Active Discriminative Text Representation Learning

We propose a new active learning (AL) method for text classification with convolutional neural networks (CNNs). In AL, one selects the instances to be manually labeled with the aim of maximizing model performance with minimal effort. Neural models capitalize on word embeddings as representations (features), tuning these to the task at hand. We argue that AL strategies for multi-layered neural models should focus on selecting instances that most affect the embedding space (i.e., induce discriminative word representations). This is in contrast to traditional AL approaches (e.g., entropy-based uncertainty sampling), which specify higher level objectives. We propose a simple approach for sentence classification that selects instances containing words whose embeddings are likely to be updated with the greatest magnitude, thereby rapidly learning discriminative, task-specific embeddings. We extend this approach to document classification by jointly considering: (1) the expected changes to the constituent word representations; and (2) the model's current overall uncertainty regarding the instance. The relative emphasis placed on these criteria is governed by a stochastic process that favors selecting instances likely to improve representations at the outset of learning, and then shifts toward general uncertainty sampling as AL progresses. Empirical results show that our method outperforms baseline AL approaches on both sentence and document classification tasks. We also show that, as expected, the method quickly learns discriminative word embeddings. To the best of our knowledge, this is the first work on AL addressing neural models for text classification.Comment: This paper got accepted by AAAI 201

Visual Representation of Text in Web Documents and Its Interpretation

This paper examines the uses of text and its representation on Web documents in terms of the challenges in its interpretation. Particular attention is paid to the significant problem of non-uniform representation of text. This non-uniformity is mainly due to the presence of semantically important text in image form as opposed to the standard encoded text. The issues surrounding text representation in Web documents are discussed in the context of colour perception and spatial representation. The characteristics of the representation of text in image form are examined and research towards interpreting these images of text is briefly described

Visual Representation of Text in Web Documents and Its Interpretation

This paper examines the uses of text and its representation on Web documents in terms of the challenges in its interpretation. Particular attention is paid to the significant problem of non-uniform representation of text. This non-uniformity is mainly due to the presence of semantically important text in image form as opposed to the standard encoded text. The issues surrounding text representation in Web documents are discussed in the context of colour perception and spatial representation. The characteristics of the representation of text in image form are examined and research towards interpreting these images of text is briefly described

THE POWER OF LANGUAGE OF AN INTERNET WEBSITE IN INFLUENCING PEOPLE’S PERCEPTION: A TEXT ANALYSIS OF REPRESENTATION

In this millennial era the Internet has become a very principal media and therefore, the language used in any text in the Internet can automatically serve as a very powerful tool to influence people’s perception. This paper analyzes the language used in a text of a website and tries to reveal the representation of the Self and Other of the text. The text analyzed was published in a website of a community that called itself The Knights Party, a non-aggressive racist group in the United States of America. The text was written by the director of the party, Thomas Robb. Robb is a pastor and director of this racist group. The analysis will apply Systemic Functional Grammar in unveiling the positive representation of the Self and negative representation of the Other. Transitivity and appraisal will be the focus of the analysis. The findings show that through transitivity and appraisal, it is obvious that the text writer is making a positive representation of the Self and negative representation of the Other. The analysis also results in the fact that the racist issue can be found within the text