i am currently working on my thesis in information processing in the humanities.
i am developping an extension for lucene, that integrates the user�s query history into the retrieval process.
i want to implement a neural network, that adapts to the users information need.
first, the application performs a full-text search on a metadata corpus.
q1: how can i modify the format of lucenes output, for example, adding the ranking value.
the user then selects the apparently most interesting documents (by it dc metadata). this second user-input should be used to adapt the neural network weights.
q2: is it possible to
a: reuse / generate a lucene term-document-matrix and
b: initialize the synapses of a nn with that matrix
c: does lucene provide any interface at that level of the information extraction process
until now, i am not entirely decided which neural network api i should use. joone, at a first glance, seems to be quite user friendly but integrate it into one�s own applications doesn�t, so that a more "customizeable" solution is needed.
thank you for any hint!
thomas kr�mer university of cologne, germany
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