  Proof by induction plays a critical role in formal verification and
mathematics at large. However, its automation remains as one of the
long-standing challenges in Computer Science. To address this problem, we
developed sem_ind. Given inductive problem, sem_ind recommends what arguments
to pass to the induct method. To improve the accuracy of sem_ind, we introduced
definitional quantifiers, a new kind of quantifiers that allow us to
investigate not only the syntactic structures of inductive problems but also
the definitions of relevant constants in a domain-agnostic style. Our
evaluation shows that compared to its predecessor sem_ind improves the accuracy
of recommendation from 20.1% to 38.2% for the most promising candidates within
5.0 seconds of timeout while decreasing the median value of execution time from
2.79 seconds to 1.06 seconds.
