Named Entity Recognition and Aspect based Sentiment Analysis
نویسندگان
چکیده
منابع مشابه
Named Entity Recognition in Persian Text using Deep Learning
Named entities recognition is a fundamental task in the field of natural language processing. It is also known as a subset of information extraction. The process of recognizing named entities aims at finding proper nouns in the text and classifying them into predetermined classes such as names of people, organizations, and places. In this paper, we propose a named entity recognizer which benefi...
متن کاملMemory-Based Named Entity Recognition
We apply a memory-based learner to the CoNLL-2002 shared task: language-independent named entity recognition. We use three additional techniques for improving the base performance of the learner: cascading, feature selection and system combination. The overall system is trained with two types of features: words and substrings of words which are relevant for this particular task. It is tested on...
متن کاملImprovement of Chemical Named Entity Recognition through Sentence-based Random Under-sampling and Classifier Combination
Chemical Named Entity Recognition (NER) is the basic step for consequent information extraction tasks such as named entity resolution, drug-drug interaction discovery, extraction of the names of the molecules and their properties. Improvement in the performance of such systems may affects the quality of the subsequent tasks. Chemical text from which data for named entity recognition is extracte...
متن کاملAspect Based Sentiment Analysis
Sentiment analysis aims to determine the evaluation of an author with respect to a particular topic and detecting the overall contextual polarity of a document. Sentiment analysis is increasingly viewed as a vital task both from an academic and a commercial standpoint. The majority of current approaches, however, attempt to detect the overall polarity of a sentence, paragraph, or text span, irr...
متن کاملArabic Named Entity Recognition
Stemming is the process of reducing words to their stems or roots. Due to the morphological richness and complexity of the Arabic language, stemming is an essential part of most Natural Language Processing (NLP) tasks for this language. In this paper, we study the impact of different stemming approaches on the Named Entity Recognition (NER) task for Arabic and explore the merits, limitations an...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2019
ISSN: 0975-8887
DOI: 10.5120/ijca2019919367