Clustering of Research Documents - A Survey on Semantic Analysis and Keyword Extraction

Nair, Srikesh Rajesh; Gokul, G; Vadakkan, Akshay Anto; Pillai, Aditya G; Thushara, MG

doi:10.1109/i2ct51068.2021.9418197

Cited by 9 publications

(2 citation statements)

References 34 publications

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“…The model employs algorithms like Sentence-Transformers, UMAP, HDBSCAN, and classbased TF-IDF [41] throughout the modeling process. Outliers are documents or words that don't suit BERTopic subjects.…”

Section: Bertopicmentioning

confidence: 99%

Subjectivity Analysis for Aspect-based Sentiment and Opinion Detection of YouTube Product Reviews

Tetteh,

Thushara

2023

Preprint

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The advent of the internet has presented a novel paradigm for conducting consumer research and focus group investigations. Social media platforms enable organizations and entities to efficiently obtain and analyze public opinions regarding their products and services. This eliminates the need for extensive resource allocation towards traditional survey methods and information-gathering strategies. The present study investigates the potential of utilizing the YouTube platform as a valuable data source for product review analysis—our research centers on Apple Inc. and its most profitable product, the Apple iPhone. Using user feedback from review videos, we employ a lexicon-based subjectivity analysis methodology to identify statements articulating subjective viewpoints about the iPhone product. Traditional sentiment analysis methods categorize opinionated views into two broad categories: positive or negative. To assess the general market perception of the product, we employ SpaCy’s aspect extraction functionality to identify significant parts of the product that are subject to viewer critique. A BERTopic model processes the user’s text by using topic modeling techniques to extract latent themes that provide insights into the various detected characteristics. The BERTopic model has high efficiency and yields a coherence score of 69%.

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Section: Bertopicmentioning

confidence: 99%

Subjectivity Analysis for Aspect-based Sentiment and Opinion Detection of YouTube Product Reviews

Tetteh,

Thushara

2023

Preprint

Self Cite

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“…Moreover, classification accuracy based on the mined features depends on the expert capabilities 13,14 . Machine learning approaches can have the ability to classify the data correctly, which come across results in semantic analysis when linked with NLP techniques 15 . Techniques based on machine learning models use algorithmic models and datasets to develop programs that provide appropriate solutions to the identified problems.…”

Section: Introductionmentioning

confidence: 99%

Web information mining and semantic analysis in heterogeneous unstructured text data using enhanced latent Dirichlet allocation

Venugopal

Sharma

2022

Concurrency and Computation

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Summary Information mining and semantic analysis have gained significant attention over recent years to obtain appropriate information from unstructured data. Several approaches have been introduced for web information mining. However, the expected accuracy is not reached by these approaches. Therefore, hybrid fuzzy clustering and enhanced latent Dirichlet allocation (ELDA) are proposed for the accuracy increment in this work. The information clustering process is performed using the hybrid fuzzy clustering algorithm called fuzzy‐C‐medoids optimized using improved whale algorithm. The clustering procedure entails grouping data points into more similar clusters than data points from other clusters. Finally, the context of the text is recognized by analyzing the semantic information with ELDA, which offers a suitable index for accurate and fast data extraction. PYTHON tool is used to develop the proposed web mining model, and the simulation analysis of the proposed model is carried out using the BibTex dataset and compared with baseline models. The performance of the proposed method is evaluated using purity, normalized mutual information, accuracy, and precision metrics. Also, it is compared with different existing algorithms. Thus, the analysis of the results proved that the proposed approach achieves better outcomes than the existing approaches.

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Study of Document Clustering Algorithms Applied on Covid Data

Suresh

Krishna

Thushara

2022

Advances in Intelligent Systems and Computing

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Clustering of Research Documents - A Survey on Semantic Analysis and Keyword Extraction

Cited by 9 publications

References 34 publications

Subjectivity Analysis for Aspect-based Sentiment and Opinion Detection of YouTube Product Reviews

Subjectivity Analysis for Aspect-based Sentiment and Opinion Detection of YouTube Product Reviews

Web information mining and semantic analysis in heterogeneous unstructured text data using enhanced latent Dirichlet allocation

Study of Document Clustering Algorithms Applied on Covid Data

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