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11 articles for “Corpus-based approach”
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Opinion Mining through Enhanced Lexicon Approach
Abstract: AbstractThe World Wide Web’s rapid growth has enhanced online communication. One of the approaches to putting user views is the use of social networking sites. The user’s opinion needs to be analyzed by studying user’s input text using techniques of machine learning with subjectivity, emotion, sentiment analysis or polarity calculation. Most of the existing work in the field of opinion mining has largely focused on identifying sentiment polarity as positive, …
Published in Journal of Web Engineering & Technology · Vol. 7, Issue 3, 2020 · pp. 8–15 Read article
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Rating Based Sentimental prediction: A Six Gram Statistical Mean-Median Approach
Abstract: Revolution in internet has opened a new platform for expressing the user opinions on various aspects openly in various Business domains. The expressed views include very useful information with which analysis of the user expectation and requirements can be done. Analyzing the user views and its prediction will help the business people to enhance their services to the customers as per user requirement. In this paper a novel approach is …
Published in Journal of Advanced Database Management & Systems · Vol. 5, Issue 2, 2018 · pp. 33–42 Read article
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Graph based Word Sense Disambiguation for Gujarati
Abstract: Due to high Semantic Ambiguity that is associated with language, Word Sense Disambiguation is an open problem of Natural Language Processing and Ontology in Computer Linguistics. For instance, the Gujarati word પુવૅ (Purva) can mean East and Past. The task of automatically assigning the most suitable meaning to a polysemous word can be defined as Word Sense Disambiguation. Several approaches have been done, from Dictionary-and Knowledge-based method that uses Lexical …
Published in Journal of Advancements in Robotics · Vol. 5, Issue 2, 2018 · pp. 35–43 Read article
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An Analytical Review on Word Sense Disambiguation
Abstract: Due to high Semantic Ambiguity that is associated with language, Word Sense Disambiguation is an open problem of Natural Language Processing and Ontology in Computer Linguistics. For instance, the word Head can mean the part of body and a person in charge of organization. The task of automatically assigning the most suitable meaning to a polysemous word can be defined as Word Sense Disambiguation. Several approaches have been done, from …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 1, 2018 · pp. 32–37 Read article
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From Documentation to Digital Stewardship: A Bibliometric Analysis of the Technological Transformation in Indigenous Knowledge Management
Abstract: This bibliometric study systematically maps the technological evolution of Indigenous Knowledge Management (IKM) over a 30-year period (1995–2025). It aims to identify the conceptual shifts and emerging technologies defining the transition from passive digital documentation to active algorithmic stewardship. The study utilises a scientometric approach to analyse a corpus of 835 unique documents retrieved from the Scopus database. Scientific-mapping techniques, including thematic evolution and keyword co-occurrence analysis, were performed using …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 3, 2026 Read article
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Human Deep Skin Surface Vibration Frequency Detection from CT and DT Signals Using Genetic Algorithms
Abstract: To diagnose respiratory problems early on, a contactless, non-invasive, real-time assessment of human vibration is a crucial prerequisite. Optoelectronic plethysmography (OEP) and the forced oscillation technique (FOT), are two widely utilized methodologies, depending on variations in each patient’s local chest impedance. Calibration of the devices before each measurement is hence the primary problem of these approaches. This report presents a simulation-based analysis to assess the effectiveness of the CT and …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 9–16 Read article
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Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 Read article
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A Real-time Visualization Framework to Enhance Prompt Accuracy and Result Outcomes Based on the Number of Tokens
Abstract: In the rapidly evolving domain of artificial intelligence (AI), the efficacy of user-generated prompts has emerged as a critical factor influencing the quality of model-generated responses. Current methodologies for prompt evaluation predominantly rely on post-hoc analysis, which often leads to iterative prompting and increased computational overhead. Furthermore, the challenge of “prompt hallucinations,” where AI models produce irrelevant or nonsensical responses, persists as a significant impediment to effective AI utilization. The …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 45–53 Read article
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A Supervised Learning Approach for Toxic Comment Detection on Social Media Platforms
Abstract: Nowadays everyone uses social media platforms like X (formerly Twitter), Instagram, Facebook, etc. for various purposes. With the help of this, we share our opinions, ideas, and feelings. Generally, the datasets obtained from the internet are constructive; however, there is a significant proportion of toxic ones. The datasets are filtered to remove noise, and noise is removed in post-processing. The study initiates with the upload and preprocessing of a toxic …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 7–14 Read article
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Automatic Language Identification using Basic Signal Class
Abstract: Automatic language identification (ASLID) is a problem of identifying an unknown language from spoken utterance by a computer. A segmental approach to ASLID based on the assumption that the acoustic structure of languages can be estimated by segmenting speech into three basic classes of speech signals. This paper presents a procedure of ASLID with the details of methodology and the results without recognizing the words, but the lengths segments of …
Published in Trends in Electrical Engineering · Vol. 9, Issue 2, 2019 · pp. 12–19 Read article
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AI Hindi Poem Generator
Abstract: The Hindi Poetry Generator project represents a pioneering initiative in the domain of computational creativity, blending machine learning algorithms and natural language processing methodologies to craft poetic expressions in the Hindi language. Rooted in the vast landscape of Hindi literature, this project harnesses the power of deep learning models to generate evocative and culturally significant poetry. At its core, the system relies on neural networks and sophisticated language modeling techniques …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 10–16 Read article