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Internet traffic classification has been studied widely in recent years, and many machine learning approaches have been applied to it. Internet traffic classification has increased in relevance in recent years because of its potential applications in ...
In the Big Data era, machine learning has more potential to discover valuable insights from the data. As an important machine learning technique, Bayesian Network (BN) has been widely used to model probabilistic relationships among variables. To deal ...
In a polarized society, rhetorical arguments are usually expressed by strong, extreme terms which by themselves carry a positive or negative sentiment about one side of the social debate or conflict. By detecting extreme terms in a social-political text ...
Personality research on social media is a hot topic recently due to the rapid development of social media as well as the central importance of personality study in psychology, but most studies are conducted on inadequate label samples. Our research aims ...
The rapid development of online social networks (OSN) renders them a powerful tool for information diffusion. Understanding the temporal behavior of OSN users is critical in studying the diffusion process. While there is much work on building various ...
Cross-lingual sentiment classification aims to leverage the rich sentiment resources in one language for sentiment classification in a different language. The biggest challenge of this task is how to eliminate the sentimental semantic gap between two ...
In The Emperor's New Mind, Roger Penrose [1] claimed that quantum-mechanical effects are critical to human intelligence. But those effects need not be represented at the atomic level. A method of encoding conceptual graphs in a continuous representation ...
The success of opinion mining for automatically processing vast amounts of opinionated content available on the Internet has been demonstrated as a less expensive and lower latency solution for gathering public opinion. In this paper, we investigate ...
Nowadays the World Wide Web has evolved into a leading communication channel and information exchange medium. Especially after the introduction of the so-called web 2.0 and the explosion that followed regarding user generated content, the amount of data ...
Emotional Polarity Classification is an important task in Sentiment Analysis area. It is applied in many real problems such as reviews of consumer products and services, financial markets, and forensic analysis. The scientists from the areas of text ...
Discourse markers not only express some sorts of relations between two arguments, but also entail sentiment information. In this paper, we investigate the associations between the relation type and the sentiment polarity of Chinese discourse markers ...
Work on sentiment analysis has thus far been limited in the news article domain. This has mainly been caused by 1) news articles lacking a clearly defined target, 2) the difficulty in separating good and bad news from positive and negative sentiment, ...
Topic modeling is a popular research topic and is widely used in text mining based applications. Many researchers realize that the learned topics in the LDA model, each as a multinomial distribution on the word vocabulary space, are often not intuitive ...
This paper presents a highly parallel solution for cross-document co reference resolution, which can deal with billions of documents that exist in the current web. At the core of our solution lies a novel algorithm for community detection in large scale ...
Point of interest (POI) categorization is the task of finding of categories of POIs within a document. Because the documents that possess POIs have clue words for identifying POI categories, the task can be solved as document classification. However, ...
With the overwhelming increase in the amount of data on the web and data bases, many text mining techniques have been proposed for mining useful patterns in text documents. Extracting closed sequential patterns using the Pattern Taxonomy Model (PTM) is ...
In this paper, we propose two methods to measure the semantic similarity for multi-lingual and short texts by using Wikipedia. In recent years, people around the world have been continuously generating information about their local area in their own ...
In this paper, methods for ranking coordinate terms and hypernyms of a given query according to their appropriateness are proposed. Although previous studies have proposed methods for discovering coordinate terms or hypernyms of a query, they focused on ...
In our work we investigate the relationship between semantic textual similarity and credibility of the individual sentence. For this purpose we performed an experiment to create a corpus of sentences with known credibility value. Then we calculated ...
In this article we examine the use of Text Rank algorithm for identifying web content credibility. Text Rank has come to be a widely applied method for automated text summarization. In our research we apply it to see how well does it fare in recognizing ...