Systems and methods for determining semantically related terms using an active learning framework such as Transductive Experimental Design are disclosed. Generally, to enhance a keyword suggestion tool, an active learning module trains a model to predict whether a term is relevant to a user. The model is then used to present the user with terms that have been determined to be relevant based on the model so that an online advertisement service provider may more efficiently provide a user with terms that are semantically related to a seed set.

 
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< Voice to text conversion with keyword parse and match to semantic and transactional concepts stored in a brain pool state machine using word distance to generate character model interaction in a plurality of dramatic modes

< Use of sequential nearest neighbor clustering for instance selection in machine condition monitoring

> Automatic invocation of computational resources without user intervention across a network

> Memory assistance system comprising of a signal processing server receiving a media signal and associated data relating to information to be remembered and processing the input signal to identify media characteristics relevant to aiding user memory
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