CPS need rigorous verification;Agenda-based computation for semantic inference via MDP and RL.

We propose a multi-model ensemble learning architecture for semantic code search.It combines several individual learners, each of which emphasizes a specific perspective of code snippets.

Semantic technologies gained influence; propose semantic correlation rules as interface for content management, modeling and delivery.

BR's contain large categories making analysis difficult. We present approach giving complete SBVR BR's based on query integrating text search and SMT approach capturing logic.

We study semantic clone detection in logic programs.We use anti-unification to control the search and guide detection of cloned predicates.

Establishing semantic similarity of information is integral.DL- based similarity approach, model and measure classification define and match the conceptual level.

Semantic types add metadata;existing methods find limited types inaccurately.We developed AUTOTYPE to identify types;it found more web table types.

In this work, a POMDP based decision making module is integrated with a semantic mapping system to enable efficient search for objects in domestic environments.

SP-NLG proposes a semantic-parsing-guided natural language generation framework for logical content generation. It adopts a coarse-to-fine generation scheme with a slot-tied back-search algorithm ,ensuring logical correctness.

Probabilistic logic handles inaccurate terms better; query performance depends on worst terms in a query.