Rutgers, The State University of New Jersey-New Brunswick
2000 to 2005
Specialities:
Linguistics
Skills
Natural Language Processing • Computational Linguistics • Data Mining • Text Mining • Linguistics • Algorithms • Information Extraction • Machine Learning • Python • Research • Analysis • Data Analysis • Artificial Intelligence • Human Computer Interaction • Teaching • Syntax • Linux • Software Engineering • Social Media • Computer Science • Cognitive Science • Nlp • Psycholinguistics • Discourse Analysis • Java
Languages
English • Russian • Spanish
Interests
Argentine Tango • Sentiment Extraction From Texts • Computational Models of Humor • Science and Technology • Human Rights • Animal Welfare • Human Computer Interface • Discourse Analysis • Natural Language Processing • Health
Disney Online Studios Los Angeles
Computational Linguistics Engineer
NeuralIQ since 2008
Senior Data Mining Engineer
Simon Fraser University Sep 2007 - Sep 2008
Assistant Professor (Limited Term)
Pomona College Jan 2006 - Jul 2007
Visiting Assistant Professor
Education:
Rutgers, The State University of New Jersey-New Brunswick 2000 - 2005
Ph. D., Linguistics
New York University 1996 - 2000
BA, Linguistics
Skills:
Natural Language Processing Computational Linguistics Data Mining Text Mining Linguistics Algorithms Information Extraction Machine Learning Python Research Analysis Data Analysis Artificial Intelligence Human Computer Interaction Teaching Syntax Linux Software Engineering Social Media Computer Science Cognitive Science Nlp Psycholinguistics Discourse Analysis Java
Interests:
Argentine Tango Sentiment Extraction From Texts Computational Models of Humor Science and Technology Human Rights Animal Welfare Human Computer Interface Discourse Analysis Natural Language Processing Health
Vita G. Markman - Los Angeles CA, US Michael Veprinsky - Encino CA, US Roger H. Hughston - Lancaster CA, US Andrew R. Beechum - Pasadena CA, US Arkady G. Trestman - Sherman Oaks CA, US
International Classification:
G06F 17/28 G06F 17/27
US Classification:
704 2, 704 9
Abstract:
Techniques are disclosed for generating phrases for selection by users communicating in an online virtual world environment. A phrase generation engine automatically constructs new phrases using pre-approved words from a dictionary of frequently used words and language-specific rules for phrase formation to ensure safety and supplement an existing database of commonly used, pre-approved phrases. Increasing the number of phrases that are available for selection by a user increases the user expressivity. Each word in the dictionary is annotated with semantic and grammatical information that constrains how the word is combined with other words to generate a new phrase. Each new phrase may also be tagged to enable translation into a different language so a phrase in a first language selected by a first user may be displayed in a second language to a second user.
VITA MARKMAN - LOS ANGELES CA, US SEAN O'DELL - WEST HILLS CA, US ARKADY TRESTMAN - SHERMAN OAKS CA, US DREW BEECHUM - PASADENA CA, US PAUL PAK - NORTH HOLLYWOOD CA, US STEPHANE JANKOWSKI - KELOWNA, CA MARC SILBEY - MERCER ISLAND WA, US KIP MARTIN - LOS ANGELES CA, US KEVIN O'SULLIVAN - LOS ANGELES CA, US CHRISTIAN SHRIGLEY - SIMI VALLEY CA, US LANE MERRIFIELD - KELOWNA, CA
Assignee:
DISNEY ENTERPRISES, INC. - BURBANK CA
International Classification:
G06F 17/30
US Classification:
707794, 707E17099
Abstract:
Techniques are disclosed for supplying users in an online environment with a safe and effective chat facility. The chat facility is “safe” in the sense that the ability of users to compose inappropriate messages is greatly restricted, while “effective” in the sense that users are still allowed a broad range of expressivity in composing and exchanging chat messages.
VITA MARKMAN - LOS ANGELES CA, US SEAN O'DELL - WEST HILLS CA, US ARKADY TRESTMAN - SHERMAN OAKS CA, US DREW BEECHUM - PASADENA CA, US PAUL PAK - NORTH HOLLYWOOD CA, US CHRISTIAN SHRIGLEY - SIMI VALLEY CA, US
Assignee:
DISNEY ENTERPRISES, INC. - BURBANK CA
International Classification:
G06F 15/16
US Classification:
715758
Abstract:
Techniques are disclosed for supplying users in an online environment with a safe and effective chat facility. The chat facility is “safe” in the sense that the ability of users to compose inappropriate messages is greatly restricted, while “effective” in the sense that users are still allowed a broad range of expressivity in composing and exchanging chat messages.
Contextual Chat Message Generation In Online Environments
Cyrus J. Hoomani - Studio City CA, US Vita Markman - Los Angeles CA, US
Assignee:
DISNEY ENTERPRISES, INC. - Burbank CA
International Classification:
G06F 3/00
US Classification:
715758
Abstract:
Techniques are disclosed for providing an enhanced contextual chat feature in online environments. The contextual chat feature may be used to present users with a list of expressions that may be sent to other users within an online environment (or to users in other online environments). The list of messages may be derived from a linguistic profile which itself may change as the use of language in an online environment (or by a particular user group) evolves, over time. In cases where a user sends a contextual chat message to another user in the same online environment, messages may be sent without being altered. However, when a user selects a contextual chat message from the list to send to a user in another online environment, the message may be translated based on a linguistic profile associated with users in the second environment.
Cyrus J. Hoomani - Studio City CA, US Vita Markman - Los Angeles CA, US
Assignee:
DISNEY ENTERPRISES, INC. - Burbank CA
International Classification:
G06F 3/01 G06F 15/16
US Classification:
715758
Abstract:
Techniques are disclosed for providing an enhanced contextual chat feature in online environments. The contextual chat feature may be used to present users with a list of expressions that may be sent to other users within an online environment (or to users in other online environments). The list of messages may be derived from a linguistic profile which itself may change as the use of language in an online environment (or by a particular user group) evolves, over time. In cases where a user sends a contextual chat message to another user in the same online environment, messages may be sent without being altered. However, when a user selects a contextual chat message from the list to send to a user in another online environment, the message may be translated based on a linguistic profile associated with users in the second environment.
Discovery, Extraction, And Recommendation Of Talent-Screening Questions
Methods, systems, and computer programs are presented for automatically generating phrase-based talent-screening questions. One method includes analyzing job descriptions to generate ngrams. Each ngram comprises one or more words. Further, the method includes identifying, from the ngrams, an ngram set comprising a predetermined number of bigrams and trigrams according to frequency of appearance in the job descriptions. The method further includes removing, from the ngram set, bigrams and trigrams comprising one or more of stop words, negation words, or requirement words, to obtain first seed phrases. The first seed phrases are filtered based on a frequency of appearance of the seed phrase in the job descriptions to obtain second seed phrases. Further, the second seed phrases are added to the first seed phrases to obtain third seed phrases. Each seed phrase is a sequence of one or more words that is associated with a category of talent-screening questions.
- Redmond WA, US Vita G. Markman - San Francisco CA, US
Assignee:
Microsoft Technology Licensing, LLC - Redmond WA
International Classification:
G06F 17/27 G06F 17/28 G06N 20/00
Abstract:
Methods, systems, and computer programs are presented for estimating the language used in a user communication. One method includes an operation for utilizing counters to track use of languages by a user of an online service, the counters being updated based on interactions of the user in the online service. Further, the method includes operations for detecting a text entered by the user and obtaining, by a language classifier, an initial prediction having probabilities for the languages that the text is in the language. A language distribution prediction is calculated based on the initial prediction and the user counters, where the language distribution prediction comprises a probability, for each language, that the text is in the language. Further, the method includes operations for selecting a language used in the text based on the language distribution prediction and causing presentation on a display of a message in the selected language.
Determination Of Languages Spoken By A Member Of A Social Network
- Sunnyvale CA, US Ajay Srivastava - Milpitas CA, US Vita Markman - San Francisco CA, US
International Classification:
G06F 17/27 G06Q 50/00
Abstract:
Methods, systems, and computer programs are presented for determining languages spoken by a user based on analysis of the information and activities of the user. One method includes an operation for extracting values for features, associated with a user of a social network, related to a language. Each feature is a primary or a secondary feature. For each primary feature, a determination is made whether the value of the feature exceeds a threshold. The method further includes operations for determining that the user speaks the language when at least one primary feature exceeds the respective threshold, and when no primary feature exceeds the respective threshold, analyzing values of the primary and secondary features to determine if the user speaks the language. The determination that the user speaks the language is stored in the user profile, and the user interface of the social network is customized based on the language.
Youtube
Magic of Tango, June 6, 2009 - Followers can ...
Leaders and Followers in Tango. Exhibition by Elena Alexandra and Vita...