Sentimento - Opinion Mining System for Product Review / (Record no. 8840)

MARC details
000 -LEADER
fixed length control field 04322nam a22002537a 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 210112b2015 a|||f mb|| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency EG-CaNU
Transcribing agency EG-CaNU
041 0# - Language Code
Language code of text eng
Language code of abstract eng
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 610
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Emad Ashraf Samuel
245 1# - TITLE STATEMENT
Title Sentimento - Opinion Mining System for Product Review /
Statement of responsibility, etc. Emad Ashraf Samuel
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Date of publication, distribution, etc. 2015
300 ## - PHYSICAL DESCRIPTION
Extent 107 p.
Other physical details ill.
Dimensions 21 cm.
500 ## - GENERAL NOTE
Materials specified Supervisor: Samhaa El-Beltagy
502 ## - Dissertation Note
Dissertation type Thesis (M.A.)—Nile University, Egypt, 2015 .
504 ## - Bibliography
Bibliography "Includes bibliographical references"
505 0# - Contents
Formatted contents note Contents:<br/>CHAPTER 1: INTRODUCTION 1<br/>1.1. Motivation ............................................................................................2<br/>1.2. Background ..........................................................................................3<br/>1.3. Problem Definition..............................................................................5<br/>1.4. Proposed Solution ...............................................................................7<br/>1.5. Methodology ........................................................................................8<br/>1.6. Thesis Outline ....................................................................................11<br/>CHAPTER 2: LITERATURE REVIEW 13<br/>2.1 About Sentiment Analysis ...............................................................14<br/>2.2 Aspect-Based Sentiment Analysis Research .................................22<br/>2.3 Our Approach in Sentimento ..........................................................32<br/>CHAPTER 3: SYSTEM ARCHITECTURE 35<br/>3.1 What is Sentimento? .........................................................................36<br/>3.2 Sentimento’s Architecture ...............................................................37<br/>3.3 Sentimento’s Stages ..........................................................................38<br/>CHAPTER 4: ASPECTS EXTRACTION 45<br/>4.1 Aspect-Based Ontology ....................................................................46<br/>4.2 Aspects Extraction and Categorization in Sentimento ................52<br/>CHAPTER 5: SENTIMENT CLASSIFICATION 55<br/>5.1 Opinion Lexicon ................................................................................57<br/>5.2 Sentiment Classification in Sentimento .........................................60<br/>iv<br/>CHAPTER 6: EVALUATION 65<br/>6.1 Choosing Datasets For Evaluation .................................................67<br/>6.2 SemEval Datasets ..............................................................................69<br/>6.3 Evaluation of Aspects Extraction ....................................................71<br/>6.4 Evaluation of Sentiment Classification ..........................................73<br/>6.5 Evaluation of Other Parameters......................................................76<br/>CHAPTER 7: CONCLUSION 79<br/>7.1 Current Status of Sentimento ..........................................................80<br/>7.2 Future Work .......................................................................................81<br/>APPENDIX A – HOW TO USE SENTIMENTO 85<br/>APPENDIX B – SAMPLES FROM EVALUATION DATASET 91<br/>REFERENCES
520 3# - Abstract
Abstract Abstract:<br/>and more and more people are writing online reviews. These reviews are very important to give the real experience of products to potential customers and to the producing corporations. The number of reviews for some products may reach hundreds or even thousands. We need an automatic system that is able to summarize these reviews in a way that shows what exactly people like and dislike about the product. In this work, we develop Sentimento as an opinion mining system for online product reviews that is able to provide an aspect-based summary with accuracy close to an expert human reviewer and within an acceptable time. Sentimento is mainly divided to two tasks: aspects extraction and categorization, and opinions extraction and classification. The main idea is using ontology for the first task and opinion lexicon for the second task. Our experimental results using annotated test data on laptop reviews are promising for both tasks.
546 ## - Language Note
Language Note Text in English, abstracts in English.
650 #4 - Subject
Subject Informatics-IFM
655 #7 - Index Term-Genre/Form
Source of term NULIB
focus term Dissertation, Academic
690 ## - Subject
School Informatics-IFM
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Thesis
650 #4 - Subject
-- 266
655 #7 - Index Term-Genre/Form
-- 187
690 ## - Subject
-- 266
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Total Checkouts Full call number Date last seen Price effective from Koha item type
    Dewey Decimal Classification   Not For Loan Main library Main library 01/12/2021   610/ ES.S 2015 01/12/2021 01/12/2021 Thesis