Abstract: A method (1400) of and a system (222) for associating past activity indications (602) associated with past activities of a user (170) with items. The method comprises accessing (1402) the past activity indications (602); accessing (1404) item indications; determining (1406) a past activity feature vector (606); determining (1408) a text feature vector (706) corresponding to the text features; mapping (1410) the past activity feature vector (606) and the text feature vector (706) to generate a text feature space (904); determining (1412) an image feature vector (806); mapping (1414) the past activity feature vector (606) and the image feature vector (806) to generate an image feature space (1004); generating a user item space (1104); and storing (1418) the user item space (1104). A method (1500) of and a system (222) for associating a first item and a second item are also disclosed.

Abstract: A method of determining an income of a user of a mobile device, the method comprising: acquiring device data associated with the user of the mobile device; associating the user with a first occupational class, the first occupational class being associated with at least one event type and a first MLA; extracting a first dataset from the device data based on the first occupational class; applying a first logical analysis of the first MLA to the first dataset, the applying comprises: extracting from the first dataset a first data pattern being indicative of a first occupational event performed by the user, the first data pattern being associated with one of the at least one event types; and determining a first income value associated with the first occupational event based on the first data pattern, the first income value being representative of an income of the user of the mobile device.

Abstract: A method of determining an income of a user of a mobile device, the method comprising: acquiring device data associated with the user of the mobile device; associating the user with a first occupational class, the first occupational class being associated with at least one event type and a first MLA; extracting a first dataset from the device data based on the first occupational class; applying a first logical analysis of the first MLA to the first dataset, the applying comprises: extracting from the first dataset a first data pattern being indicative of a first occupational event performed by the user, the first data pattern being associated with one of the at least one event types; and determining a first income value associated with the first occupational event based on the first data pattern, the first income value being representative of an income of the user of the mobile device.

Abstract: A method for generating an entity-vector associated with a geographical location is disclosed. The entity-vector is generated based on data from sensors of user-wireless-devices and user profile associated with user-wireless-devices.

Abstract: A method (1400) of and a system (222) for associating past activity indications (602) associated with past activities of a user (170) with items. The method comprises accessing (1402) the past activity indications (602); accessing (1404) item indications; determining (1406) a past activity feature vector (606); determining (1408) a text feature vector (706) corresponding to the text features; mapping (1410) the past activity feature vector (606) and the text feature vector (706) to generate a text feature space (904); determining (1412) an image feature vector (806); mapping (1414) the past activity feature vector (606) and the image feature vector (806) to generate an image feature space (1004); generating a user item space (1104); and storing (1418) the user item space (1104). A method (1500) of and a system (222) for associating a first item and a second item are also disclosed.

Abstract: A method for generating an entity-vector associated with a geographical location is disclosed. The entity-vector is generated based on data from sensors of user-wireless-devices and user profile associated with user-wireless-devices.

Abstract: Computer-implemented method for estimating user interests, executable by a computing device in communication with an output device, comprising: determining a first input vector corresponding to a first user event and a second input vector corresponding to a second user event; mapping first input vector to a first output vector and second input vector to a second 5 output vector in a first multidimensional space using a first vector-mapping module; determining a third input vector based on first output vector and second output vector; mapping third input vector to a third output vector in a second multidimensional space using a second vector-mapping module; determining a message to be provided to a user based on an analysis of at least one of first output vector and third output vector; and causing output 10 device to provide message to user. Also non-transitory computer-readable medium storing program instructions for carrying out the method.

Abstract: Computer-implemented method for estimating user interests, executable by a computing device in communication with an output device, comprising: determining a first input vector corresponding to a first user event and a second input vector corresponding to a second user event; mapping first input vector to a first output vector and second input vector to a second 5 output vector in a first multidimensional space using a first vector-mapping module; determining a third input vector based on first output vector and second output vector; mapping third input vector to a third output vector in a second multidimensional space using a second vector-mapping module; determining a message to be provided to a user based on an analysis of at least one of first output vector and third output vector; and causing output 10 device to provide message to user. Also non-transitory computer-readable medium storing program instructions for carrying out the method.