Abstract: Disclosed is a method of correcting a response of an instrument. The method includes determining an inverse convolution function, the inverse convolution function being in the time domain. A response of an instrument to an exhaust sample is recorded as a function of time. The recorded response is then convolved with the inverse convolution function, the result being a convolution corrected instrument response.

Abstract: Disclosed is a method of correcting a response of an instrument. The method includes determining an inverse convolution function, the inverse convolution function being in the time domain. A response of an instrument to an exhaust sample is recorded as a function of time. The recorded response is then convolved with the inverse convolution function, the result being a convolution corrected instrument response.

Abstract: Disclosed is a method of correcting a response of an instrument. The method includes determining an inverse convolution function, the inverse convolution function being in the time domain. A response of an instrument to an exhaust sample is recorded as a function of time. The recorded response is then convolved with the inverse convolution function, the result being a convolution corrected instrument response.

Abstract: A computerized method and corresponding means for rating an item within a recommendation system. In a recommendation scheme, each of a multitude of users U and each of a multitude of items I is included in a profile P(U,I) that comprises ratings. Based on the similarity between a given user and the multitude of users in terms of the ratings, a subset of users is selected who have interest similar to those of the given user.

Abstract: A computerized method and corresponding means for rating an item within a recommendation system, that exploits additional external knowledge or the relationships between the ratable items to implicitly derive, from a first item rated explicitly by a certain user, implicit ratings for items related to the explicitly rated item. In response to a first explicit rating for a first item, the following steps are performed: determining, for the first item, a first set related items based on a predefined item relationship; storing, within the recommendation system, the first explicit rating of the first item; and storing, within the recommendation system, first implicit ratings for the first set of related items.

Abstract: A system for recommending items to a given user based on item recommendations of the given user and other users of the system, using general properties of users or items characterized by arbitrary property values as parameters of the recommendation process to improve recommendation quality.