Extended Max-Occurrence with Normalized Non-Occurrence as MONO Term Weighting Modification to Improve Text Classification

Abalorio, Cristopher C.; Sison, Ariel M.; Medina, Ruji P.; Dalaorao, Gleen A.

doi:10.14569/ijacsa.2022.0130411

Cited by 3 publications

(2 citation statements)

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“…Fig. 1 illustrates the MONO TWS designed by [17] separated into seven (7) steps, and visualized by [18][19], which will be further explained in details.…”

Section: Supervised Term Weighting Schemementioning

confidence: 99%

Automated Categorization of Research Papers with MONO Supervised Term Weighting in RECApp

Biol¹,

Depositario²,

Noangay³

et al. 2023

IJACSA

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Natural Language Processing, specifically text classification or text categorization, has become a trend in computer science. Commonly, text classification is used to categorize large amounts of data to allocate less time to retrieve information. Students, as well as research advisers and panelists, take extra effort and time in classifying research documents. To solve this problem, the researchers used state-of-the-art supervised term weighting schemes, namely: TF-MONO and SQRTF-MONO and its application to machine learning algorithms: K-Nearest Neighbor, Linear Support Vector, Naive Bayes Classifiers, creating a total of six classifier models to ascertain which of them performs optimally in classifying research documents while utilizing Optical Character Recognition for text extraction. The results showed that among all classification models trained, SQRTF-MONO and Linear SVC outperformed all other models with an F1 score of 0.94 both in the abstract and the background of the study datasets. In conclusion, the developed classification model and application prototype can be a tool to help researchers, advisers, and panelists to lessen the time spent in classifying research documents.

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“…Fig. 1 illustrates the MONO TWS designed by [17] separated into seven (7) steps, and visualized by [18][19], which will be further explained in details.…”

Section: Supervised Term Weighting Schemementioning

confidence: 99%

Automated Categorization of Research Papers with MONO Supervised Term Weighting in RECApp

Biol¹,

Depositario²,

Noangay³

et al. 2023

IJACSA

View full text Add to dashboard Cite

show abstract

“…Deep learning involves learning representations directly from data, as opposed to traditional methods. Representation learning is a technique employed by machines to learn the relationships of raw, labeled or unlabeled data, which is essential in the classification process [7][8] [9][10]. This, in turn, leads to the creation of a more effective model to aid the deep learning model [11].…”

Section: Artificialmentioning

confidence: 99%

Optimizing Local Repository Search with Bidirectional Encoder Representations from Transformer Models

Escol,

Guibone,

Duenas

et al. 2023

IJETAE

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—In this research, we investigate the relationship between sentence transformer models and the accuracy and recall of asymmetric semantic search engines. Our results show that the chosen sentence transformer model has a significant impact on the performance of the search engine. Using a pre-trained model specific to the domain resulted in a high cosine similarity score of 0.64. Fine-tuning a pre-trained sentence transformer for asymmetric semantic search improved the score to 0.4, but a larger corpus was needed for optimal results. Our findings highlight the importance of careful model selection and training data in the development of asymmetric semantic search engines.

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Philippine Stock Exchange Index Forecasting Using a Tuned Artificial Neural Network Model with a Modified Firefly Algorithm

Villaruz,

Gerardo,

Medina

2023

2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence (PRAI)

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Extended Max-Occurrence with Normalized Non-Occurrence as MONO Term Weighting Modification to Improve Text Classification

Cited by 3 publications

References 0 publications

Automated Categorization of Research Papers with MONO Supervised Term Weighting in RECApp

Automated Categorization of Research Papers with MONO Supervised Term Weighting in RECApp

Optimizing Local Repository Search with Bidirectional Encoder Representations from Transformer Models

Philippine Stock Exchange Index Forecasting Using a Tuned Artificial Neural Network Model with a Modified Firefly Algorithm

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