Aspect based opinion mining on restaurant reviews

Aspect based opinion mining on restaurant reviews

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

Xehetasun bibliografikoak
Egile Nagusiak:	Tonmoy, Sazid Hasan, Ahmed, Faiyaj Bin, Sarkar, Madhurjya, Bashar, Mehejabin Binta, Ahmed, Rafi
Beste egile batzuk:	Sadeque, Farig Yousuf
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2024
Gaiak:	Opinion mining Aspect extraction Support vector machine Deep learning Customer feedback Data mining Machine learning
Sarrera elektronikoa:	http://hdl.handle.net/10361/23516

Antzeko izenburuak

A machine learning approach to detect depression and anxiety using supervised learning
nork: Ullas, Md Tahmidur Rahman, et al.
Argitaratua: (2019)

Where will you setup your business next?: a machine learning approach to suggest ideal geographical location for new restaurant establishment
nork: Shihab, Ibne Farabi, et al.
Argitaratua: (2018)

Pattern recognition with Quantum Support Vector Machine(QSVM) on near term quantum processors.
nork: Ahmed, Sajjad
Argitaratua: (2019)

Detection of fake identities on twitter using supervised machine learning
nork: Rahman, MD. Takiur, et al.
Argitaratua: (2019)

Gene classification and pattern analysis using data mining and machine learning techniques
nork: Ramisa, Aiman Jabeen, et al.
Argitaratua: (2021)

Automate crime news segmentation, knowledge-based generation and public opinion mining for social awareness
nork: Sabit, Ahmed Bin, et al.
Argitaratua: (2021)

Predicting depression in Bangladeshi undergraduates using machine learning
nork: Choudhury, Ahnaf Atef, et al.
Argitaratua: (2019)

Aspect-based sentiment analysis using SemEval and Amazon datasets
nork: Hasib, Tamanna, et al.
Argitaratua: (2018)

Detection of handwritten text using convolutional neural network
nork: Jasim, Rabib Bin, et al.
Argitaratua: (2024)

Yield prediction for precision agriculture using extreme gradient boosting and support vector regression
nork: Ahmed, Md. Sabbir, et al.
Argitaratua: (2021)

An implementation and analysis of deep learning models for the detection of wheat diseases
nork: Zubair, Ahmad, et al.
Argitaratua: (2024)

Detecting Adverse Drug Reaction (ADR) with data mining and predicting its intensity with machine learning
nork: Hussain, Nadib, et al.
Argitaratua: (2018)

Data analysis on the Bangladesh share market using Machine-Learning
nork: Sadman, Syed Hassan, et al.
Argitaratua: (2021)

Amazon product reviews sentiment analysis using supervised learning algorithms
nork: Hawladar, Mohibullah, et al.
Argitaratua: (2021)

Support vector machines: theory and applications /
Argitaratua: (2005)

An introduction to support vector machines : and other kernel-based learning methods /
nork: Cristianini, Nello
Argitaratua: (2000)

Predicting stock market movement using sentiment analysis of twitter feed
nork: Chakraborty, Pranjal, et al.
Argitaratua: (2017)

A machine learning approach to credit default prediction and Individual credit scoring
nork: Rahman, Md. Jaber, et al.
Argitaratua: (2018)

Hypothesizing precise cancer treatments based on patient survival using machine learning & deep learning
nork: Sakib, Hasibul, et al.
Argitaratua: (2024)

An efficient deep learning approach to classify white blood cells
nork: Turja, Afif Ibna Kadir Khan, et al.
Argitaratua: (2024)

Comparative analysis and implementation of credit risk prediction through distinct machine learning models
nork: Turjo, Aquib Abtahi, et al.
Argitaratua: (2021)

Emotion recognition from facial expression of autism spectrum disordered children using image processing and machine learning algorithms
nork: Tasnim, Nishat, et al.
Argitaratua: (2019)

Application of machine learning techniques on the context of livestock analysis
nork: Islam, Md. Shajedul, et al.
Argitaratua: (2018)

Detecting propagandistic poster title: a machine learning approach
nork: Mahmood, Riaz, et al.
Argitaratua: (2024)

A hybrid rumor detection model derived from a comparative study of supervised approaches
nork: Aothoi, Mehzabin Sadat, et al.
Argitaratua: (2023)

Credit card fraud detection using machine learning techniques
nork: Kabir, Tasmia, et al.
Argitaratua: (2021)

An effective machine learning approach for sentiment analysis of restaurant reviews
nork: Karim, Rabita
Argitaratua: (2018)

Performance analysis of machine learning classi ers for detecting PE malware
nork: Azmee, ABM.Adnan, et al.
Argitaratua: (2020)

Stock price prediction
nork: Das, Kaushik, et al.
Argitaratua: (2023)

A framework for sentiment analysis: a data-driven approach
nork: Islam, Md. Jahedul, et al.
Argitaratua: (2021)

A machine learning approach to predict young voter enthusiasm based on non-political factors
nork: Rahman, Md. Nowroz Junaed, et al.
Argitaratua: (2021)

Approaching (almost) any Machine learning problem /
nork: Thakur, Abhishek
Argitaratua: (2020)

Predicting criminal activities analyzing video signal using machine learning
nork: Sadman, Syed Md., et al.
Argitaratua: (2021)

Classi cation of magnetic configurations using machine learning algorithms
nork: Bokul, Saffat, et al.
Argitaratua: (2019)

Analysing Facebook user risk using machine learning algorithm
nork: Barua, Arnab, et al.
Argitaratua: (2021)

Medical image reader powered by artificial intelligence
nork: Palok, Tanvir Ahmed, et al.
Argitaratua: (2024)

Bangla text classification using machine learning and deep learning techniques
nork: Salehin, Kamrus, et al.
Argitaratua: (2021)

Travel time prediction using machine learning and weather impact on traffic conditions
nork: Deb, Bilash, et al.
Argitaratua: (2018)

Supervising vehicle using pattern recognition
nork: Lushan, Mihodi Hasan, et al.
Argitaratua: (2018)

Supershop management Models: An optimised way to manage the supershop using hyperautomation and machine learning
nork: Ahmed, Shuvro, et al.
Argitaratua: (2023)