نتایج جستجو برای: inferencing
تعداد نتایج: 988 فیلتر نتایج به سال:
Childlessness among married couples is a rising problem in India. One of the major factors of childlessness is due to being infertile of either one or both of wife or husband. Infertility refers to the failure of a couple to become pregnant after one year of regular unprotected sexual intercourse. Infertility is a life crisis with invisible losses, and its consequences are manifold. This paper ...
Ontologies now play an important role for many knowledge-intensive applications for which they provide a source of precisely defined terms. The terms are used for concise communication across people and applications. OntoEdit is an ontology editor that has been developed keeping five main objectives in mind: 1. Ease of use. 2. Methodology-guided development of ontologies. 3. Ontology developmen...
The problem of deciding what is implied by a written text. of “reading between the lines” is the problem of text Inference. To extract proper inferences from a text requires a great deal of generol knowledge on the port of the reader. Past approaches have often used a “strong method” tuned to process a particular kind of knowledge structure (such OS a script, or a plan). The alternative is a “w...
People-centric sensor-based applications targeting mobile device users offer enormous potential. However, learning inference models in this setting is hampered by the lack of labeled training data and appropriate feature inputs. Data features that lead to better classification models are not available at all devices due to device heterogeneity. Even for devices that provide superior data featur...
This paper describes a new framework for using natural selection to evolve Bayesian Networks for use in forecasting time series data. It extends current research by introducing a tree based representation of a candidate Bayesian Network that addresses the problem of model identification and training through the use of natural selection. The framework constructs a modified Naïve Bayesian classif...
Anytime algorithms have demonstrated their usefulness in solving many classes of intractable and NPhard problems. This approach allows the potential for improvement in the quality of the solution to be balanced against the cost of generating that improvement, both in time and system resources. While significant work has been accomplished on characterizing individual algorithms and sequences of ...
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