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Staff Researches

Amr Mansour

A Proposed Approach for Emotion Lexicon Enrichment

Amr Mansour Mohsen Afifi

Hisham Hassan , Amira Idrees

ICDAR 2016: 18th International Conference on Document Analysis and Recognition

2016

Document analysis is an important research field that aims to gather information by analyzing data in documents. As one of the important targets for many fields is to understand what people actually want, sentimental analysis field has been one of the vital fields that are tightly related to the document analysis. This research focuses on analyzing text documents to classify each document according to its opinion. The aim of this research is to detect the emotions from text documents based on enhancing the lexicon based approach. The proposed approach has been presented and different experiments are applied by different perspectives to reveal the positive impact of the proposed approach on the classification results

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Documents Emotions Classification Model Based on TF-IDF Weighting Measure

Amr Mansour Mohsen Afifi

HA Hassan, AM Idrees

ICDAR 2016 : 18th International Conference on Document Analysis and Recognition

2016

Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

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