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Efficient Reasoning Algorithms for Fragments of Horn Description Logics

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2017, Doctor of Philosophy (PhD), Wright State University, Computer Science and Engineering PhD.
We characterize two fragments of Horn Description Logics and we define two specialized reasoning algorithms that effectively solve the standard reasoning tasks over each of such fragments. We believe our work to be of general interest since (1) a rather large proportion of real-world Horn ontologies belong to some of these two fragments and (2) the implementations based on our reasoning approach significantly outperform state-of-the-art reasoners. Claims (1) and (2) are extensively proven via empirically evaluation.
Pascal Hitzler, Ph.D. (Advisor)
Bernardo Cuenca Grau, Ph.D. (Committee Member)
Krishnaprasad Thirunarayan, Ph.D. (Committee Member)
MIchael Raymer, Ph.D. (Committee Member)
70 p.

Recommended Citations

Citations

  • Carral, D. (2017). Efficient Reasoning Algorithms for Fragments of Horn Description Logics [Doctoral dissertation, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1491317096530938

    APA Style (7th edition)

  • Carral, David. Efficient Reasoning Algorithms for Fragments of Horn Description Logics. 2017. Wright State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1491317096530938.

    MLA Style (8th edition)

  • Carral, David. "Efficient Reasoning Algorithms for Fragments of Horn Description Logics." Doctoral dissertation, Wright State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1491317096530938

    Chicago Manual of Style (17th edition)