Wei Peng

US Patent:

8312056, Nov 13, 2012

Filed:

Sep 13, 2011

Appl. No.:

13/231321

Inventors:

Wei Peng - Fremont CA, US
Tong Sun - Penfield NY, US

Assignee:

Xerox Corporation - Norwalk CT

International Classification:

G06F 17/30

US Classification:

707802, 705319

Abstract:

A system and method for identifying a key influencer in a social media environment for enterprise marketing utilizing topic modeling and social diffusion analysis. A user interest profile can be generated by analyzing historical data stored in a database utilizing. A social graph can be generated and an influence measuring process based on the social graph data can be performed utilizing a static diffusion model and a dynamic diffusion model to calculate a set of key influencers. The dynamic diffusion model considers time stamp information to assess an impact of each user communication on the growth of a conversation within a time period. The key influencer can be identified in a specific topic area and a number of total users that can be reached via the influencer within a specific time window can be predicted.

US Patent:

20120259616, Oct 11, 2012

Filed:

Apr 8, 2011

Appl. No.:

13/082963

Inventors:

Wei Peng - Sunnyvale CA, US
Dae Hoon Park - Champaign IL, US

Assignee:

Xerox Corporation - Norwalk CT

International Classification:

G06F 17/27

US Classification:

704 9, 704E11001

Abstract:

Embodiments generally relate to systems and methods for generating a sentiment dictionary and calculating sentiment scores of adjectives within the sentiment dictionary. A set of seed words can be identified and expanded using synonyms and antonyms of the set of seed words. Social media data can be parse to identify adjectives that link to the set of seed words with the words “and” or “but.” Matrices representing the attraction and repulsion among the linked adjectives can be generated. A factorization algorithm can be minimized to determine an output matrix that comprises positive and negative sentiment scores for each of the adjectives. In embodiments, a sentiment score for part of all of the social media data can be calculated using the output matrix, and one or more parts of the social media data can be classified as a positive or negative sentiment.

US Patent:

20130086072, Apr 4, 2013

Filed:

Oct 3, 2011

Appl. No.:

13/251731

Inventors:

Wei Peng - Fremont CA, US
Anuj Jaiswal - State College PA, US
Tong Sun - Penfield NY, US
Matthew DeRoller - Webster NY, US

Assignee:

XEROX CORPORATION - Norwalk CT

International Classification:

G06F 17/30

US Classification:

707743, 707754, 707E1711, 707E17018

Abstract:

Methods, systems and processor-readable media for extracting and classifying location information utilizing social media messages and/or data thereof. The social media messages can be sampled from a social media database and the messages filtered based on a heuristic rule. A geolocation entity from the unstructured social media messages can be extracted utilizing a geolocation entity extracting module. The messages with the geoentities can be uploaded onto a crowd sourcing platform to manually annotate the messages with a label. A text classification model can be built and learned from the label utilizing a machine learning algorithm and the messages can be classified by a location classifier in order to extract the user location. The user location can then be transformed into a geocode so that a spatial search can be enabled and the distance between the locations can be easily calculated.

US Patent:

20210110163, Apr 15, 2021

Filed:

Oct 13, 2020

Appl. No.:

17/069638

Inventors:

- Mountain View CA, US
Wei Peng - Fremont CA, US
Nicolas Crowell - San Francisco CA, US

International Classification:

G06K 9/00
G06K 9/62
G06N 5/02

Abstract:

In one aspect, a method includes obtaining videos and for each video: obtaining a set of anchors for the video, each anchor beginning at the playback time and including anchor text; identifying, from text generated from audio of the video, a set of entities specified in the text, wherein each entity in the set of entities is associated with a times stamp at which the entity is mentioned; determining, by a language model and from the text generated from the audio of the video, an importance value for each entity; for a subset of the videos, receiving rater data that describes, for each anchor, the accuracy of the anchor text in describing subject matter of the video; and training, using the human rater data, the importance values, the text, and the set of entities, an anchor model that predicts an entity label for an anchor for a video.

US Patent:

20150309962, Oct 29, 2015

Filed:

Apr 25, 2014

Appl. No.:

14/262391

Inventors:

- Norwalk CT, US
Wei Peng - Fremont CA, US
Tong Sun - Penfiled NY, US
Ming Yang - Fairport NY, US

Assignee:

Xerox Corporation - Norwalk CT

International Classification:

G06F 17/18
H04L 29/08
H04L 12/58

Abstract:

A method, non-transitory computer readable medium, and apparatus for predicting a location behavior of at least one individual are disclosed. For example, the method receives a plurality of social networking messages having spatial location data and user identification information, filters the plurality of social networking messages to remove one or more of the plurality of social networking messages that are not related to mobility of a user to create a filtered plurality of social networking messages, creates a population model by applying a kernel density estimation to the filtered plurality of social networking messages, creates an individual model for each different user identification by applying the kernel density estimation to a subset of the filtered plurality of social networking messages for the each different user identification and generates a probability density function map that predicts the location behavior of the at least one individual.

US Patent:

20140279618, Sep 18, 2014

Filed:

Mar 15, 2013

Appl. No.:

13/836233

Inventors:

- Norwalk CT, US
Wei Peng - Fremont CA, US
Saurabh Kataria - Webster NY, US
Tong Sun - Penfield NY, US

Assignee:

Xerox Corporation - Norwalk CT

International Classification:

G06Q 30/00
G06Q 50/00

US Classification:

705319

Abstract:

A method, non-transitory computer readable medium, and apparatus for recommending a topic-cohesive and interactive implicit community are disclosed. For example, the method receives a request for customer care, selects an implicit community identified from a plurality of individual users of a social media website based upon a relevance score related to a topic of the request for customer care and recommends the implicit community in response to the request for customer care.

US Patent:

20140250032, Sep 4, 2014

Filed:

Mar 1, 2013

Appl. No.:

13/782463

Inventors:

- Norwalk CT, US
Wei Peng - Sunnyvale CA, US
Jingxuan Li - Miami FL, US

Assignee:

Xerox Corporation - Norwalk CT

International Classification:

G06N 99/00

US Classification:

706 12

Abstract:

Methods, systems and processor-readable media for simultaneous sentiment analysis and topic classification with multiple labels. A sentiment and topic associated with a post can be classified at similar time and a result can be incorporated to predict a feature so that a label of two (or more) tasks can promote and reinforce each other iteratively. A feature extraction and selection can be performed on the tasks and a multi-task multi-label classification model can be trained for each task with maximum entropy utilizing multiple labels to ascertain information derived from an extra label and to manage class ambiguities. Each task has a separate classification model with different predicting features and they can be trained collectively which allows flexibility in model construction. The multi-task multi-label classification model produces a probabilistic result and the classes can be ranked by the probabilistic result and the post can be classified with the multi-label.