Natural-language understanding NLU or natural-language interpretation NLI  is a subtopic of natural-language processing in artificial intelligence that deals with machine reading comprehension. Natural-language understanding is considered an AI-hard problem. There is considerable commercial interest in the field because of its application to automated reasoning ,  machine translation ,  question answering ,  news-gathering, text categorization , voice-activation , archiving, and large-scale content analysis. ELIZA worked by simple parsing and substitution of key words into canned phrases and Weizenbaum sidestepped the problem of giving the program a database of real-world knowledge or a rich lexicon. Yet ELIZA gained surprising popularity as a toy project and can be seen as a very early precursor to current commercial systems such as those used by Ask. In Roger Schank at Stanford University introduced the conceptual dependency theory for natural-language understanding.
Feature Extraction Techniques for Face Recognition
Deep Learning Feature Extraction for Image Processing - iCoSys
Shirui Pan is a Senior Lecturer equiv. Shirui received his Ph. D degree in computer science from UTS, Australia. His research interests include data mining and machine learning, specialized in graph mining and network analysis.
Aloha, I am currently the CEO of you. Previously, I was the chief scientist EVP at Salesforce where I lead teams working on fundamental research , applied research, product incubation, CRM search, customer service automation and a cross-product AI platform for unstructured and structured data. I like paramotor adventures, traveling and photography.
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