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Non-disjoint groupping of Documents based on word sequence approach
This is a GUI for learning non disjoint groups of documents based on Weka machine learning framework. It offers the possibility to make non disjoint
clustering of documents using both vectorial and sequential representation (word sequence approach based on WSK kernel). All data format supported
by WEKA could be used in DocCO. Data could be loaded from files, from
databases or from specified URL. All the preprocessing techniques implemented in
WEKA could be used before performing the learning.
This article talks about how to create a chatterbot that can serve as an interactive help agent. The bot has been "taught" to answer FAQs about a system. It can help solve petty issues for users quickly or point them to a human agent.
CAMA (Context-Aware Mobile Agents) is a middleware for supporting mobile agents coordination. It is based on Linda-style coordination and provides numerous extentions for interoperability and fault-tolerance. It supports portable platforms such as PDAs.
Robot Controlling System (RCS) - is a .NET-oriented software group for controlling remote mechanical objects, debuging and programming them by .NET-languages
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*** This page is no longer used by the Dasher project - please see http://www.inference.phy.cam.ac.uk/dasher/ *** Dasher is a data entry interface incorporating language modelling and driven by continuous two-dimensional gestures, e.g. a mouse, a stylus
3A-TRE evaluates traditionally logical expressions under 3 assumptions
3A-TRE evaluates traditionally logical expressions under the three assumptions. The open world assumption (OWA) states that the truth value of a statement that is not included in or inferred from the knowledge explicitly recorded in the system shall be considered unknown. The closed world assumption (CWA) is the assumption that any statement that is not known to be true is false. We distinguish yet another case in software testing. Frequently, there are test stubs which simulate the...