A method for leaving hierarchical-embedded reviews for verified transactions comprising: (i) receiving a first provider entity data set; (ii) creating a first provider portion of a first graph data structure; (iii) creating a first customer entity node in the first graph data structure; (iv) receiving a new transaction data set including information indicative of a business transaction between the first customer entity and a first provider sub-entity of the plurality of sub-entities; (v) creating a new transaction node in the first graph data structure, with the new transaction node including data from the first new transaction data set; (vi) creating a pairwise connection in the first graph data structure between the new transaction node and the lower level node corresponding to the first provider sub-entity; and (vii) creating a pairwise connection in the first graph data structure between the new transaction node and the first customer entity node.
Decentralized Management Of Software Configurations
- Armonk NY, US Tommy Chaoping Li - San Francisco CA, US Cindy Han Lu - San Jose CA, US Animesh Singh - Santa Clara CA, US Srinivas R. Brahmaroutu - San Jose CA, US
International Classification:
G06F 8/71 H04L 29/08 H04L 12/42
Abstract:
A peer-to-peer decentralized software configuration manager is described. The peer-to-peer system provides a crowdsourced mechanism to determine and recommend the efficient software configurations. A computer system may subscribe to a ring or group of network connected computers. Once subscribed, the computer system receives a ring data structure that may include one or more software configuration entries. The ring data structure is accessible to each subscribed computer system to the currently installed software configurations and document the relative success or failure of those configurations. The ring data structure may be utilized to identify a more efficient or user friendly software configuration that is currently installed and utilized by a subscribed computer system.
Resolution Of Edit Conflicts In Audio-File Development
- Armonk NY, US Animesh Singh - Santa Clara CA, US Cindy Han Lu - San Jose CA, US Nimesh Bhatia - San Jose CA, US Srinivas R. Brahmaroutu - San Jose CA, US
International Classification:
G10L 25/51 G06F 3/16 G06F 16/16 G06F 16/18
Abstract:
A processor may store a first version of an audio file and fragment the audio file into at least a first time segment. The processor may receive a first edit to the audio file and identify a first edited version of the first time segment in the first edit. The processor may update the first version of the audio file with the first edit, resulting in a second version of the audio file comprising the first edited version of the first time segment. The processor may receive a second edit to the first version of the audio file and identify a second edited version of the first time segment in the second edit. The processor may determine, based on the second edited version, that the second edit alters an outdated version of the first time segment, resulting in an edit conflict. The processor may notify a user of the conflict.
Interwoven Group Trip Itinerary Development Based On Social Footprints And Crowdsourcing
- Armonk NY, US Srinivas R. Brahmaroutu - San Jose CA, US Seyyed Vahid Hashemian - Redwood City CA, US Cindy Han Lu - San Jose CA, US Animesh Singh - Santa Clara CA, US Thai Quoc Tran - San Jose CA, US
International Classification:
G06Q 50/14 G06Q 50/00 G06Q 10/10 G06F 17/30
Abstract:
Approaches presented herein enable development of interwoven group trip itineraries based on social media footprints. More specifically, for each member of the group, a travel interests footprint is generated based on his/her social media history. These footprints are mapped together in a semantic web that includes identifiers associated with the interests of the footprints. Activities corresponding to a time and location are obtained and matched based on correlations to the interest-associated identifiers. Based on an association of a group member’ footprint to a semantic web identifier, and from there to an activity, itineraries are built for the members and activities are added to particular members' itineraries in which those members are likely to have an interest. Based on user-defined criteria, activities in the itineraries can be shared by the group as a whole or subgroups may be formed when the itineraries of some group members are assigned different activities.
Information Propagation Via Weighted Semantic And Social Graphs
- Armonk NY, US Seyyed Vahid Hashemian - Redwood City CA, US Cindy H. Lu - San Jose CA, US Thai Q. Tran - San Jose CA, US
International Classification:
G06F 17/30
Abstract:
Propagating information in a computer network, in one aspect, may include detecting an online action performed by a user on a content presented on a computer. The content may be annotated with an identifier. A semantic graph may be searched for a semantic node representing the identifier. The semantic graph may be searched for one or more other semantic nodes representing one or more other identifiers that meet a semantic similarity threshold based on weighted distances between the semantic node and the one or more other semantic nodes. One or more other users represented in a social graph may be determined that have interest in one or more topics represented by the identifier and the one or more other identifiers. The online action on the content may be propagated to the one or more other users.
Identification Of Target Audience For Content Delivery In Social Networks By Quantifying Semantic Relations And Crowdsourcing
- Armonk NY, US Seyyed Vahid Hashemian - Redwood City CA, US Arnaud J. Le Hors - Santa Clara CA, US Cindy H. Lu - San Jose CA, US Thai Q. Tran - San Jose CA, US
International Classification:
G06F 17/30
Abstract:
A mechanism is provided in a data processing system for content delivery. The mechanism identifies a candidate user of a social networking service. The candidate user has an associated profile including at least one concept of interest. The mechanism determines a probability that the candidate user is interested in an item of content based on a semantic similarity of the at least one concept of interest and at least one concept tag associated with the item of content using a weighted semantic graph. Responsive to the probability exceeding a probability threshold, the mechanism delivers the item of content to the candidate user. Responsive to receiving feedback comprising at least one action taken by the candidate user with respect to the item of content, the mechanism adjusts weights in the weighted semantic graph.
Identification Of Target Audience For Content Delivery In Social Networks By Quantifying Semantic Relations And Crowdsourcing
- Armonk NY, US Seyyed Vahid Hashemian - San Mateo CA, US Arnaud J. Le Hors - Santa Clara CA, US Cindy H. Lu - San Jose CA, US Thai Q. Tran - San Jose CA, US
International Classification:
G06F 17/30
Abstract:
A mechanism is provided in a data processing system for content delivery. The mechanism identifies a candidate user of a social networking service. The candidate user has an associated profile including at least one concept of interest. The mechanism determines a probability that the candidate user is interested in an item of content based on a semantic similarity of the at least one concept of interest and at least one concept tag associated with the item of content using a weighted semantic graph. Responsive to the probability exceeding a probability threshold, the mechanism delivers the item of content to the candidate user. Responsive to receiving feedback comprising at least one action taken by the candidate user with respect to the item of content, the mechanism adjusts weights in the weighted semantic graph.
Information Propagation Via Weighted Semantic And Social Graphs
- Armonk NY, US Seyyed Vahid Hashemian - San Mateo CA, US Cindy H. Lu - San Jose CA, US Thai Q. Tran - San Jose CA, US
International Classification:
G06F 17/30
Abstract:
Propagating information in a computer network, in one aspect, may include detecting an online action performed by a user on a content presented on a computer. The content may be annotated with an identifier. A semantic graph may be searched for a semantic node representing the identifier. The semantic graph may be searched for one or more other semantic nodes representing one or more other identifiers that meet a semantic similarity threshold based on weighted distances between the semantic node and the one or more other semantic nodes. One or more other users represented in a social graph may be determined that have interest in one or more topics represented by the identifier and the one or more other identifiers. The online action on the content may be propagated to the one or more other users.
Allied-THA San Francisco, CA May 2012 to Aug 2012 Publicity & Promotions InternCenter for Asian American Media (CAAM) San Francisco, CA May 2012 to Aug 2012 Development InternSoutheast Asian Berkeley, CA May 2011 to May 2012 External ChairFTW Group Oakland, CA May 2011 to Aug 2011 Marketing/Operations Intern
Education:
University of California, Berkeley Berkeley, CA May 2013 B.A. in Globalization & BusinessUniversity of Hong Kong Hong Kong, Hong Kong Island 2013 to 2013 Global Business in AsiaUniversity of Manchester Manchester Sep 2012
Skills:
Technical: Microsoft Word, Powerpoint, Excel, File Maker Pro, Adobe Photoshop, MAC OSC & Windows. Other: Logistical Planning, Social Media Marketing, working in both collaborative & independent environments