Bayesian Description Logics
نویسندگان
چکیده
We present Bayesian Description Logics (BDLs): an extension of Description Logics (DLs) with contextual probabilities encoded in a Bayesian network (BN). Classical DL reasoning tasks are extended to consider also the contextual and probabilistic information in BDLs. A complexity analysis of these problems shows that, for propositionally closed DLs, this extension comes without cost, while for tractable DLs the complexity is affected by the cost of reasoning in the BN.
منابع مشابه
Tractable Reasoning with Bayesian Description Logics
The DL-Lite family of tractable description logics lies between the semantic web languages RDFS and OWL Lite. In this paper, we present a probabilistic generalization of the DL-Lite description logics, which is based on Bayesian networks. As an important feature, the new probabilistic description logics allow for flexibly combining terminological and assertional pieces of probabilistic knowledg...
متن کاملQuery Answering in Bayesian Description Logics
The Bayesian Description Logic (BDL) BEL is a probabilistic DL, which extends the lightweight DL EL by defining a joint probability distribution over EL axioms with the help of a Bayesian network (BN). In the recent work, extensions of standard logical reasoning tasks in BEL are shown to be reducible to inferences in BNs. This work concentrates on a more general reasoning task, namely on conjun...
متن کاملMarket Analysis Using a Combination of Bayesian Networks and Description Logics
The work described in this paper was inspired by a problem increasingly vexatious to many businesses confronting the ever-diminishing life cycles of modern products—viz., that of predicting characteristics (such as overall demand, segmentation, etc.) of markets facing new product introductions. A framework is proposed that allows the market parameters of new products to be derived by analogy wi...
متن کاملDynamic Bayesian Description Logics
It is well known that many artificial intelligence applications need to represent and reason with knowledge that is not fully certain. This has motivated the study of many knowledge representation formalisms that can effectively handle uncertainty, and in particular probabilistic description logics (DLs) [7–9]. Although these logics are encompassed under the same umbrella, they differ greatly i...
متن کاملSemantic Query Extension through Probabilistic Description Logics
This paper presents a novel approach for semantic query extension using a probabilistic description logic. Concepts that are related to a keyword-based query are used for finding other concepts and relations through the use of a relational Bayesian network built using the probabilistic description logic crALC. Furthermore, probabilistic assessments allow us to rank the information returned by s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014