Search Results for author: Asif Ekbal

Found 133 papers, 15 papers with code

Novelty Detection: A Perspective from Natural Language Processing

no code implementations CL (ACL) 2022 Tirthankar Ghosal, Tanik Saikh, Tameesh Biswas, Asif Ekbal, Pushpak Bhattacharyya

In this work, we build upon our earlier investigations for document-level novelty detection and present a comprehensive account of our efforts toward the problem.

Natural Language Inference Natural Language Processing

SEPRG: Sentiment aware Emotion controlled Personalized Response Generation

no code implementations INLG (ACL) 2021 Mauajama Firdaus, Umang Jain, Asif Ekbal, Pushpak Bhattacharyya

We design a Transformer based Dialogue Generation framework, that generates responses that are sensitive to the emotion of the user and corresponds to the persona and sentiment as well.

Dialogue Generation Response Generation

Team IITP-AINLPML at WASSA 2022: Empathy Detection, Emotion Classification and Personality Detection

no code implementations WASSA (ACL) 2022 Soumitra Ghosh, Dhirendra Maurya, Asif Ekbal, Pushpak Bhattacharyya

Computational comprehension and identifying emotional components in language have been critical in enhancing human-computer connection in recent years.

Emotion Classification

Unknown Intent Detection Using Multi-Objective Optimization on Deep Learning Classifiers

no code implementations RANLP 2021 Prerna Prem, Zishan Ahmad, Asif Ekbal, Shubhashis Sengupta, Sakshi C. Jain, Roshni Ramnani

This task of separating the unknown intent samples from known intents one is challenging as the unknown user intent can range from intents similar to the predefined intents to something completely different.

Intent Detection Intent Discovery

Only text? only image? or both? Predicting sentiment of internet memes

no code implementations ICON 2020 Pranati Behera, Mamta ., Asif Ekbal

We propose a multi-modal framework for meme sentiment classification by utilizing textual and visual features of the meme.

Classification Meme Classification +1

A Multi-task Model for Multilingual Trigger Detection and Classification

no code implementations ICON 2019 Sovan Kumar Sahoo, Saumajit Saha, Asif Ekbal, Pushpak Bhattacharyya

In this paper we present a deep multi-task learning framework for multilingual event and argument trigger detection and classification.

Classification Multi-Task Learning

A Deep Ensemble Framework for Fake News Detection and Multi-Class Classification of Short Political Statements

no code implementations ICON 2019 Arjun Roy, Kingshuk Basak, Asif Ekbal, Pushpak Bhattacharyya

Fake news, rumor, incorrect information, and misinformation detection are nowadays crucial issues as these might have serious consequences for our social fabrics.

Fake News Detection Misinformation +1

Modelling Source- and Target- Language Syntactic Information as Conditional Context in Interactive Neural Machine Translation

no code implementations EAMT 2020 Kamal Kumar Gupta, Rejwanul Haque, Asif Ekbal, Pushpak Bhattacharyya, Andy Way

In this study, we model source-language syntactic constituency parse and target-language syntactic descriptions in the form of supertags as conditional context for interactive prediction in neural MT (NMT).

Machine Translation Translation

Product Review Translation using Phrase Replacement and Attention Guided Noise Augmentation

no code implementations MTSummit 2021 Kamal Gupta, Soumya Chennabasavaraj, Nikesh Garera, Asif Ekbal

Given that 44% of Indian population speaks and operates in Hindi language and we address the above challenges by presenting an English–to–Hindi neural machine translation (NMT) system to translate the product reviews available on e-commerce websites by creating an in-domain parallel corpora and handling various types of noise in reviews via two data augmentation techniques and viz.

Data Augmentation Machine Translation +1

Sentiment Preservation in Review Translation using Curriculum-based Re-inforcement Framework

no code implementations MTSummit 2021 Divya Kumari, Soumya Chennabasavaraj, Nikesh Garera, Asif Ekbal

Machine Translation (MT) systems often fail to preserve different stylistic and pragmatic properties of the source text (e. g. sentiment and emotion and gender traits and etc.)

Machine Translation Natural Language Processing +2

Commonsense and Named Entity Aware Knowledge Grounded Dialogue Generation

1 code implementation27 May 2022 Deeksha Varshney, Akshara Prabhakar, Asif Ekbal

In this paper, we present a novel open-domain dialogue generation model which effectively utilizes the large-scale commonsense and named entity based knowledge in addition to the unstructured topic-specific knowledge associated with each utterance.

Dialogue Generation

Am I No Good? Towards Detecting Perceived Burdensomeness and Thwarted Belongingness from Suicide Notes

no code implementations20 May 2022 Soumitra Ghosh, Asif Ekbal, Pushpak Bhattacharyya

The World Health Organization (WHO) has emphasized the importance of significantly accelerating suicide prevention efforts to fulfill the United Nations' Sustainable Development Goal (SDG) objective of 2030.

COVIDRead: A Large-scale Question Answering Dataset on COVID-19

no code implementations5 Oct 2021 Tanik Saikh, Sovan Kumar Sahoo, Asif Ekbal, Pushpak Bhattacharyya

This dataset creates a new avenue of carrying out research on COVID-19 by providing a benchmark dataset and a baseline model.

Question Answering

Towards Developing a Multilingual and Code-Mixed Visual Question Answering System by Knowledge Distillation

no code implementations Findings (EMNLP) 2021 Humair Raj Khan, Deepak Gupta, Asif Ekbal

We also create the large-scale multilingual and code-mixed VQA dataset in eleven different language setups considering the multiple Indian and European languages.

Knowledge Distillation Question Answering +2

M2H2: A Multimodal Multiparty Hindi Dataset For Humor Recognition in Conversations

1 code implementation3 Aug 2021 Dushyant Singh Chauhan, Gopendra Vikram Singh, Navonil Majumder, Amir Zadeh, Asif Ekbal, Pushpak Bhattacharyya, Louis-Philippe Morency, Soujanya Poria

We propose several strong multimodal baselines and show the importance of contextual and multimodal information for humor recognition in conversations.

Dialogue Understanding

IITP at WAT 2021: System description for English-Hindi Multimodal Translation Task

no code implementations ACL (WAT) 2021 Baban Gain, Dibyanayan Bandyopadhyay, Asif Ekbal

Neural Machine Translation (NMT) is a predominant machine translation technology nowadays because of its end-to-end trainable flexibility.

Machine Translation Translation

IITP@COLIEE 2019: Legal Information Retrieval using BM25 and BERT

1 code implementation17 Apr 2021 Baban Gain, Dibyanayan Bandyopadhyay, Tanik Saikh, Asif Ekbal

We make use of different Information Retrieval(IR) and deep learning based approaches to tackle these problems.

Information Retrieval Natural Language Processing

Modelling Context Emotions using Multi-task Learning for Emotion Controlled Dialog Generation

no code implementations EACL 2021 Deeksha Varshney, Asif Ekbal, Pushpak Bhattacharyya

We employ multi-task learning to predict the emotion label and to generate a viable response for a given utterance using a common encoder with multiple decoders.

Multi-Task Learning Response Generation +1

Leveraging Multi-domain, Heterogeneous Data using Deep Multitask Learning for Hate Speech Detection

no code implementations ICON 2020 Prashant Kapil, Asif Ekbal

With the exponential rise in user-generated web content on social media, the proliferation of abusive languages towards an individual or a group across the different sections of the internet is also rapidly increasing.

Hate Speech Detection Multi-Task Learning

EmotionGIF-IITP-AINLPML: Ensemble-based Automated Deep Neural System for predicting category(ies) of a GIF response

no code implementations23 Dec 2020 Soumitra Ghosh, Arkaprava Roy, Asif Ekbal, Pushpak Bhattacharyya

In this paper, we describe the systems submitted by our IITP-AINLPML team in the shared task of SocialNLP 2020, EmotionGIF 2020, on predicting the category(ies) of a GIF response for a given unlabelled tweet.

IITP-AINLPML at SemEval-2020 Task 12: Offensive Tweet Identification and Target Categorization in a Multitask Environment

no code implementations SEMEVAL 2020 Soumitra Ghosh, Asif Ekbal, Pushpak Bhattacharyya

In this paper, we describe the participation of IITP-AINLPML team in the SemEval-2020 SharedTask 12 on Offensive Language Identification and Target Categorization in English Twitter data.

Language Identification

Hostility Detection Dataset in Hindi

1 code implementation6 Nov 2020 Mohit Bhardwaj, Md Shad Akhtar, Asif Ekbal, Amitava Das, Tanmoy Chakraborty

In this paper, we present a novel hostility detection dataset in Hindi language.

MultiDM-GCN: Aspect-guided Response Generation in Multi-domain Multi-modal Dialogue System using Graph Convolutional Network

no code implementations Findings of the Association for Computational Linguistics 2020 Mauajama Firdaus, Nidhi Thakur, Asif Ekbal

In this work, we present a multi-modal conversational framework for a task-oriented dialogue setup that generates the responses following the different aspects of a product or service to cater to the user{'}s needs.

Response Generation

Hierarchical Deep Multi-modal Network for Medical Visual Question Answering

1 code implementation27 Sep 2020 Deepak Gupta, Swati Suman, Asif Ekbal

To address this issue, we propose a hierarchical deep multi-modal network that analyzes and classifies end-user questions/queries and then incorporates a query-specific approach for answer prediction.

Medical Visual Question Answering Question Answering +2

Assessing the Severity of Health States based on Social Media Posts

no code implementations21 Sep 2020 Shweta Yadav, Joy Prakash Sain, Amit Sheth, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya

The diverse NLU views demonstrate its effectiveness on both the tasks and as well as on the individual disease to assess a user's health.

Multiview Learning Natural Language Understanding

Relation Extraction from Biomedical and Clinical Text: Unified Multitask Learning Framework

no code implementations20 Sep 2020 Shweta Yadav, Srivatsa Ramesh, Sriparna Saha, Asif Ekbal

Towards this, we model the relation extraction problem in multi-task learning (MTL) framework and introduce for the first time the concept of structured self-attentive network complemented with the adversarial learning approach for the prediction of relationships from the biomedical and clinical text.

Multi-Task Learning Relation Extraction

Sentiment and Emotion help Sarcasm? A Multi-task Learning Framework for Multi-Modal Sarcasm, Sentiment and Emotion Analysis

no code implementations ACL 2020 Dushyant Singh Chauhan, Dhanush S R, Asif Ekbal, Pushpak Bhattacharyya

In this paper, we hypothesize that sarcasm is closely related to sentiment and emotion, and thereby propose a multi-task deep learning framework to solve all these three problems simultaneously in a multi-modal conversational scenario.

Emotion Recognition Multi-Task Learning +2

Investigating Deep Learning Approaches for Hate Speech Detection in Social Media

no code implementations29 May 2020 Prashant Kapil, Asif Ekbal, Dipankar Das

Moreover, the varieties in user-generated data and the presence of various forms of hate speech makes it very challenging to identify the degree and intention of the message.

Hate Speech Detection

A Deep Learning Approach for Automatic Detection of Fake News

1 code implementation ICON 2019 Tanik Saikh, Arkadipta De, Asif Ekbal, Pushpak Bhattacharyya

We evaluate our techniques on the two recently released datasets, namely FakeNews AMT and Celebrity for fake news detection.

Fake News Detection Feature Engineering

ScholarlyRead: A New Dataset for Scientific Article Reading Comprehension

no code implementations LREC 2020 Tanik Saikh, Asif Ekbal, Pushpak Bhattacharyya

We present ScholarlyRead, span-of-word-based scholarly articles{'} Reading Comprehension (RC) dataset with approximately 10K manually checked passage-question-answer instances.

Question Answering Reading Comprehension

Multi-domain Tweet Corpora for Sentiment Analysis: Resource Creation and Evaluation

no code implementations LREC 2020 Mamta ., Asif Ekbal, Pushpak Bhattacharyya, Shikha Srivastava, Alka Kumar, Tista Saha

Due to the phenomenal growth of online content in recent time, sentiment analysis has attracted attention of the researchers and developers.

Sentiment Analysis

CEASE, a Corpus of Emotion Annotated Suicide notes in English

no code implementations LREC 2020 Soumitra Ghosh, Asif Ekbal, Pushpak Bhattacharyya

In this paper, we create a fine-grained emotion annotated corpus (CEASE) of suicide notes in English and develop various deep learning models to perform emotion detection on the curated dataset.

A Platform for Event Extraction in Hindi

no code implementations LREC 2020 Sovan Kumar Sahoo, Saumajit Saha, Asif Ekbal, Pushpak Bhattacharyya

In this paper, we present an Event Extraction framework for Hindi language by creating an annotated resource for benchmarking, and then developing deep learning based models to set as the baselines.

Classification Event Extraction +2

Incorporating Politeness across Languages in Customer Care Responses: Towards building a Multi-lingual Empathetic Dialogue Agent

no code implementations LREC 2020 Mauajama Firdaus, Asif Ekbal, Pushpak Bhattacharyya

Our system is competent in generating responses in different languages (here, English and Hindi) depending on the customer{'}s preference and also is able to converse with humans in an empathetic manner to ensure customer satisfaction and retention.

Reinforced Multi-task Approach for Multi-hop Question Generation

no code implementations COLING 2020 Deepak Gupta, Hardik Chauhan, Akella Ravi Tej, Asif Ekbal, Pushpak Bhattacharyya

Question generation (QG) attempts to solve the inverse of question answering (QA) problem by generating a natural language question given a document and an answer.

Multi-hop Question Answering Question Answering +1

Related Tasks can Share! A Multi-task Framework for Affective language

no code implementations6 Feb 2020 Kumar Shikhar Deep, Md. Shad Akhtar, Asif Ekbal, Pushpak Bhattacharyya

Expressing the polarity of sentiment as 'positive' and 'negative' usually have limited scope compared with the intensity/degree of polarity.

Multi-Task Learning Sentiment Analysis

A Deep Neural Framework for Contextual Affect Detection

no code implementations28 Jan 2020 Kumar Shikhar Deep, Asif Ekbal, Pushpak Bhattacharyya

A short and simple text carrying no emotion can represent some strong emotions when reading along with its context, i. e., the same sentence can express extreme anger as well as happiness depending on its context.

Word Embeddings

Emotion helps Sentiment: A Multi-task Model for Sentiment and Emotion Analysis

no code implementations28 Nov 2019 Abhishek Kumar, Asif Ekbal, Daisuke Kawahra, Sadao Kurohashi

Our network also boosts the performance of emotion analysis by 5 F-score points on Stance Sentiment Emotion Corpus.

Emotion Recognition Sentiment Analysis

Sentiment-Aware Recommendation System for Healthcare using Social Media

no code implementations18 Sep 2019 Alan Aipe, Mukuntha Narayanan Sundararaman, Asif Ekbal

Over the last decade, health communities (known as forums) have evolved into platforms where more and more users share their medical experiences, thereby seeking guidance and interacting with people of the community.

Sentiment Analysis

Parallel Corpus Filtering Based on Fuzzy String Matching

no code implementations WS 2019 Sukanta Sen, Asif Ekbal, Pushpak Bhattacharyya

Based on the scores, we sub-sample two sets (having 1 million and 5 millions English tokens) of parallel sentences from each parallel corpus, and train SMT systems for development purpose only.

DeepSentiPeer: Harnessing Sentiment in Review Texts to Recommend Peer Review Decisions

1 code implementation ACL 2019 Tirthankar Ghosal, Rajeev Verma, Asif Ekbal, Pushpak Bhattacharyya

However, the peer review texts, which contains rich sentiment information of the reviewer, reflecting his/her overall attitude towards the research in the paper, could be a valuable entity to predict the acceptance or rejection of the manuscript under consideration.

Multilingual Unsupervised NMT using Shared Encoder and Language-Specific Decoders

no code implementations ACL 2019 Sukanta Sen, Kamal Kumar Gupta, Asif Ekbal, Pushpak Bhattacharyya

In this paper, we propose a multilingual unsupervised NMT scheme which jointly trains multiple languages with a shared encoder and multiple decoders.

Denoising Translation

Courteously Yours: Inducing courteous behavior in Customer Care responses using Reinforced Pointer Generator Network

no code implementations NAACL 2019 Hitesh Golchha, Mauajama Firdaus, Asif Ekbal, Pushpak Bhattacharyya

We use real interactions on Twitter between customer care professionals and aggrieved customers to create a large conversational dataset having both forms of agent responses: {`}generic{'} and {`}courteous{'}.

NLP at SemEval-2019 Task 6: Detecting Offensive language using Neural Networks

no code implementations SEMEVAL 2019 Prashant Kapil, Asif Ekbal, Dipankar Das

The three best models that performed best on individual sub tasks are stacking of CNN-Bi-LSTM with Attention, BiLSTM with POS information added with word features and Bi-LSTM for third task.

POS

Relation extraction between the clinical entities based on the shortest dependency path based LSTM

no code implementations24 Mar 2019 Dhanachandra Ningthoujam, Shweta Yadav, Pushpak Bhattacharyya, Asif Ekbal

In this paper, we present an efficient relation extraction system based on the shortest dependency path (SDP) generated from the dependency parsed tree of the sentence.

Relation Extraction

A Deep Ensemble Framework for Fake News Detection and Classification

no code implementations12 Nov 2018 Arjun Roy, Kingshuk Basak, Asif Ekbal, Pushpak Bhattacharyya

Fake news, rumor, incorrect information, and misinformation detection are nowadays crucial issues as these might have serious consequences for our social fabrics.

Fake News Detection General Classification +1

Helping each Other: A Framework for Customer-to-Customer Suggestion Mining using a Semi-supervised Deep Neural Network

no code implementations1 Nov 2018 Hitesh Golchha, Deepak Gupta, Asif Ekbal, Pushpak Bhattacharyya

We evaluate the performance of our proposed model on a benchmark customer review dataset, comprising of the reviews of Hotel and Electronics domains.

Sentiment Analysis Suggestion mining

Time-Aware and Corpus-Specific Entity Relatedness

no code implementations23 Oct 2018 Nilamadhaba Mohapatra, Vasileios Iosifidis, Asif Ekbal, Stefan Dietze, Pavlos Fafalios

Entity relatedness has emerged as an important feature in a plethora of applications such as information retrieval, entity recommendation and entity linking.

Entity Linking Information Retrieval +1

Uncovering Code-Mixed Challenges: A Framework for Linguistically Driven Question Generation and Neural Based Question Answering

no code implementations CONLL 2018 Deepak Gupta, Pabitra Lenka, Asif Ekbal, Pushpak Bhattacharyya

In this paper, we propose a linguistically motivated technique for code-mixed question generation (CMQG) and a neural network based architecture for code-mixed question answering (CMQA).

Question Answering Question Generation

A Multi-task Ensemble Framework for Emotion, Sentiment and Intensity Prediction

no code implementations3 Aug 2018 Md. Shad Akhtar, Deepanway Ghosal, Asif Ekbal, Pushpak Bhattacharyya, Sadao Kurohashi

In this paper, through multi-task ensemble framework we address three problems of emotion and sentiment analysis i. e. "emotion classification & intensity", "valence, arousal & dominance for emotion" and "valence & arousal} for sentiment".

Emotion Classification General Classification +1

Leveraging Medical Sentiment to Understand Patients Health on Social Media

no code implementations30 Jul 2018 Shweta Yadav, Joy Sain, Amit Sheth, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya

A large percentage of this population is actively engaged in health social networks to share health-related information.

Feature Assisted bi-directional LSTM Model for Protein-Protein Interaction Identification from Biomedical Texts

no code implementations5 Jul 2018 Shweta Yadav, Ankit Kumar, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya

In this paper, we present a novel method based on deep bidirectional long short-term memory (B-LSTM) technique that exploits word sequences and dependency path related information to identify PPI information from text.

Fine-Grained Temporal Orientation and its Relationship with Psycho-Demographic Correlates

no code implementations NAACL 2018 Sabyasachi Kamila, Mohammed Hasanuzzaman, Asif Ekbal, Pushpak Bhattacharyya, Andy Way

In this paper, we propose a very first study to demonstrate the association between the sentiment view of the temporal orientation of the users and their different psycho-demographic attributes by analyzing their tweets.

Decision Making

Multi-Task Learning Framework for Mining Crowd Intelligence towards Clinical Treatment

no code implementations NAACL 2018 Shweta Yadav, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya, Amit Sheth

In this paper, we adopt a novel adversarial learning approach for our multi-task learning framework to learn the sentiment{'}s strengths expressed in a medical blog.

General Classification Multi-Task Learning +1

TAP-DLND 1.0 : A Corpus for Document Level Novelty Detection

2 code implementations LREC 2018 Tirthankar Ghosal, Amitra Salam, Swati Tiwari, Asif Ekbal, Pushpak Bhattacharyya

Detecting novelty of an entire document is an Artificial Intelligence (AI) frontier problem that has widespread NLP applications, such as extractive document summarization, tracking development of news events, predicting impact of scholarly articles, etc.

Document Summarization Extractive Document Summarization +2

Auto Analysis of Customer Feedback using CNN and GRU Network

1 code implementation12 Oct 2017 Deepak Gupta, Pabitra Lenka, Harsimran Bedi, Asif Ekbal, Pushpak Bhattacharyya

Analyzing customer feedback is the best way to channelize the data into new marketing strategies that benefit entrepreneurs as well as customers.

A Multilayer Perceptron based Ensemble Technique for Fine-grained Financial Sentiment Analysis

no code implementations EMNLP 2017 Md. Shad Akhtar, Abhishek Kumar, Deepanway Ghosal, Asif Ekbal, Pushpak Bhattacharyya

In this paper, we propose a novel method for combining deep learning and classical feature based models using a Multi-Layer Perceptron (MLP) network for financial sentiment analysis.

Sentiment Analysis Stock Prediction +1

IITP at SemEval-2017 Task 5: An Ensemble of Deep Learning and Feature Based Models for Financial Sentiment Analysis

no code implementations SEMEVAL 2017 Deepanway Ghosal, Shobhit Bhatnagar, Md. Shad Akhtar, Asif Ekbal, Pushpak Bhattacharyya

In this paper we propose an ensemble based model which combines state of the art deep learning sentiment analysis algorithms like Convolution Neural Network (CNN) and Long Short Term Memory (LSTM) along with feature based models to identify optimistic or pessimistic sentiments associated with companies and stocks in financial texts.

Sentiment Analysis

Temporal Orientation of Tweets for Predicting Income of Users

no code implementations ACL 2017 Mohammed Hasanuzzaman, Sabyasachi Kamila, M Kaur, eep, Sriparna Saha, Asif Ekbal

Automatically estimating a user{'}s socio-economic profile from their language use in social media can significantly help social science research and various downstream applications ranging from business to politics.

TAG

SMPOST: Parts of Speech Tagger for Code-Mixed Indic Social Media Text

1 code implementation1 Feb 2017 Deepak Gupta, Shubham Tripathi, Asif Ekbal, Pushpak Bhattacharyya

For the task of PoS tagging on Code-Mixed Indian Social Media Text, we develop a supervised system based on Conditional Random Field classifier.

Natural Language Processing Part-Of-Speech Tagging +2

A Hybrid Deep Learning Architecture for Sentiment Analysis

no code implementations COLING 2016 Md. Shad Akhtar, Ayush Kumar, Asif Ekbal, Pushpak Bhattacharyya

The sentiment augmented optimized vector obtained at the end is used for the training of SVM for sentiment classification.

Aspect-Based Sentiment Analysis

Semi-supervised Clustering of Medical Text

no code implementations WS 2016 Pracheta Sahoo, Asif Ekbal, Sriparna Saha, Diego Moll{\'a}, N, Kaushik an

Semi-supervised clustering is an attractive alternative for traditional (unsupervised) clustering in targeted applications.

Aspect based Sentiment Analysis in Hindi: Resource Creation and Evaluation

no code implementations LREC 2016 Md. Shad Akhtar, Asif Ekbal, Pushpak Bhattacharyya

Due to the phenomenal growth of online product reviews, sentiment analysis (SA) has gained huge attention, for example, by online service providers.

Aspect-Based Sentiment Analysis General Classification +1

Building Tempo-HindiWordNet: A resource for effective temporal information access in Hindi

no code implementations LREC 2016 Dipawesh Pawar, Mohammed Hasanuzzaman, Asif Ekbal

In this paper, we put forward a strategy that supplements Hindi WordNet entries with information on the temporality of its word senses.

General Classification

CRDT: Correlation Ratio Based Decision Tree Model for Healthcare Data Mining

no code implementations24 Sep 2015 Smita Roy, Samrat Mondal, Asif Ekbal

In this paper, we have tried to focus on this characteristics of the datasets while analysing the performance of our proposed approach which is a variant of Decision Tree model and uses the concept of Correlation Ratio(CR).

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