Abstract: Disclosed is an online system that infers interests of unresolved users for whom the interests are not known. The online system determines certain features about the unresolved users, but does not have certain information about the users themselves (e.g., their interests), so instead infers these attributes based on the features of the user. The online system provides the features as input to a classifier trained to predict a particular interest, and the classifier outputs a prediction of whether the user has the corresponding interest. In one embodiment, the online system trains a classifier for various interest values by forming training sets for the interests using the features for users who are logged into the online system and hence have known interests.

Abstract: An online system obtains a set of resolved impressions based on historical data about multiple publishers. A set of features is then extracted, for each resolved impression, based on a comparison of historical data about the first publisher and the second publisher. The online system performs training of a machine-learned model based on the set of features. Data about a plurality of new impressions are input into the trained machine-learned model to obtain an output of the trained machine-learned model. A reach overlap metric and unique reach metric can be computed based on the output of the trained machine-learned model.

Abstract: An audience analysis system determines and predicts reach and frequency information of online users. The system receives real-time ad impression data from ad publishers or other data providers as well as report requests from advertisers asking for the reach and frequency information. The reach and frequency information of online users describes characteristics of online users that are reached by the advertisers. Matched users and unmatched users are identified via online cookies. Atomic data units are generated to allow feature computation and reach prediction for online users in a more efficient way. Machine learning models are trained to help predict the reach and frequency of unmatched users and to generate reports. The audience analysis system provides the advertisers with the generated reports, responding to the report requests.

Abstract: An online system determines one or more metrics describing consumption of content by various users by identifying users of the online system capable of being identified based on information received from multiple client devices. For example, the online system identifies users associated with user identifiers that are also associated with other types of identifying information (e.g., cookies, device identifiers). From the identified users, the online system generates a set of users based on a distribution of characteristics. The distribution of characteristics may be determined by the online system as characteristics of a group of users or received by the online system from a third party system and describes characteristics of users of the third party system. Based on interactions with content by users in the set, the online system determines one or more metrics describing consumption of content.

Abstract: User inputs can indicate an intent of a user to target a location on a display. In order to determine a targeted point based on a user input, a computing device can receive an indication of at least one point, an indication of a width, and an indication of a height. The computing device can estimate a portion of the display based on the indication of the at least one point, the indication of the width, and the indication of the height. The computing device can also determine the targeted point based on a location of the at least one point and based on a location of a portion of one or more objects within the estimated portion of the display.

Abstract: A processing device may recognize a number of input handwritten strokes, which may represent a mathematical expression, a chemical formula, or other two-dimensional structure. Rewriting rules of a grammar may be applied to the strokes to produce a number of possible recognition results. Each of the possible recognition results has a respective score based on a sum of rewriting rules applied to the strokes to produce respective ones of the possible recognition results. Input may be provided to identify misrecognized strokes and a correct terminal production, or symbol corresponding to the misrecognized strokes. Strokes may be misrecognized for many reasons, including parsing errors, over-grouping or under-grouping of matrices, and improper placement of a recognized terminal production, or symbol, with respect to a root structure. Correction hints may be leveraged for correcting types of errors mentioned above.

Abstract: A natural input system is described for creating and editing complex structures in a typeset application. The natural input system receives a typeset representation of an object and converts the typeset format to generate a standard digital ink representation. The natural input system provides the generated ink representation to a natural input application where can be manipulated by the user with a rich set of correction and editing features provided by the natural input application. Once the end user is satisfied with the recognition result in the natural input application, the natural input system receives the recognition result based on the modified digital ink representation. The natural input system may convert the received recognition result to the typeset application format and provides the modified typeset representation to the typeset application for merging into the document the user is editing.

Abstract: A number of regions and partitions may be created based on input handwritten atoms and a grammar parsing framework. Productions for tabular structures may be added to the grammar parsing framework to produce an extended grammar parsing framework. Each of the regions may be searched for a tabular structure. Upon finding a tabular structure, a type of tabular structure may be determined. Configuration partitions may be created, based on the added productions, and added to the created partitions. A set of configuration regions may be created based on the configuration partitions and added to the created regions. The productions for tabular structures and productions of the grammar parsing framework may be applied, as rewriting rules, to the atoms to produce possible recognition results. A best recognition result may be determined and displayed. A mechanism for correcting misrecognition errors, which may occur while recognizing tabular structures, may be provided.

Abstract: A number of regions and partitions may be created based on input handwritten atoms and a grammar parsing framework. Productions for tabular structures may be added to the grammar parsing framework to produce an extended grammar parsing framework. Each of the regions may be searched for a tabular structure. Upon finding a tabular structure, a type of tabular structure may be determined. Configuration partitions may be created, based on the added productions, and added to the created partitions. A set of configuration regions may be created based on the configuration partitions and added to the created regions. The productions for tabular structures and productions of the grammar parsing framework may be applied, as rewriting rules, to the atoms to produce possible recognition results. A best recognition result may be determined and displayed. A mechanism for correcting misrecognition errors, which may occur while recognizing tabular structures, may be provided.

Abstract: In embodiments consistent with the subject matter of this disclosure, a user may input one or more strokes as digital ink to a processing device. The processing device may produce and present a recognition result, which may include a misrecognized portion. A user may indicate a desire to correct the misrecognized portion and may further select one or more strokes of the misrecognized portion. The processing device may then present the one or more recognition alternates corresponding to the selected one or more strokes of the misrecognized portion. In some embodiments, the processing device may permit a user to rewrite the selected one or more strokes of the misrecognized portion with newly entered digital ink. Features, such as, rewriting and correction of the input digital ink may be discoverable in some embodiments.

Abstract: A processing device may parse a group of strokes representing a mathematical expression. The group of strokes may be examined to determine whether the group of strokes satisfies any of a finite set of rules. When the group of strokes, included in a region, satisfies any of the finite set of rules, the region may be partitioned according to a satisfied one of the finite set of rules. The group of strokes included in the region may be further examined to determine whether the group of strokes may be further partitioned according to any of the finite set of rules. After all regions have been examined and no further partitioning of regions may be performed, all mathematical symbols of the mathematical expression may be isolated in at least some of the regions and may be recognized.

Abstract: In embodiments consistent with the subject matter of this disclosure, a user may input strokes as digital ink to a processing device. The processing device may partition the input strokes into multiple regions of strokes. A first recognizer and a second recognizer may score grammar objects included in regions and represented by chart entries. The scores may be converted to a converted score, which may have at least a near standard normal distribution. The processing device may present a recognition result based on highest converted scores according to a recurrence formula. The processing device may receive a correction hint with respect to misrecognized strokes and may add a penalty score with respect to chart entries representing grammar objects breaking the correction hint. Incremental recognition may be performed when a pause is detected during inputting of strokes.

Abstract: A natural input system is described for creating and editing complex structures in a typeset application. The natural input system receives a typeset representation of an object and converts the typeset format to generate a standard digital ink representation. The natural input system provides the generated ink representation to a natural input application where can be manipulated by the user with a rich set of correction and editing features provided by the natural input application. Once the end user is satisfied with the recognition result in the natural input application, the natural input system receives the recognition result based on the modified digital ink representation. The natural input system may convert the received recognition result to the typeset application format and provides the modified typeset representation to the typeset application for merging into the document the user is editing.

Abstract: A number of regions and partitions may be created based on input handwritten atoms and a grammar parsing framework. Productions for tabular structures may be added to the grammar parsing framework to produce an extended grammar parsing framework. Each of the regions may be searched for a tabular structure. Upon finding a tabular structure, a type of tabular structure may be determined. Configuration partitions may be created, based on the added productions, and added to the created partitions. A set of configuration regions may be created based on the configuration partitions and added to the created regions. The productions for tabular structures and productions of the grammar parsing framework may be applied, as rewriting rules, to the atoms to produce possible recognition results. A best recognition result may be determined and displayed. A mechanism for correcting misrecognition errors, which may occur while recognizing tabular structures, may be provided.

Abstract: A processing device may recognize a number of input handwritten strokes, which may represent a mathematical expression, a chemical formula, or other two-dimensional structure. Rewriting rules of a grammar may be applied to the strokes to produce a number of possible recognition results. Each of the possible recognition results has a respective score based on a sum of rewriting rules applied to the strokes to produce respective ones of the possible recognition results. Input may be provided to identify misrecognized strokes and a correct terminal production, or symbol corresponding to the misrecognized strokes. Strokes may be misrecognized for many reasons, including parsing errors, over-grouping or under-grouping of matrices, and improper placement of a recognized terminal production, or symbol, with respect to a root structure. Correction hints may be leveraged for correcting types of errors mentioned above.

Abstract: In embodiments consistent with the subject matter of this disclosure, a user may input one or more strokes as digital ink to a processing device. The processing device may produce and present a recognition result, which may include a misrecognized portion. A user may indicate a desire to correct the misrecognized portion and may further select one or more strokes of the misrecognized portion. The processing device may then present the one or more recognition alternates corresponding to the selected one or more strokes of the misrecognized portion. In some embodiments, the processing device may permit a user to rewrite the selected one or more strokes of the misrecognized portion with newly entered digital ink. Features, such as, rewriting and correction of the input digital ink may be discoverable in some embodiments.

Abstract: In embodiments consistent with the subject matter of this disclosure, a user may input strokes as digital ink to a processing device. The processing device may partition the input strokes into multiple regions of strokes. A first recognizer and a second recognizer may score grammar objects included in regions and represented by chart entries. The scores may be converted to a converted score, which may have at least a near standard normal distribution. The processing device may present a recognition result based on highest converted scores according to a recurrence formula. The processing device may receive a correction hint with respect to misrecognized strokes and may add a penalty score with respect to chart entries representing grammar objects breaking the correction hint. Incremental recognition may be performed when a pause is detected during inputting of strokes.

Abstract: A processing device may parse a group of strokes representing a mathematical expression. The group of strokes may be examined to determine whether the group of strokes satisfies any of a finite set of rules. When the group of strokes, included in a region, satisfies any of the finite set of rules, the region may be partitioned according to a satisfied one of the finite set of rules. The group of strokes included in the region may be further examined to determine whether the group of strokes may be further partitioned according to any of the finite set of rules. After all regions have been examined and no further partitioning of regions may be performed, all mathematical symbols of the mathematical expression may be isolated in at least some of the regions and may be recognized.