[미국특허]
System and method for addressing communications
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G06F-015/16
G06F-015/173
출원번호
US-0057878
(2008-03-28)
등록번호
US-8589486
(2013-11-19)
발명자
/ 주소
Martinez, Ronald
Davis, Marc Eliot
Higgins, Christopher William
O'Sullivan, Joseph James
출원인 / 주소
Yahoo! Inc.
대리인 / 주소
DeCarlo, James J.
인용정보
피인용 횟수 :
2인용 특허 :
112
초록▼
The disclosure describes systems and methods for utilizing data collected and stored on multiple devices in order to improve the performance of the network via a markup language for addressing and delivering communications. The markup language invokes W4COMN operations through a free-form, natural l
The disclosure describes systems and methods for utilizing data collected and stored on multiple devices in order to improve the performance of the network via a markup language for addressing and delivering communications. The markup language invokes W4COMN operations through a free-form, natural language syntax which enables completely personalized user-defined designations for real-world entities (RWEs) or information objections (IOs) utilizing names or functional tags. Desired network operations including addressing network resources, entities or users are activated when the markup language is augmented via processing with W4 contextual data into an actual W4COMN circuit, process or event.
대표청구항▼
1. A method comprising: defining, via a computing device, a user-defined markup language, the user-defined markup language comprising a plurality of user-defined conditional operators, each user-defined conditional operator of the plurality of user-defined conditional operators defining a respective
1. A method comprising: defining, via a computing device, a user-defined markup language, the user-defined markup language comprising a plurality of user-defined conditional operators, each user-defined conditional operator of the plurality of user-defined conditional operators defining a respective relationship type and being associated with a respective syntax, such that the user-defined markup language is defined in response to receiving data relating to the plurality of user-defined conditional operators from a user;receiving, at the computing device, a request from a sender real-world entity (RWE) to deliver a first information object (IO) to a recipient RWE identified by an address string;parsing, via the computing device, the address string to identify at least a first address string descriptor, a second address string descriptor and an address string conditional operator, such that the address string conditional operator matches one user-defined conditional operator of the plurality of user-defined conditional operators, and the respective syntax associated with the one user-defined conditional operator of the plurality of user-defined conditional operators is used in parsing the address string;determining, via the computing device, that the one user-defined conditional operator of the plurality of user-defined conditional operators defines a first relationship between the first address string descriptor and the second address string descriptor;identifying, via the computing device, a first subset of one or more RWEs matching the first address string descriptor;identifying, via the computing device, a second subset of one or more RWEs matching the second address string descriptor;identifying, via the computing device, spatial, temporal, social and topical relationships between the each of the RWEs in the first subset and the second subset using a combined graph of data available, via a network, for RWEs and IOs known to the network;selecting, via the computing device, one RWE of the first subset of RWEs to be the recipient RWE based on a comparison of the spatial, temporal, social and topical relationships and the first relationship; andtransmitting, from the computing device over a network, the first IO to the selected recipient RWE using a unique identifier associated with the recipient RWE. 2. The method of claim 1 further comprising: determining, via the computing device, that the one conditional operator of the plurality of user-defined conditional operators identifies a delivery condition defined by the second descriptor;retrieving the unique identifier associated with the first descriptor; andtransmitting the first IO to recipient RWE when the delivery condition is satisfied. 3. The method of claim 1 further comprising: generating, via the computing device, based on the spatial, temporal, social and topical relationships and the first relationship, a respective probability score for each combination of RWEs from the first subset and the second subset;selecting, via the computing device, one of the combinations of RWEs based on the respective probability score for the one of the combinations of RWEs; andselecting the recipient RWE based on the one of the combinations of RWEs. 4. The method of claim 1 further comprising: retrieving, via the computing device, the unique identifier for the recipient RWE from a set of unique identifiers associated with the recipient RWE, such that each unique identifier in the set of unique identifiers is associated with a respective one of a plurality of communication channels and the method further comprises:selecting, via the computing device, based on the request, a selected one of the plurality of communication channels for transmitting the first IO to the recipient RWE; andselecting, via the computing device, the unique identifier for the recipient RWE associated with the selected one of the plurality of communication channels. 5. A system comprising: a processor connected via at least one communication channel to a plurality of computing devices transmitting information objects (IOs) over the at least one communication channel;a storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising: markup language definition logic executed by the processor for defining a user-defined markup language the user-defined markup language comprising a plurality of user-defined conditional operators, each user-defined conditional operator of the plurality of user-defined conditional operators defining a respective relationship type and being associated with a respective syntax, such that the user-defined markup language is defined in response to receiving data relating to the plurality of user-defined conditional operators from a user;request receiving logic executed by the processor for receiving, at the computing device, a request from a sender real-world entity (RWE) to deliver a first IO to a recipient RWE identified by an address string;parsing logic executed by the processor for parsing the address string to identify at least a first address string descriptor, a second address string descriptor and an address string conditional operator, such that the address string conditional operator matches one user-defined conditional operator of the plurality of user-defined conditional operators, and the respective syntax associated with the one user-defined conditional operator of the plurality of user-defined conditional operators is used in parsing the address string;conditional operator logic executed by the processor for determining that the one user-defined conditional operator of the plurality of user-defined conditional operators defines a first relationship between the first descriptor and the second descriptor;RWE identification logic executed by the processor for identifying a first subset of one or more RWEs matching the first descriptor and identifying a second subset of one or more RWEs matching the second descriptor;correlation logic executed by the processor for identifying spatial, temporal, social and topical relationships between the each of the RWEs in the first subset and the second subset using a combined graph of data available, via a network, for RWEs and IOs known to the network;RWE selection logic executed by the processor for selecting one RWE of the first subset of RWEs to be the recipient RWE based on a comparison of the spatial, temporal, social and topical relationships and the first relationship; andIO transmission logic executed by the processor for transmitting, from the computing device over a network, the first IO to the selected recipient RWE using a unique identifier associated with the recipient RWE. 6. The system of claim 5 further comprising: delivery logic executed by the processor for retrieving a unique communication channel address for the recipient RWE and transmitting a first IO to the unique communication channel address, the unique communication channel address being different from the address string. 7. The system of claim 6, such that the RWE selection logic further generates, based on the data spatial, temporal, social and topical relationships and the first relationship, a different respective probability score for each combination of RWEs from the first subset and the second subset, selects one of the combinations of RWEs based on the respective probability score for the one of the combinations of RWEs and selects the recipient RWE based on the selected one of the combinations of RWEs. 8. The system of claim 7 further comprising: attribution logic executed by the processor for that identifing the sender RWE of the first IO from the data of the first IO, the owner being one of the plurality of RWEs; andsuch that the RWE selection logic further generates the probability for each of the plurality of RWEs based on relationships between the sender RWE and the each RWE of the first subset and the second subset. 9. The method of claim 1 such that the combined graph is a histogram of RWEs and IOs known to the network. 10. The method of claim 9 such that the histogram comprises a plurality of categories, wherein each RWE and IO are in a respective one category of a plurality of categories, and a count is assigned to each category of the plurality of categories, each count comprising a number of observations in the data available for RWEs and IOs that fall into the respective one category of the plurality of categories. 11. The method of claim 3 such that the respective probability score is determined by ascribing a weight to each respective relationship based on a predetermination of their relative importance by relationship type and strength. 12. The method of claim 1 such that the combined graph is a feature vector of RWEs known to the network. 13. The method of claim 12 such that feature vector comprises raw sensed data and higher order features relating to RWEs known to the network. 14. The method of claim 12 such that higher order features comprise contextual and periodic patterns of states and actions of RWEs known to the network. 15. The method of claim 13 such that relationships within the feature vector are identified using a learning algorithm. 16. The method of claim 15 such that the learning algorithm is selected from the list: Sparse Factor Analysis, Hidden Markov Model, Support Vector Machine, Bayesian Methods. 17. A non-transitory computer readable storage media for tangibly storing thereon computer readable instructions for a method comprising: defining a user-defined markup language, the user-defined markup language comprising a plurality of user-defined conditional operators, each user-defined conditional operator of the plurality of user-defined conditional operators defining a respective relationship type and being associated with a respective syntax, such that the user-defined markup language is defined in response to receiving data relating to the plurality of user-defined conditional operators from a user;receiving a request from a sender real-world entity (RWE) to deliver a first information object (IO) to a recipient RWE identified by an address string;parsing the address string to identify at least a first address string descriptor, a second address string descriptor and an address string conditional operator, such that the address string conditional operator matches one user-defined conditional operator of the plurality of user-defined conditional operators, and the respective syntax associated with the one user-defined conditional operator of the plurality of user-defined conditional operators is used in parsing the address string;determining that the one user-defined conditional operator of the plurality of user-defined conditional operators defines a first relationship between the first address string descriptor and the second address string descriptor;identifying a first subset of one or more RWEs matching the first address string descriptor;identifying a second subset of one or more RWEs matching the second address string descriptor;identifying spatial, temporal, social and topical relationships between the each of the RWEs in the first subset and the second subset using a combined graph of data available, via a network, for RWEs and IOs known to the network;selecting one RWE of the first subset of RWEs to be the recipient RWE based on a comparison of the spatial, temporal, social and topical relationships and the first relationship; andtransmitting the first IO to the selected recipient RWE using a unique identifier associated with the recipient RWE.
Deligne Sabine ; Sagisaka Yoshinori,JPX ; Nakajima Hideharu,JPX, Apparatus for generating a statistical sequence model called class bi-multigram model with bigram dependencies assumed between adjacent sequences.
Nair, Rahul; Higgins, Christopher W.; Davis, Marc E.; O'Sullivan, Joseph J.; Paretti, Christopher T., Bandwidth and cost management for ad hoc networks.
Stolorz, Paul E.; Salmon, John K.; Warren, Michael S.; Koller, Jeffrey G.; Hagberg, Aric; Yevmenkin, Maksim; Brady, Mark; Pfitzner, David; Middleton, Ted, Configurable adaptive global traffic control and management.
Biebesheimer, Debra L.; Jasura, Donn P.; Keller, Neal M.; Oblinger, Daniel A.; Podlaseck, Mark E.; Rolando, Stephen J., Customer self service system for resource search and selection.
Shingo Nishioka JP; Makoto Iwayama JP; Kazuhiro Ono JP; Akihiko Takano JP; Yoshiki Niwa JP; Atsuko Yamaguchi JP, Document retrieval assisting method and system for the same and document retrieval service using the same.
Horvitz Eric ; Breese John S. ; Heckerman David E. ; Hobson Samuel D. ; Hovel David O. ; Klein Adrian C. ; Rommelse Jacobus A.,NLX ; Shaw Gregory L., Intelligent user assistance facility.
Bennett, Ian M.; Babu, Bandi Ramesh; Morkhandikar, Kishor; Gururaj, Pallaki, Interactive speech based learning/training system formulating search queries based on natural language parsing of recognized user queries.
Bassett,Ronald W.; Beadle,Bruce A.; Brown,Michael Wayne; Doud,Leon P.; Paolini,Michael A., Method and apparatus for dynamic distribution of controlled and additional selective overlays in a streaming media.
Atcheson John (San Francisco CA) Miller ; III James R. (Stanford CA), Method and apparatus for recommending selections based on preferences in a multi-user system.
Brandenberg, Carl Brock; Kay, Robert L.; Maxwell, Kenneth J.; Cotter, R. Brandon, Method and apparatus for scheduling presentation of digital content on a personal communication device.
Makar, Michael G.; Mosley, Joseph M.; Tindall, Tracy A., Method and system for filtering messages based on a user profile and an informational processing system event.
Bates, Cary Lee; Crenshaw, Robert James; Day, Paul Reuben; Santosuosso, John Matthew, Method for resolving meeting conflicts within an electronic calendar application.
Gabai, Oz; Gabai, Jacob; Sanlerman, Nimrod; Weiss, Nathan, Methods and apparatus for integration of interactive toys with interactive television and cellular communication systems.
Beall Christopher W. ; Motycka John D. ; Pendleton Samuel S. ; Terpening Brooke E. ; Appelbaum Matthew A. ; Neal Michael R., Search engine for remote access to database management systems.
Theimer Marvin M. (Mountain View CA) Spreitzer Michael J. (Tracy CA) Weiser Mark D. (Palo Alto CA) Goldstein Richard J. (San Francisco CA) Terry Douglas B. (San Carlos CA) Schilit William N. (Palo Al, Selective delivery of electronic messages in a multiple computer system based on context and environment of a user.
Langseth, Justin; Talwar, Ajay; Fishman, Phillippa J., System and method for a subject-based channel distribution of automatic, real-time delivery of personalized informational and transactional data.
Shimizu,Atsushi; Masuda,Kiyoshi; Yamato,Masaki; Ando,Tanichi; Oyagi,Masayuki, System and method for accepting information from information providers, mediating the received information, and providing mediated information to information beneficiaries.
Langseth, Justin; Talwar, Ajay; Fishman, Phillippa J., System and method for automatic, real-time delivery of personalized informational and transactional data to users via content delivery device.
Chidlovskii Boris,FRX ; Glance Natalie S.,FRX ; Grasso Antonietta,FRX, System and method for collaborative ranking of search results employing user and group profiles derived from document collection content analysis.
Davis, Marc Eliot; O'Sullivan, Joseph James; Higgins, Christopher William; Saft, Keith David; Hayashi, Nathanael Joe; Boerries, Marco; Callan, Paul; Wroblewski, Luke, System and method for delivery of augmented messages.
Langseth, Justin; Talwar, Ajay; Fishman, Phillippa J., System and method for information warehousing supporting the automatic, real-time delivery of personalized informational and transactional data to users via content delivery device.
Cherveny Kevin ; Crane Aaron ; Kaplan Lawrence M. ; Jasper John ; Shields Russell, System and method for updating, enhancing or refining a geographic database using feedback.
Cherveny, Kevin; Crane, Aaron; Kaplan, Lawrence M.; Jasper, John; Shields, Russel, System and method for updating, enhancing, or refining a geographic database using feedback.
Kaplan Craig A. (Santa Cruz CA) Chen James R. (Saratoga CA) Fallside David C. (San Jose CA) Fenwick Justine R. (Santa Cruz CA) Forcier Mitchell D. (Walnut Creek CA) Wolff Gregory J. (Mountain View CA, System for adjusting hypertext links with weighed user goals and activities.
Richardson-Bunbury, David; Riise, Soren; Patel, Devesh; Stipp, Eugene H.; Grealish, Paul J., System for determining probable meanings of inputted words.
Herz Frederick S. M. ; Eisner Jason M. ; Ungar Lyle H., System for generation of object profiles for a system for customized electronic identification of desirable objects.
Abrams,Jonathan H., System, method and apparatus for connecting users in an online computer system based on their relationships within social networks.
Shear Victor H. ; Van Wie David M. ; Weber Robert P., Systems and methods for matching, selecting, narrowcasting, and/or classifying based on rights management and/or other information.
Steinberg,Robert M.; Yurman,Ronald M.; Rosenberg,Jeremy C.; McGonigal,Daniel L.; Feras,John; DelBeccaro,David J.; Farber,Stuart H., Systems and methods for providing a broadcast entertainment service and an on-demand entertainment service.
Thompson, J. Patrick, Systems and methods for the implementation of a core schema for providing a top-level structure for organizing units of information manageable by a hardware/software interface system.
Higgins, Christopher W.; Paretti, Christopher T.; Ghezzi, Nicola Stefano; Spiegelman, Michael; Martinez, Ronald; Davis, Marc; Kalaboukis, Chris, System and method for presentation of media related to a context.
Higgins, Christopher W.; Paretti, Christopher T.; Ghezzi, Nicola Stefano; Spiegelman, Michael; Martinez, Ronald; Davis, Marc; Kalaboukis, Chris, System and method for presentation of media related to a context.
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