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Modified term frequency-inverse document frequency based deep hybrid framework for sentiment analysis
Sentiment Analysis is a highly crucial subfield in Natural Language Processing that attempts to extract the public sentiment from the accessible user...
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Inverse document frequency-based sensitivity scoring for privacy analysis
Privacy risk analysis of online social network (OSN) users aims at generating a risk score for each OSN user such that higher scores potentially...
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Term Frequency and Estimating the Closeness of Short Texts to the Semantic Standard
AbstractThis work deals with the interrelated problems of assessing the closeness of a text to the most rational (reference) form of conveying its...
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ExMo: Explainable AI Model Using Inverse Frequency Decision Rules
In this paper, we present a novel method to compute decision rules to build a more accurate interpretable machine learning model, denoted as ExMo....
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A non-redundant feature selection method for text categorization based on term co-occurrence frequency and mutual information
Feature selection is a crucial preprocessing step for text categorization that can help to reduce the feature space, speed up the learning process,...
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HierMDS: a hierarchical multi-document summarization model with global–local document dependencies
Multi-document summarization (MDS) has attracted increasing attention in recent years. Most existing MDS systems simply encode the flat connected...
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Privacy Preservation of Periodic Frequent Patterns Using Sensitive Inverse Frequency
Pattern mining methods help to extract valuable information from a large dataset. The extraction of knowledge might result in the risk of privacy...
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Exploring AI-driven approaches for unstructured document analysis and future horizons
In the current industrial landscape, a significant number of sectors are grappling with the challenges posed by unstructured data, which incurs...
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A deep learning framework for multi-document summarization using LSTM with improved Dingo Optimizer (IDO)
Multi-document summarization (MDS) is a topic of much attention in extensive knowledge areas. Extractive MDS techniques intend to shrink the text...
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A document image classification system fusing deep and machine learning models
Artificial Intelligence (AI) technologies are now widely employed to overcome human-induced faults in a variety of systems used in our daily lives,...
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Rumors detection in social networks using dynamic graph-structured bi-directional long-short term memory technique
The rumor detection, several algorithms retrieve rumor attributes via textual semantics and the rumor's transmission structure. However, most of...
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Effective Elytron Vespid-B rank BiLSTM classifier for Multi-Document Summarization
Multi-Document Summarization is the progression of extracting the pertinent information from a group of documents and weeding out the irrelevant...
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Large text document summarization based on an enhanced fuzzy logic approach
In today’s digital world, there is an enormous and exponential growth in the amount of knowledge available online. When seeking precise and pertinent...
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Predicting document novelty: an unsupervised learning approach
In the age of information deluge, it is pivotal to have access to information or knowledge which is not just relevant but also, novel. Knowledge...
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Sentence and Document Representation Learning
Sentence and document are high-level linguistic units of natural languages. Representation learning of sentences and documents remains a core and...
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Improving document classification using domain-specific vocabulary: hybridization of deep learning approach with TFIDF
Extracting domain keywords from the corpus helps optimize the task of document classification. Specialized vocabularies built only from semantically...
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Document keyword extraction based on semantic hierarchical graph model
Keyword provide a brief profile of document contents and serve as an important method for quickly obtaining the document’s themes. Traditional...
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A novel network-based paragraph filtering technique for legal document similarity analysis
The common law system is a legal system that values precedent, or previous court decisions, in the resolution of current cases. As the availability...
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A dictionary based model for bengali document classification
Computer-aided documented content analysis is a prominent research area in natural language processing . A realistic implementation of this task is...
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Neural models for semantic analysis of handwritten document images
Semantic analysis of handwritten document images offers a wide range of practical application scenarios. A sequential combination of handwritten text...
