Borchert

James Borchert, Vancouver CA

Patent application number	Description	Published
20110021663	LIGHT WEIGHT AGGREGATE COMPOSITION - An expanded material suitable for industrial application may have a nominal tap density from 0.18 grams/cc to 1.00 grams/cc and a wall thickness greater than 1.00 microns. The expanded material may take the form of an expanded silicate, for instance perlite, obsidian, pitchstone or vermiculite. A composition may include the expanded material in a dispersion, for example a resin dispersion, for instance a latex acrylic. Such may be particularly suitable as a partial or complete substitute for another aggregate used in the composition, such as sand. The composition may be suitable in structural applications, for example as an EIFS coat. The expanded material may, or may not, include a partial or complete hydrophobic coating.	01-27-2011

Patent application number	Description	Published
20100262568	Scalable Clustering - A scalable clustering system is described. In an embodiment the clustering system is operable for extremely large scale applications where millions of items having tens of millions of features are clustered. In an embodiment the clustering system uses a probabilistic cluster model which models uncertainty in the data set where the data set may be for example, advertisements which are subscribed to keywords, text documents containing text keywords, images having associated features or other items. In an embodiment the clustering system is used to generate additional features for associating with a given item. For example, additional keywords are suggested which an advertiser may like to subscribe to. The additional features that are generated have associated probability values which may be used to rank those features in some embodiments. User feedback about the generated features is received and used to revise the feature generation process in some examples.	10-14-2010

Patent application number	Description	Published
20110184778	Event Prediction in Dynamic Environments - Event prediction in dynamic environments is described. In an embodiment a prediction engine may use the learnt information to predict events in order to control a system such as for internet advertising, email filtering, fraud detection or other applications. In an example one or more variables exists for pre-specified features describing or associated with events and each variable is considered to have an associated weight and time stamp. For example, belief about each weight is represented using a probability distribution and a dynamics process is used to modify the probability distribution in a manner dependent on the time stamp for that weight. For example, the uncertainty about the associated variable's influence on prediction of future events is increased. Examples of different schedules for applying the dynamics process are given.	07-28-2011