Review opinions search engine

Wouldn't it be great if you can instantly search user reviews and opinions on any products and services? And you do not want to waste time looking through all the reviews from all different reviews website? ReviewLab is there for you! ReviewLab.com is a one-stop reviews and opinions search...

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Bibliographic Details
Main Author: Dong, Wei
Other Authors: Chang Kuiyu
Format: Final Year Project
Language:English
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/10356/17022
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Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-17022
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spelling sg-ntu-dr.10356-170222023-03-03T20:43:53Z Review opinions search engine Dong, Wei Chang Kuiyu School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval Wouldn't it be great if you can instantly search user reviews and opinions on any products and services? And you do not want to waste time looking through all the reviews from all different reviews website? ReviewLab is there for you! ReviewLab.com is a one-stop reviews and opinions search engine with rich user interfaces for a wide variety of products and services. We promise to provide users with high quality reviews and opinions to make informed purchasing decisions. What's more? We are available in both Chinese and English languages, with still more language supports to come. Advanced machine learning and data mining techniques have been employed to build a back-end system that is robust, automated and intelligent. Our smart crawler engine is able to craw products information and raw reviews from many websites; our intelligent information extraction engine is able to discover useful and hidden information from huge amount of data; our sentiment classifier is able to train dataset and create models to classify user reviews. What's more? All these engines have been automated. Bachelor of Engineering (Computer Engineering) 2009-05-29T04:02:00Z 2009-05-29T04:02:00Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/17022 en Nanyang Technological University 93 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
spellingShingle DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
Dong, Wei
Review opinions search engine
description Wouldn't it be great if you can instantly search user reviews and opinions on any products and services? And you do not want to waste time looking through all the reviews from all different reviews website? ReviewLab is there for you! ReviewLab.com is a one-stop reviews and opinions search engine with rich user interfaces for a wide variety of products and services. We promise to provide users with high quality reviews and opinions to make informed purchasing decisions. What's more? We are available in both Chinese and English languages, with still more language supports to come. Advanced machine learning and data mining techniques have been employed to build a back-end system that is robust, automated and intelligent. Our smart crawler engine is able to craw products information and raw reviews from many websites; our intelligent information extraction engine is able to discover useful and hidden information from huge amount of data; our sentiment classifier is able to train dataset and create models to classify user reviews. What's more? All these engines have been automated.
author2 Chang Kuiyu
author_facet Chang Kuiyu
Dong, Wei
format Final Year Project
author Dong, Wei
author_sort Dong, Wei
title Review opinions search engine
title_short Review opinions search engine
title_full Review opinions search engine
title_fullStr Review opinions search engine
title_full_unstemmed Review opinions search engine
title_sort review opinions search engine
publishDate 2009
url http://hdl.handle.net/10356/17022
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