Abstract:
The present teaching, which includes methods, systems and computer-readable media, relates to providing content from multiple disparate sources including a person's personal data sources and non-personal data sources. The disclosed techniques may include receiving a request for content from a person; obtaining first content from a first source private to the person based on the request; obtaining second content from at least one second source based on the request; blending the first content from the first source and the second content from the at least one second source to generate a blended content; and providing the blended content to the person in response to the request.
Abstract:
The present teaching relates to online task exchange. In one example, information related to a task automatically created based on an intent of a person is received. The task is posted to a plurality of parties that are capable of completing the task. One or more bids are received from at least some of the plurality of parties. At least one winning bid is selected from the one or more bids based on at least one criterion. Information indicative of a status as to completion of the task is received. Resource is allocated to the at least one winning bid based on the status.
Abstract:
A method, implemented on at least one computing device each of which has at least one processor, storage, and a communication platform connected to a network for providing synthetic answers to a personal question is disclosed. A personal question is received from a person. One or more entities are extracted from the personal question. One or more relations are extracted from the personal question. A model is selected based on the personal question. One or more synthetic answers to the personal question are obtained based on the one or more entities, the one or more relations, and the selected model.
Abstract:
A method is provided for building a user interest profile, including the following method operations: identifying features of each of a plurality of articles; for a given user, logging views of one or more of the plurality of articles; for each view, measuring a corresponding dwell time for the view by the given user; applying a weight to each view based on the corresponding measured dwell time; determining user interest scores for features of the one or more of the plurality of articles based on the weighted views; generating a user interest profile for the given user based on the user interest scores.
Abstract:
A system and/or technique for graphical interface presentation comprises receiving a search string and presenting a search result series to a user on a client device. Search results of the search result series are presented in the form of cards, where a first card comprises information associated with a first search result of the search result series and a second card comprises information associated with a second search result of the search result series. A user may navigate through the cards to view various search results.
Abstract:
Embodiments of the present teachings disclose method, system, and programs that monetize personalized user behavioral profiles by remapping the users to audience segments related to advertisement. In the method, the users can be targeted with advertisements that are personalized and hence are more likely to lead to conversions
Abstract:
A method and system for exploring a list of user interests beyond the currently known user interests by defining a distance metrics in the interest space is disclosed. The new method and system target for exploration, items of interests which are close in proximity to the current set of user interests, thereby greatly improving the chance that one of the exploration items will be liked by the user.
Abstract:
Embodiments of the present teachings disclose method, system, and programs for a multi-phase ranking system for implementation with a personalized content system. The disclosed method, system, and programs utilize a weighted AND system to compute a dot product of the user profile and a content profile in a first phase, a content quality indicator in the second phase and a rules filter in a third phase.
Abstract:
A method of targeting receives several granular events and preprocesses the received granular events thereby generating preprocessed data to facilitate construction of a model based on the granular events. The method generates a predictive model by using the preprocessed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive model. A system for targeting includes granular events, a preprocessor for receiving the granular events, a model generator, and a model. The preprocessor has one or more modules for at least one of pruning, aggregation, clustering, and/or filtering. The model generator is for constructing a model based on the granular events, and the model is for determining a likelihood of a user action. The system of some embodiments further includes several users, a selector for selecting a particular set of users from among the several users, a trained model, and a scoring module.
Abstract:
Methods, systems, and computer programs are presented for selecting news articles for presentation to a user. One method includes an operation for measuring dwelltimes for a first set of news items, where the dwelltime for a news item is based on the amount of time that the news item is displayed to a viewer. Further, the method includes an operation for training a classifier of news items based on the measured dwelltimes and based on features associated with the first set of news items. Additionally, the method includes an operation for ranking with the classifier a second set of news items for presentation to the user, the ranking also using the profile of the user for delivery of customized news to the user. The ranked second set of news item is then presented to the user.