Model for Classification of Poems in Hindi Language Based on Ras

@article{Pal2019ModelFC,
  title={Model for Classification of Poems in Hindi Language Based on Ras},
  author={Kaushika Pal and Biraj V. Patel},
  journal={Smart Systems and IoT: Innovations in Computing},
  year={2019}
}
The developed model will classify poem into Shringar, Hasya, Adbhuta, Shanta, Raudra, Veera, Karuna, Bhayanaka, Vibhasta rasas, which will use mix of part-of-speech-based feature and emotional features to classify the poem. Emotional features are features, which are responsible for particular emotion and it is represented in 9 categories. We have 9 classes each class-containing feature for one class, overlapping of feature is possible and is dealt with term frequency in the document. The… 
Automatic Multiclass Document Classification of Hindi Poems using Machine Learning Techniques
  • Kaushika Pal, B. Patel
  • Computer Science
    2020 International Conference for Emerging Technology (INCET)
  • 2020
TLDR
Experiments shows that Naïve Bayes with 64% accuracy and Random Forest with 56% are performing better as compared to other algorithms for Hindi Poem Classification.
Hindi Poetry Classification using Eager Supervised Machine Learning Algorithms
TLDR
Two eager machine learning algorithms are applied on the corpus containing 450 Hindi poems and poetry/poem gets classified based on terms present in it using a misclassification error.
SUKHAN: Corpus of Hindi Shayaris annotated with Sentiment Polarity Information
TLDR
This paper introduces SUKHAN, a dataset consisting of Hindi shayaris along with sentiment polarity labels, which is the first corpus of HindiShayaris annotated with sentimentPolarity information.
Towards Natural Language Processing with Figures of Speech in Hindi Poetry
TLDR
This work is the first of its kind in Hindi Natural Language Processing (NLP), which touches on the area of Hindi figure of speech and has created a systematic hierarchical structure of Hindi “Alankaar” types and sub-types and attempted and extended the work to identify a few.
On Exhaustive Evaluation of Eager Machine Learning Algorithms for Classification of Hindi Verses
TLDR
Text classification algorithms along with Natural Language Processing (NLP) facilitates fast, cost-effective, and scalable solution for classification and prediction of verses on Hindi corpus.
Stanza Type Identification using Systematization of Versification System of Hindi Poetry
TLDR
The paper covers various challenges and the best possible solutions for those challenges, describing the methodology to generate automatic metadata for “Chhand” based on the poems’ stanzas, and provides some advanced information and techniques for metadata generation for ”Muktak Chhands”.
Sentiment Analysis in Hindi—A Survey on the State-of-the-art Techniques
TLDR
This research portrays a systematic review specifically in the field of Hindi SA of state-of-the-art computational intelligence techniques based on different aspects such as their impact on the issues of SA, levels of analysis, and performance evaluation measures.
Multi - Class Document Classification: Effective and Systematized Method to Categorize Documents
TLDR
This research work is combining approach of Natural Language Processing and Machine Learning for content-based classification of documents that is successful in classifying documents with more than 70% of accuracy for major Indian Languages and more than 80% accuracy for English Language.
Analysing the Poetic Structure of Jana-Gaṇa-Mana in Entirety: A Statistical Approach
Measurable investigation of abstract content so as to bring bits of knowledge into its expressive highlights has been a shared zone of enthusiasm among the aficionados of writing and measurements.
Hindi Verse Class Predictor using Concept Learning Algorithms
TLDR
In this paper, 565 Hindi poems are classified based on four topics using lazy machine-learning algorithms which are K-nearest neighbours and regression, and K nearset neighbours performs better than Linear regression.
...
...

References

SHOWING 1-10 OF 12 REFERENCES
Classification of children stories in hindi using keywords and POS density
TLDR
This paper is proposing a framework for story classification using keyword and Part-of-speech (POS) based features for Hindi stories into three genres: fable, folk-tale and legend.
Emotion-specific features for classifying emotions in story text
TLDR
The importance of story genre information in emotion classification was observed from the experiments conducted on classifying emotions within story genre, and SVM models outperformed other models in terms of classification accuracy.
Children story classification based on structure of the story
  • M. HarikrishnaD., K. S. Rao
  • Computer Science
    2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
  • 2015
TLDR
The main part of the stories has the highest classification accuracy compared to introduction and climax parts of the story, and a framework for story classification using keyword and Part-of-speech (POS) based features is proposed.
Multiclass classification and class based sentiment analysis for Hindi language
TLDR
A model for classification of Hindi speech documents into multiple classes with the help of ontology is proposed and sentiment analysis is carried out using HindiSentiWordNet (HSWN) to determine the polarity of individual class.
Performance analysis of flexible zone based features to classify Hindi numerals
TLDR
The performance of fixed boundary and flexible boundary is evaluated and performance for SVM is better than SVM for recognition of the digits and MLP based classifier is used.
A Framework for Sentiment Analysis in Hindi using HSWN
TLDR
The proposed system for sentiment analysis of Hindi movie review uses HindiSentiWordNet (HSWN) to find the overall sentiment associated with the document; polarity of words in the review are extracted from HSWN and then final aggregated polarity is calculated which can sum as either positive, negative or neutral.
Handwritten Hindi character recognition using k-means clustering and SVM
  • Akanksha Gaur, S. Yadav
  • Computer Science
    2015 4th International Symposium on Emerging Trends and Technologies in Libraries and Information Services
  • 2015
TLDR
Recognition of Hindi characters is done by using a three step procedure, in which binarization of the image and separations of characters are performed.
HOMS: Hindi opinion mining system
TLDR
A Hindi Opinion Mining System (HOMS) is proposed for movie review data and performs the task of opinion mining at the document level and classifies the documents as positive, negative and neutral using two different methods: Machine learning technique and Part-Of-Speech (POS) tagging.
Identification of relations from IndoWordNet for Indian languages using Support Vector Machine
TLDR
Support Vector Machine (SVM) based approach for learning, classifying and automatically predicting relationships between Hindi Synsets and the system performance has been validated using the performance measures namely Precision, Recall and F-score.
Multi-stage children story speech synthesis for Hindi
TLDR
A multi-stage children story speech synthesis system for Hindi language performs the following tasks: classification of stories into different genres based on text, prediction of emotion from story text, deriving prosody rules specific to emotions and story genres and synthesis of story speech using mark-up language and prosody modification factors.
...
...