Patents by Inventor Daniel Kifer

Daniel Kifer has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 7877380
    Abstract: A system of query scheduling to maximize work sharing. The system schedules queries to account for future queries possessing a sharability component. Included in the system are operations for assigning an incoming query to a query queue based on a sharability characteristic of the incoming query, and evaluating a priority function for each member of a plurality of query queues to identify one highest priority query queue. The priority function accounts for the probability that a future incoming query will contain the sharability characteristic common to a member of the plurality of query queues. The system of query scheduling to maximize work sharing selects a batch of queries from the highest priority query queue, and dispatches the batch to one or more query execution units.
    Type: Grant
    Filed: February 25, 2008
    Date of Patent: January 25, 2011
    Assignee: Yahoo! Inc.
    Inventors: Parag Agrawal, Daniel Kifer, Chris Olston
  • Publication number: 20100274770
    Abstract: Disclosed are methods and apparatus for segmenting and labeling a collection of token sequences. A plurality of segments of one or more tokens in a token sequence collection are partially labeled with labels from a set of target labels using high precision domain-specific labelers so as to generate a partially labeled sequence collection having a plurality of labeled segments and a plurality of unlabeled segments. Any label conflicts in the partially labeled sequence collection are resolved. One or more of the labeled segments of the partially labeled sequence collection are expanded so as to cover one or more additional tokens of the partially labeled sequence collection. A statistical model, for labeling segments using local token and segment features of the sequence collection, is trained based on the partially labeled sequence collection. This trained model is then used to label the unlabeled segments and the labeled segments of the sequence collection so as to generate a labeled sequence collection.
    Type: Application
    Filed: April 24, 2009
    Publication date: October 28, 2010
    Applicant: Yahoo! Inc.
    Inventors: Rahul Gupta, Sathiya Keerthi Selvaraj, Daniel Kifer, Srujana Merugu
  • Publication number: 20100241639
    Abstract: Disclosed are methods and apparatus for extracting (or annotating) structured information from web content. Web content of interest from a particular domain is represented as one or more tree instances having a plurality of branching nodes that each correspond to a web object such that the tree instances correspond to one or more structured data instances. The particular domain is associated with domain knowledge that includes one or more presentation rulesets that each specifies a particular structure for a set of data instances, a domain-specific concept labeler, one or more specified properties of the web objects in the tree instances, and a concept schema that specifies a representation of the data to be extracted from the web content. A structured data instance that conforms to the concept schema is extracted from the one or more tree instances based on the domain knowledge for the particular domain.
    Type: Application
    Filed: March 20, 2009
    Publication date: September 23, 2010
    Applicant: YAHOO! INC.
    Inventors: Daniel Kifer, Srujana Merugu, Ankur Jain, Sathiya Keerthi Selvaraj, Alok S. Kirpal, Philip L. Bohannon, Raghu Ramakrishnan
  • Publication number: 20090327168
    Abstract: Embodiments are directed towards employing a playful incentive to encourage users to provide feedback that is useable to train a classifier. The classifier being associated with any of a variety of different settings, including but not limited to classifying: messages as ham/spam, images, advertising, bookmarking, music, videos, photographs, shopping, or the like. An animated image, such as a pet, provides an interface to the classifier that encourages and responds to user feedback. Users may share their classifiers or aspects thereof with other users to enable a community of knowledge to be applied to a classification task, while preserving privacy of the user feedback. One form of sharing may be within the context of a competitive game. Various evaluations may be performed on a classifier to indicate user feedback consistency, or quality. Classifiers may also be used to provide users with advertisements, products, or services based on the user's feedback.
    Type: Application
    Filed: June 26, 2008
    Publication date: December 31, 2009
    Applicant: Yahoo! Inc.
    Inventors: Kilian Quirin Weinberger, Anirban Dasgupta, Raghu Ramakrishnan, David Reiley, Martin Andre Monroe Zinkevich, Bo Pang, Daniel Kifer
  • Publication number: 20090216718
    Abstract: A system of query scheduling to maximize work sharing. The system schedules queries to account for future queries possessing a sharability component. Included in the system are operations for assigning an incoming query to a query queue based on a sharability characteristic of the incoming query, and evaluating a priority function for each member of a plurality of query queues to identify one highest priority query queue. The priority function accounts for the probability that a future incoming query will contain the sharability characteristic common to a member of the plurality of query queues. The system of query scheduling to maximize work sharing selects a batch of queries from the highest priority query queue, and dispatches the batch to one or more query execution units.
    Type: Application
    Filed: February 25, 2008
    Publication date: August 27, 2009
    Inventors: Parag Agrawal, Daniel Kifer, Chris Olston