Titlebook: Inductive Logic Programming; 20th International C Paolo Frasconi,Francesca A. Lisi Conference proceedings 2011 The Editor(s) (if applicable

Matrimony

皮薩

Extending ProbLog with Continuous Distributionscify continuous distributions and that we show how ProbLog’s exact inference mechanism can be modified to cope with such distributions. The resulting inference engine combines an interval calculus with a dynamic discretization algorithm into an effective solver.

Cholecystokinin

Multivariate Prediction for Learning on the Semantic Webe entities and almost nothing might be known for others. A popular example is the well known friend-of-a-friend data set where some members document exhaustive private and social information whereas, for privacy concerns and other reasons, almost nothing is known for other members. Although deductiv

Engulf

induct

致詞

BET : An Inductive Logic Programming Workbenchformat for the input data. This makes it very tedious and time consuming on the part of a user to utilize such a system for experimental purposes as it demands a thorough understanding of that system and its input specification. In the spirit of Weka [1], we present a relational learning workbench c

CANT

劇本

輪流

Variation of Background Knowledge in an Industrial Application of ILPtworks. In the present paper we describe two new applications of this type in the area of plant biology. These applications are of particular interest to the agrochemical industry in which improvements in plant strains can have benefits for modelling crop development. The background knowledge in the

Bridle

d other users, allowing sharees also to perform searches. We introduce the concept of a ., an extension of Multi-Key Searchable Encryption (NSDI ’14), that supports dynamic sharing and unsharing of documents amongst users. We also strengthen the security notion by considering a simulation-based noti