewritable, whereas the problem becomes "shP"-hard when the ontology language can encode reachability queries (via axioms like $\exists R. A \sqsubseteq A$). To better understand the tractability frontier, we next explore the combined complexity of WSMS computation. We prove that intractability applies already to atomic queries if the ontology language supports conjunction, as well as to unions of `well-behaved' conjunctive queries, even in the absence of an ontology. By contrast, our study yields positive results for common DL-Lite dialects: by means of careful analysis, we identify classes of structurally restricted conjunctive queries (which intuitively disallow undesirable interactions between query atoms) that admit tractable WSMS computation. |
| title | Tractable Responsibility Measures for Ontology-Mediated Query Answering |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2507.23191 |