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\section{Introduction}  Twitter, Cohen: Bio aproximative matching. Abu: Relaxed matching.  Use data from SEMEVAL 2014 for sentence semantic relatedness. Dependency Depandency  parsing based links as Walsh codes, capture relation between words expressed by a vector (word2vec). Unified search from RDF Graphs and unstructured text. Use iconic environment (m3data or Simulink). Study deeplearning4J twitter application. To draw dependency graphs: DependenSee A Dependency Parse Visualisation Tool that makes pictures of Stanford Dependency output. By Awais Athar. (http://nlp.stanford.edu/software/lex-parser.shtml#Sample). Form a document signal by concatenate sentences associated signals. A dependancy graph link source is encoded by a Walsh code and the destination by the code obtained by a rotation with -90 degree. Question-Answering as a decoding-encoding problem or filter(docs)/Fourier(search). Apply at multimedia annotation or unified searching, encryption and watermarking. Jive search with relations represented as database tabels in M3Data \cite{Campbell_2014}, community detection, leadership... implemented as M3Data big data (AROM) by Apache Crunch on top of Spark with collaborative interface by NoFlo