Abstract: A machine learning system and method for estimating real estate property sales prices by combining property attributes, contextual attributes, and crowdsourced user estimates in a closed-loop learning system. The system learns numeric representations for properties and users, and employs a modified weighting mechanism that incorporates property information into the value computation, enabling property-specific adjustment of user estimates based on learned user biases. Unlike standard weighting mechanisms that compute values solely from input source representations, the modified mechanism computes values from a combination of user representations, user price estimates, and property representations, enabling context-dependent corrections through a multi-layer transformation.

Abstract: A method, for use in a user computer system including a pointing device and a visual display unit, for providing a graphical user interface to a computer program for electronic discovery of information, wherein the information is stored in a database, and wherein the information has been preprocessed using social network analysis to find social network relationships between items of the information, and wherein topics are determined using distributed Latent Dirichlet Allocation (LDA)