Logotipo do Freelancer Como Funciona Busque Trabalhos
Fazer Login Cadastrar
Publicar um Projeto
Profile cover photo
Agora você está seguindo .
Erro seguindo usuário.
Esse usuários não permite que o sigam.
Você já está seguindo esse usuário.
Seu plano permite apenas 0 seguidas. Aprimore-o aqui.
Deixou de seguir o usuário com sucesso.
Ocorreu um erro ao deixar de seguir o usuário.
Você recomendou com sucesso
Ocorreu um erro ao recomendar o usuário.
Algo deu errado. Por favor, atualize a página e tente novamente.
E-mail verificado com sucesso
Avatar do Usuário
 $10 USD / hora
Bandeira do(a) UNITED STATES
philadelphia, united states
$10 USD / hora
Atualmente, está 6:18 AM aqui
Ingressou em junho 2, 2012
0 Recomendações

Wenbin Z.

@iqlowest

 0,0 (0 avaliações)
0,0
0,0
0%
0%
$10 USD / hora
Bandeira do(a) UNITED STATES
philadelphia, united states
$10 USD / hora
Não se aplica
Trabalhos Concluídos
Não se aplica
Dentro do Orçamento
Não se aplica
No Prazo
Não se aplica
Taxa de Recontratação

University of Pennsylvania

Ready for Helping :-)
Freelancer C Programmers United States
Ver todos C Programmers em United States

Contate Wenbin Z. para falar sobre o seu trabalho

Entre para falar sobre qualquer detalhe pelo chat

Itens de Portfólio

We propose an anomaly detection system based on user profiling analysis to promote its performance. It presents a method to extract user's behavior by carefully choosing features of the user's data. It improves performance of Principle Component Analysis (PCA) algorithm by sampling and online PCA methods. In this way it fits the demands of anomaly detection systems and thus improves the efficiency and stability to achieve a better user profiling. In addition, we apply our model into applications of databases and web browsers. Using data mining methods we successfully deduce the parameters in our model and then deploy it in real environment.
User Profiling Analysis based Anomaly Detection System
We propose an anomaly detection system based on user profiling analysis to promote its performance. It presents a method to extract user's behavior by carefully choosing features of the user's data. It improves performance of Principle Component Analysis (PCA) algorithm by sampling and online PCA methods. In this way it fits the demands of anomaly detection systems and thus improves the efficiency and stability to achieve a better user profiling. In addition, we apply our model into applications of databases and web browsers. Using data mining methods we successfully deduce the parameters in our model and then deploy it in real environment.
User Profiling Analysis based Anomaly Detection System
We propose an anomaly detection system based on user profiling analysis to promote its performance. It presents a method to extract user's behavior by carefully choosing features of the user's data. It improves performance of Principle Component Analysis (PCA) algorithm by sampling and online PCA methods. In this way it fits the demands of anomaly detection systems and thus improves the efficiency and stability to achieve a better user profiling. In addition, we apply our model into applications of databases and web browsers. Using data mining methods we successfully deduce the parameters in our model and then deploy it in real environment.
User Profiling Analysis based Anomaly Detection System
Developed a lightweight single sign-on system based on plug-ins. Facilitated users to access multiple services via one authentication by combining browser, BHO and DOM technology into an integrated system. We have built a SSO model based on B / S structure.This model uses plug-in technology. Client starts local enterprise applications and interacts with SSO server through plug-in to complete the automatic login.There are two major concerns in the designing of this system: security and convenience. For security, data in the databases are stored encrypted. Data transmission between the two ends is secured by SSL protocol. For convenience, the browser plug-in is under unified management and distribution, thus toreduce the costs of maintaining and updating the client. And the system does not require additional operations that users can easily get started.
Single Sign-On System
We have developed a system to automatically categorize comments as positive or negative based on SVM. Predicted the rating of a review given its text and other properties from Amazon. In this project, we tried a lot of machine learning approaches to address sentiment analysis problems on Amazon. We first eliminated words that are non-related to ratings, most of which are objective words. We used methods including frequency-based word-probability, stemming, PCA and so on. Then we added many useful additional features, like data, title and bigram features. Furthermore, we tried and compared standard machine learning approaches. During the competition, we constantly utilized cross validation to evaluate our performance. After trying SVM, Adaboost, logistic regression, knn and our own kernel, we found that a combination of several features after performing PCA using liblinear could give the us best performance: RMSE of 0.8529.
Sentiment Analysis System for Amazon Views
In this project, we built a cloud-base search engine called MiniGoogle. Data of the system are crawled and computed based on distributed system. Final search result returned will sorted by page rank, value of TF/IDF and other 5 features. Users also have access to a friendly user interface which provides concise way of searching and visualization of search history. Search results can be returned in around 0.5 seconds. The project involves four parts, each of which is loosely coupled with the others: Crawler Indexer/TF-IDF Retrieval Engine PageRank Search Engine and User Interface
MiniGoogle
In this project, we built a cloud-base search engine called MiniGoogle. Data of the system are crawled and computed based on distributed system. Final search result returned will sorted by page rank, value of TF/IDF and other 5 features. Users also have access to a friendly user interface which provides concise way of searching and visualization of search history. Search results can be returned in around 0.5 seconds. The project involves four parts, each of which is loosely coupled with the others: Crawler Indexer/TF-IDF Retrieval Engine PageRank Search Engine and User Interface
MiniGoogle
In this project, we built a cloud-base search engine called MiniGoogle. Data of the system are crawled and computed based on distributed system. Final search result returned will sorted by page rank, value of TF/IDF and other 5 features. Users also have access to a friendly user interface which provides concise way of searching and visualization of search history. Search results can be returned in around 0.5 seconds. The project involves four parts, each of which is loosely coupled with the others: Crawler Indexer/TF-IDF Retrieval Engine PageRank Search Engine and User Interface
MiniGoogle
In this project, we built a cloud-base search engine called MiniGoogle. Data of the system are crawled and computed based on distributed system. Final search result returned will sorted by page rank, value of TF/IDF and other 5 features. Users also have access to a friendly user interface which provides concise way of searching and visualization of search history. Search results can be returned in around 0.5 seconds. The project involves four parts, each of which is loosely coupled with the others: Crawler Indexer/TF-IDF Retrieval Engine PageRank Search Engine and User Interface
MiniGoogle
In this project, we built a cloud-base search engine called MiniGoogle. Data of the system are crawled and computed based on distributed system. Final search result returned will sorted by page rank, value of TF/IDF and other 5 features. Users also have access to a friendly user interface which provides concise way of searching and visualization of search history. Search results can be returned in around 0.5 seconds. The project involves four parts, each of which is loosely coupled with the others: Crawler Indexer/TF-IDF Retrieval Engine PageRank Search Engine and User Interface
MiniGoogle

Avaliações

Mudanças salvas
Nenhuma avaliação aqui!

Experiência

RA

University of Pennsylvania
jan. 2012 - mai. 2012 (4 meses, 1 dia)
RA for the project "Accountable Virtual Machines" at University of Pennsylvania. Mainly responsible for the design of the deterministic replay component.

Internship

Huaxin Information Security Company, China
mai. 2010 - ago. 2010 (3 meses, 1 dia)
Gained experience in developing .NET security products and in configuring and maintaining network. Designed and implemented classification system for the protection of information as a final project.

Educação

Master of Science

University of Pennsylvania, United States 2011 - 2012
(1 ano)

Bachelor of Science

Northeastern University, China 2007 - 2011
(4 anos)

Publicações

Distributed Center-Controlled Based Network Auditing Architecture Design

ISAI 2010
Distributed Center-Controlled Based Network Auditing Architecture Design

Lightweight Single Sign-On System based on Plug-in Technology

ISAI 2010
Developed a lightweight single sign-on system based on plug-ins. Facilitated users to access multiple services via one authentication by combining browser, BHO and DOM technology into an integrated system.

Contate Wenbin Z. para falar sobre o seu trabalho

Entre para falar sobre qualquer detalhe pelo chat

Verificações

 Freelancer Preferencial
Identidade Verificada
Pagamento Verificado
Telefone Verificado
E-mail Verificado
Conectado ao Facebook

Certificações

freelancer_orientation.png Freelancer Orientation 1 75%

Principais Habilidades

C Programming
Java
JavaScript
XML
.NET

Busque Freelancers Parecidos

C Programmers in United States
C Programmers
Java Developers
Javascript Developers

Busque Mostruários Parecidos

C Programming
Java
JavaScript
XML
Usuário Anterior Usuário Seguinte
Convite enviado com sucesso!
Logotipo do Freelancer
 Brazil / Português
Ajuda & Suporte
 Freelancer Categories Projetos Contests Freelancers Enterprise Membership Preferred Freelancer Program Project Management Local Jobs Photo Anywhere Showcase API for Developers Get Verified Desktop App Sobre About us How it Works Security Investor Sitemap Stories News Team Awards Press Releases Careers Termos Privacy Policy Terms and Conditions Copyright Policy Code of Conduct Fees and Charges Parceiros Escrow.com Loadshift Warrior Forum AplicativosLogotipo da Loja de Apps da AppleLogotipo do Google Play
Não foi possível copiar para a área de transferência, por favor, tente novamente após ajustar suas permissões.
Copiado para a área de transferência.
Usuários Registrados Total de Trabalhos Publicados
Freelancer ® is a registered Trademark of Freelancer Technology Pty Limited (ACN 142 189 759)
Copyright © 2023 Freelancer Technology Pty Limited (ACN 142 189 759)
Carregando pré-visualização
Permissão concedida para Geolocalização.
Sua sessão expirou e você foi desconectado. Por favor, faça login novamente.