Abstract: Embodiments of the invention relate to generating automated web task procedures from an analysis of web history logs. One aspect of the invention concerns a method that comprises identifying sequences of related web actions from a web log, grouping each set of similar web actions into an action class, and mapping the sequences of related web actions into sequences of action classes. The method further clusters each group of similar sequences of action classes into a cluster, wherein relationships among the action classes in the cluster are represented by a state machine, and generates automated web task procedures from the state machine.

Abstract: Embodiments of the invention relate to user identification in social media for task performance based on past usage and traits. One embodiment includes identifying users of a social media platform for ability of performing a task. Readiness scores are predicted based on past usage of the social media platform. A predicted readiness score includes a value corresponding to whether a user is predicted to be ready for performing the task. Users that are ready to perform the task are determined based on comparing the readiness scores with a threshold. Willingness scores for performing the task by the users determined to be able and ready to perform the task are determined. A willingness score includes a value corresponding to whether a user is estimated to be willing for performing the task. Users that are willing to perform the task are determined based on comparing the willingness scores with a threshold.

Abstract: Provided are techniques for tailoring correspondence based upon individual recipients, comprising receiving a correspondence for dissemination to a set of recipients; annotating text within the composition to identify words and characteristics of the words; identifying a customization criteria based upon a target audience; generating, a template, wherein the template comprises: the customization criteria; and modification constraints; and applying the template and the customization criteria to the annotated text to generate a revised correspondence.

Abstract: Embodiments relate to optimizing user response rate in social media. One embodiment includes generating a model for modeling a likelihood of social media user response from data collected from social media based on social media user filtering criteria and historical information. Modeling the likelihood includes estimating ability of social media users to perform a particular task based on social media user information including tracking of the social media users, evaluating previous task responses and personality features. Social media users are selected based on estimated ability to perform the particular task for maximizing a response rate.

Abstract: Embodiments relate to optimizing user response rate in social media. One embodiment includes generating a model for modeling a likelihood of social media user response from data collected from social media based on social media user filtering criteria and historical information. Modeling the likelihood includes estimating ability of social media users to perform a particular task based on social media user information including tracking of the social media users, evaluating previous task responses and personality features. Social media users are selected based on estimated ability to perform the particular task for maximizing a response rate.

Abstract: Embodiments of the invention relate to predicting user activity in a social media application. In one embodiment, user activity information is collected for a user from a social media application and activity features of the user are determined, based on the collected activity information for the user. Then a model is created to predict a future activity of the user in the social media application. The model uses the determined activity features of the user and results obtained from running the created model, to determine future activity of the user in the social media application.

Abstract: Embodiments of the invention relate to optimizing user response rate in social media. One embodiment includes generating a statistical model for modeling a likelihood of social media user response from data collected from social media using a set of available features. The social media users are ranked in an estimation set based on the statistical model. The ranked social media users are placed in a rank ordered list. A sub-interval on the rank ordered list is selected for maximizing the response rate.

Abstract: Embodiments include a program product and a method for providing responses to questions provided on a social media site. The method includes receiving, via a processor, a user question from a social networking site and decomposing and filtering the user question so that it can be further analyzed. The method also includes generating a list of most closely matched potential responders based on analysis of the user question and sending the most closely matched potential responders the user question. Upon receiving responses back from the most closest matched potential responders, these responses are aggregated by the processor in a final response format.

Abstract: Various embodiments relate to estimating the location of social network users. In one embodiment, a plurality of social media messages generated by a given user is received. A plurality of location features is extracted from the social media messages. Each of the location features is processed with at least one classifier from an ensemble of classifiers. A location classification is generated by each of the classifiers for each of the social media messages. Each classification comprises a location and a weight associated with that location. One of the locations is selected from the location classifications as the location of the given user based on a combination of the weights of the location classifications.

Abstract: Various embodiments of the invention relate to estimating the location of social network users. In one embodiment, a plurality of social media messages generated by a given user is received. A plurality of location features is extracted from the social media messages. Each of the location features is processed with at least one classifier from an ensemble of classifiers. A location classification is generated by each of the classifiers for each of the social media messages. Each classification comprises a location and a weight associated with that location. One of the locations is selected from the location classifications as the location of the given user based on a combination of the weights of the location classifications.

Abstract: A method of assembling a frame and suspension module includes determining locations of first and second suspension member supports on the frame. Target positions of first and second connections between the frame and third and fourth suspension members are defined based on the locations of the first and second suspension member supports. Target positions of third and fourth connections between a fifth suspension member and the first and second suspension members are defined based on the locations and the target positions of the first and second connections. The first and second suspension members are connected to the frame at the locations. The third and fourth suspension members are connected to the frame at the first and second target positions. The fifth suspension member is connected to the first and second suspension members at the third and fourth target positions.

Abstract: A recommendation of a direct engagements is made. A topic is received from a recommendee system, and a social media post is received from a social media server. A first and second information about the source of the social media post are determined. The first information can include the location of the source of the social media post, the readiness for engagement of the source of the social media post, or the personality of the source of the social media post. The second information can include the relevance of the content of the social media post to the topic, the opinion of the content of the social media post about the topic, or the intent of the content of the social media post regarding the topic. A direct engagement to be performed on the source based on the first information and the second information is determined.

Abstract: Embodiments of the invention relate to identifying users for initiating information spreading in social network. In one embodiment, information for one or more users of a social network is collected and one or more features for each of the one or more users based on the collected information is computed. The one or more features are compared with a statistical model and calculating a probability that each of the one or more users will spread a message received from outside their social network based on the comparison.

Abstract: Embodiments of the invention relate to predicting user activity in a social media application. In one embodiment, user activity information is collected for a user from a social media application and activity features of the user are determined, based on the collected activity information for the user. Then a model is created to predict a future activity of the user in the social media application. The model uses the determined activity features of the user and results obtained from running the created model, to determine future activity of the user in the social media application.

Abstract: Embodiments of the invention relate to optimizing user response rate in social media. One embodiment includes generating a statistical model for modeling a likelihood of social media user response from data collected from social media using a set of available features. The social media users are ranked in an estimation set based on the statistical model. The ranked social media users are placed in a rank ordered list. A sub-interval on the rank ordered list is selected for maximizing the response rate.

Abstract: Embodiments include a program product and a method for providing responses to questions provided on a social media site. The method includes receiving, via a processor, a user question from a social networking site and decomposing and filtering the user question so that it can be further analyzed. The method also includes generating a list of most closely matched potential responders based on analysis of the user question and sending the most closely matched potential responders the user question. Upon receiving responses back from the most closest matched potential responders, these responses are aggregated by the processor in a final response format.

Abstract: The method includes collecting a first plurality of social media messages, where each of the first plurality of social media messages contains a respective location of a first social media user; determining a first plurality of geographical distances between the respective locations contained in the first plurality of social media messages; determining a maximum or average geographical distance from the first plurality of geographical distances; and comparing the maximum or average geographical distance to a first or second threshold to determine if the first social media user is a traveler. For a plurality of social media messages, where each of the social media messages does not contain a respective location of a social media user, the method includes extracting content from the plurality of social media messages and comparing the extracted content to a traveler model to determine if the social media user is a traveler.

Abstract: Embodiments of the invention relate to user identification in social media for task performance based on past usage and traits. One embodiment includes identifying users of a social media platform for ability of performing a task. Readiness scores are predicted based on past usage of the social media platform. A predicted readiness score includes a value corresponding to whether a user is predicted to be ready for performing the task. Users that are ready to perform the task are determined based on comparing the readiness scores with a threshold. Willingness scores for performing the task by the users determined to be able and ready to perform the task are determined. A willingness score includes a value corresponding to whether a user is estimated to be willing for performing the task. Users that are willing to perform the task are determined based on comparing the willingness scores with a threshold.

Abstract: Embodiments of the invention relate to generating automated web task procedures from an analysis of web history logs. One aspect of the invention concerns a method that comprises identifying sequences of related web actions from a web log, grouping each set of similar web actions into an action class, and mapping the sequences of related web actions into sequences of action classes. The method further clusters each group of similar sequences of action classes into a cluster, wherein relationships among the action classes in the cluster are represented by a state machine, and generates automated web task procedures from the state machine.

Abstract: A method, system and program product for combining and processing web data using tables and programming-by-demonstration is disclosed. Direct manipulation and programming-by-demonstration techniques are used to automatically populate tables with information collected from various web sites. The invention augments a data set with new values computed by a web site.