Abstract: The subject disclosure is directed towards monitoring user behavior on a computerized device for any deviation from normal or acceptable behavior that is likely to affect the user's mental state. A prediction model corresponding to features of one or more mental states may be compared with features based upon current user behavior. If the user's current behavior presents a mental state indicative of an uncharacteristic deviation from the normal or acceptable behavior, descriptive data associated with that mental state may be presented to the user in addition to a trusted individual, such as a health care professional.

Abstract: The subject disclosure is directed towards monitoring user behavior on a computerized device for any deviation from normal or acceptable behavior that is likely to affect the user's mental state. A prediction model corresponding to features of one or more mental states may be compared with features based upon current user behavior. If the user's current behavior presents a mental state indicative of an uncharacteristic deviation from the normal or acceptable behavior, descriptive data associated with that mental state may be presented to the user in addition to a trusted individual, such as a health care professional.

Abstract: One embodiment accesses two or more photos taken by one or more travelers at one or more destinations and one or more points-of-interest located within the destinations; constructs one or more photo streams for each unique traveler-destination combination, wherein each one of the photo streams comprises two or more of the photos taken by the corresponding traveler at the corresponding destination; maps each one of the photos to one of the points-of-interest; constructs one or more timed paths for each unique traveler-destination combination based on the photo streams and the mapping between the photos and the points-of-interest, wherein each one of the timed paths comprises one or more of the points-of-interest located within the corresponding destination and visited by the corresponding travel; and constructs an itinerary based on a start point-of-interest, an end point-of-interest, a time constraint, and the timed paths.

Abstract: The subject disclosure is directed towards monitoring user behavior on a computerized device for any deviation from normal or acceptable behavior that is likely to affect the user's mental state. A prediction model corresponding to features of one or more mental states may be compared with features based upon current user behavior. If the user's current behavior presents a mental state indicative of an uncharacteristic deviation from the normal or acceptable behavior, descriptive data associated with that mental state may be presented to the user in addition to a trusted individual, such as a health care professional.

Abstract: Affective state classification embodiments are described which train and use a classifier to identify an affect exhibited by a segment of text. The affect being identified is chosen from a group of affects, each of which corresponds to a different emotion or sentiment being expressed by a person authoring the segment of text. In addition, each affect in the group of affects relates more than the valence of the emotion or sentiment being expressed. In other word, the identified affect is more than just an indication of the positive or negative nature of the text segment. Rather, in one embodiment, the classifier is trained to identify whether a segment of text exhibits one of the following affects: fear, sadness, guilt, hostility, joviality, self-assurance, attentiveness, shyness, fatigue, surprise, and serenity.

Abstract: One embodiment accesses two or more photos taken by one or more travelers at one or more destinations and one or more points-of-interest located within the destinations; constructs one or more photo streams for each unique traveler-destination combination, wherein each one of the photo streams comprises two or more of the photos taken by the corresponding traveler at the corresponding destination; maps each one of the photos to one of the points-of-interest; constructs one or more timed paths for each unique traveler-destination combination based on the photo streams and the mapping between the photos and the points-of-interest, wherein each one of the timed paths comprises one or more of the points-of-interest located within the corresponding destination and visited by the corresponding travel; and constructs an itinerary based on a start point-of-interest, an end point-of-interest, a time constraint, and the timed paths.

Abstract: The subject disclosure is directed towards a technology by which content items such as microblog postings may be returned to a requestor based upon a desired level of diversity based upon information entropy. Each content item is associated with a set of dimensions, which may have a learned relative importance, and the content items may be pruned into a pruned subset via a transform. A result set is constructed by finding a cluster of items having a level of entropy that is closest to a desired level. In one aspect, the result set may be ordered based upon evaluating distortion of each item in the result set.

Abstract: One embodiment accesses two or more photos taken by one or more travelers at one or more destinations and one or more points-of-interest located within the destinations; constructs one or more photo streams for each unique traveler-destination combination, wherein each one of the photo streams comprises two or more of the photos taken by the corresponding traveler at the corresponding destination; maps each one of the photos to one of the points-of-interest; constructs one or more timed paths for each unique traveler-destination combination based on the photo streams and the mapping between the photos and the points-of-interest, wherein each one of the timed paths comprises one or more of the points-of-interest located within the corresponding destination and visited by the corresponding travel; and constructs an itinerary based on a start point-of-interest, an end point-of-interest, a time constraint, and the timed paths.

Abstract: One embodiment accesses two or more photos taken by one or more travelers at one or more destinations and one or more points-of-interest located within the destinations; constructs one or more photo streams for each unique traveler-destination combination, wherein each one of the photo streams comprises two or more of the photos taken by the corresponding traveler at the corresponding destination; maps each one of the photos to one of the points-of-interest; constructs one or more timed paths for each unique traveler-destination combination based on the photo streams and the mapping between the photos and the points-of-interest, wherein each one of the timed paths comprises one or more of the points-of-interest located within the corresponding destination and visited by the corresponding travel; and constructs an itinerary based on a start point-of-interest, an end point-of-interest, a time constraint, and the timed paths.

Abstract: One embodiment accesses two or more photos taken by one or more travelers at one or more destinations and one or more points-of-interest located within the destinations; constructs one or more photo streams for each unique traveler-destination combination, wherein each one of the photo streams comprises two or more of the photos taken by the corresponding traveler at the corresponding destination; maps each one of the photos to one of the points-of-interest; constructs one or more timed paths for each unique traveler-destination combination based on the photo streams and the mapping between the photos and the points-of-interest, wherein each one of the timed paths comprises one or more of the points-of-interest located within the corresponding destination and visited by the corresponding travel; and constructs an itinerary based on a start point-of-interest, an end point-of-interest, a time constraint, and the timed paths.