Abstract: A system and method are disclosed for user preference augmentation through social network inner-circle knowledge discovery. A user's activity may be captured allow a user preference model to be created. The user preference model is compared to other models in the user's social network. A inner-circle social network is created, and the user preference model is augmented based on other preference models in the inner-circle social network, and the user's own preference for certain categories of information element. Information elements can be provided to the user based on suggestions and the user's preference model. The information elements may be organized such that the more relevant information elements are more easily accessible to the user.

Abstract: A method in a document analysis system automatically extracts from each received electronic document image and text features, in which the image features are indicative of how the document is laid out or textually-organized and therefore indicative of a corresponding document category, next compares the extracted image and text features with feature sets associated with each document category, and then classifies each document to a document category, the feature set of which best matches the extracted features of the document.

Abstract: An improved method for detecting truth or deceit (15) comprising providing a video camera (18) adapted to record images of a subject's (16) face, recording images of the subject's face, providing a mathematical model (62) of a face defined by a set of facial feature locations and textures, providing a mathematical model of facial behaviors (78, 82, 98, 104) that correlate to truth or deceit, comparing (64) the facial feature locations to the image (29) to provide a set of matched facial feature locations (70), comparing (77, 90, 94, 100) the mathematical model of facial behaviors to the matched facial feature locations, and providing a deceit indication as a function of the comparison (78, 91, 95, 101 or 23).

Abstract: Provided is a non-invasive method for identification of non-physiological, physiological or diseased states based on the volatiles in gas or biogas samples from individuals. The method uses a sensor array comprising a plurality of distinct sensors which differ from other sensors by the sensing molecules or the sol-gel holding material composition. In response to a combination of volatiles, a pattern of responses is generated which can be correlated to particular non-physiological, physiological or diseased state.

Abstract: A system for recognizing handwritten words of cursive script by extracting temporal information from static text is described. The temporal information consists of the shape, location and temporal sequence of the segments, or "primitives", constituting the word and is translated from bit maps images of the words into digital information format. By comparing the digital information with formatted digital information for a plurality of known words, as may be stored in computer memory, a list of words having a relatively high probability of matching the static text is generated, and used for word recognition by a process of selecting the most likely match.