We present an overview of our two runs submitted to the MediaEval 2014 Retrieving Diverse Social Images task, each relying only on visual and textual features. Whilst the approach for textual features is based on a standard tf-idf bag-of-words approach, we focused for visual features on a more complex contribution for the task which consists of clustering the images and diversifying the result ...

Most recent studies on emotion analysis and detection focus on how writers express their emotions through textual information. In this paper, we model emotion generation on the Plurk microblogging platform from both writer and reader perspectives. Support Vector Machine (SVM)-based classifiers are used for emotion prediction. To better model emotion generation on such a social network, three ty...

The massive amounts of digitized historical documents acquired over the last decades naturally lend themselves to automatic processing and exploration. Research work seeking automatically process facsimiles extract information thereby are multiplying with, as a first essential step, document layout analysis. If identification categorization segments interest in images have seen significant prog...

In this work, we present a binary classification problem in which we aim to identify those email messages that the receiver will reply to. The future goal is to develop a tool that informs a knowledge worker which emails are likely to need a reply. The Enron corpus was used to extract training examples. We analysed the word n-grams that characterize the messages that the receiver replies to. Ad...

In this paper, we focus on the task of identifying the best answer for a usergenerated question in Collaborative Question Answering (CQA) services. Given that most existing research on CQA has focused on non-textual features such as click-through counts which are relatively difficult to access, we examine the effectiveness of diverse content-based features for the task. Specially, we propose to...

With microblogging platforms such as Twitter generating huge amounts of textual data every day, the possibilities of knowledge discovery through Twitter data becomes increasingly relevant. Similar to the public voting mechanism on websites such as the Internet Movie Database (IMDb) that aggregates movies ratings, Twitter content contains reflections of public opinion about movies. This study ai...

This paper is concerned with the summarization of spontaneous conversations. Compared with broadcast news, which has received intensive study, spontaneous conversations have been less addressed in the literature. Previous work has focused on textual features extracted from transcripts. This paper explores and compares the effectiveness of both textual features and speechrelated features. The ex...

Framed in Farahzad’s (2009) critical discourse analysis (CDA) model, the present research aimed at analyzing these influences in two Persian translations of Alice’s Adventures in Wonderland at micro and macro levels. To do so, the textual features at micro-level, while the constituent aspects about the translated texts at macro-level were examined. As to the micro-level analysis, it was found t...