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Nowadays, many people express their opinions using user generated contains such as social media, forums and reviews. Opinion mining is a field of study that extracts sentiments from user generated contents. Because of the complexity of the Arabic language, extracting those opinions are challenging. Better representation of reviews can help to improve extraction of opinions. The traditional way of...
Conventional automatic document classification methods are currently faced with challenges in terms of learning time and computing power, owing to the ever-increasing amount of data on the web. In this paper, we propose an efficient classification method that uses time series-based dataset selection. In the proposed method, the dataset is split based on time series data and the best set of testing...
Attributes are defined as mid-level image characteristics shared among different categories. These characteristics are suitable in order to handle classification problems especially when training data are scarce. In this paper, we design discriminative real-valued attributes by learning nonlinear inductive maps. Our method is based on solving a constrained optimization problem that mixes three criteria;...
Word2vec is a neural network language model which can convert words and phrases into a high-quality distributed vector (called word embedding) with semantic word relationships, so it offers a unique perspective to the text classification and other natural language processing (NLP) tasks. In this paper, we propose to combine improved tfidf algorithm and word embedding as a way to represent documents...
People write online documents from different personal perspectives. The competitive perspectives they hold reflect the conflicts in their fundamental stances and viewpoints. For many security-related applications, it is both beneficial and critical to identify the competitive perspectives implied in online documents. Previous work on competitive perspective identification is based on word features,...
Microblog post has been a hot research source for emotion classification in recent years. However, due to bloggers' free narrative style and topics' timeliness, the data from microblog post is usually implicit and imbalanced. In this paper, the problems of emotion classification in Chinese microblog posts are solved in a hierarchical way using a knowledge-based topic model and Support Vector Machine(SVM)...
Teachers and parents may use readability to select appropriate learning materials for primary school students. This research constructs Thai stop word list and evaluates the impact of eliminating stop words on readability assessment of Thai text. The corpus contains 1,188 textbook articles used by students from grade 1 to grade 6. Word segmentation, stop word list extraction, and feature selection...
Opinion mining is a growing interest task in both research and practical applications. It deals with the computational treatment of opinion, sentiment, and subjectivity in documents. This paper focuses on retrieving the opinion documents and giving their sentiment orientation. Mining and ranking the topic relevant opinion documents are implemented with a sentiment model, combining the existing knowledge...
Context modeling for Vision Recognition and Automatic Image Annotation (AIA) has attracted increasing attentions in recent years. For various contextual information and resources, semantic context has been exploited in AIA and brings promising results. However, previous works either casted the problem into structural classification or adopted multi-layer modeling, which suffer from the problems of...
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