Abstract-Specification mining methods are used to extract candidate specifications from system execution traces. A major challenge for specification mining is succinctness. That is, in addition to the soundness, completeness, and scalable performance of the specification mining method, one is interested in producing a succinct result, which conveys a lot of information about the system under investigation but uses a short, machine and humanreadable representation.In this paper we address the succinctness challenge in the context of scenario-based specification mining, whose target formalism is live sequence charts (LSC), an expressive extension of classical sequence diagrams. We do this by adapting three classical notions: a definition of an equivalence relation over LSCs, a definition of a redundancy and inclusion relation based on isomorphic embeddings among LSCs, and a deltadiscriminative measure based on an information gain metric on a sorted set of LSCs. These are applied on top of the commonly used statistical metrics of support and confidence.A number of case studies show the utility of our approach towards succinct mined specifications.