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In particular, we have described a framework in which time series dimensional-
ity is reduced by means of TA. The framework supports multi-level abstractions,
both along the time dimension, and along a symbol taxonomy one, thus increas-
ing the flexibility of retrieval. Query answering is interactive and is made faster
by the use of orthogonal index structures, which can grow on demand.
In our opinion, flexibility and interactivity represent a relevant advantage of
our approach to time series retrieval with respect to more classical techniques,
in which end users are typically unable to intervene in the retrieval process, that
often operates in a black-box fashion.
In the future, we plan to further test our framework in several different ap-
plication domains, thus validating its significance, and studying ways of making
it more and more ecient and usable.
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