In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.

[EX Q]: Given the incessant growth of documents describing the opinions of different people circulating on the web, including Web 2.0 has made it possible to give an opinion on any product in the net. In this paper, we examine the various opinions expressed in the tweets and classify them (positive, negative or neutral) by using the emoticons for the Bayesian method and adjectives and adverbs for the Turney’s method.
[EX A]: Detecting Opinions in Tweets

[EX Q]: Chain graphs combine directed and undi­ rected graphs and their underlying mathe­ matics combines properties of the two. This paper gives a simplified definition of chain graphs based on a hierarchical combination of Bayesian (directed) and Markov (undirected) networks. Examples of a chain graph are multivariate feed-forward networks, cluster­ ing with conditional interaction between vari­ ables, and forms of Bayes classifiers. Chain graphs are then extended using the notation of plates so that samples and data analysis problems can be represented in a graphical model as well. Implications for learning are discussed in the conclusion.
[EX A]: Chain graphs for learning

[EX Q]: The research of attribute characters in information system which contains core, necessary, unnecessary is a basic and important issue in attribute reduct. Many methods for the judgement of attribute characters are based on the relationship between the objects and attributes. In this paper, a new type of judgement theorems which are absolutely based on the relationship among attributes is proposed for the judgement of attribute characters. The method is through comparing the two new attribute sets E(a) and N(a) with respect to the designated attribute a which is proposed in this paper. We conclude that which type of the attribute a belongs to is determined by the relationship between E(a) and N(a) in essence. Secondly, more concise and clear results are given about the judgment of the attribute characters through analyzing the properties of refinement and precise-refinement between E(a) andN(a) in topology. In addition, the relationship among attributes are discussed which is useful for constructing a reduct in the last section of this paper. In the last, we propose a reduct algorithm based on E(a), and this algorithm is an extended application of the analysis of attribute characters above.
[EX A]:
A new type of judgement theorems for attribute characters in information system