We propose a novel abstractive summarization system for product reviews by taking advantage of their discourse structure.First, we apply parser to each review and obtain tree representation every review.We then modify the trees such that leaf node only contains aspect words.Second, aggregate generate graph.We select subgraph representing most important aspects rhetorical relations between them using PageRank algorithm, transform selected into an tree.Finally, natural language summary...

Clauses and sentences rarely stand on their own in an actual discourse; rather, the relationship between them carries important information that allows discourse to express a meaning as whole beyond sum of its individual parts. Rhetorical analysis seeks uncover this coherence structure. In article, we present CODRA— COmplete probabilistic Discriminative framework for performing Analysis accordance with Structure Theory, which posits tree representation discourse. CODRA comprises segmenter...

Wen Xiao, Giuseppe Carenini. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint (EMNLP-IJCNLP). 2019.

Background Social media is a rich source where we can learn about people’s reactions to social issues. As COVID-19 has impacted lives, it essential capture how people react public health interventions and understand their concerns. Objective We aim investigate concerns in North America, especially Canada. Methods analyzed COVID-19–related tweets using topic modeling aspect-based sentiment analysis (ABSA), interpreted the results with experts. To generate insights on effectiveness of specific...

We introduce PRIMERA, a pre-trained model for multi-document representation with focus on summarization that reduces the need dataset-specific architectures and large amounts of fine-tuning labeled data. PRIMERA uses our newly proposed pre-training objective designed to teach connect aggregate information across documents. It also efficient encoder-decoder transformers simplify processing concatenated input With extensive experiments 6 datasets from 3 different domains zero-shot, few-shot...

Capturing knowledge from free-form evaluative texts about an entity is a challenging task. New techniques of feature extraction, polarity determination and strength evaluation have been proposed. Feature extraction particularly important to the task as it provides underpinnings extracted knowledge. The work in this paper introduces improved method for that draws on existing unsupervised method. By including user-specific prior evaluated entity, we turn into one term similarity by mapping...

Information Visualization systems have traditionally followed a one-size-fits-all model, typically ignoring an individual user's needs, abilities and preferences. However, recent research has indicated that visualization performance could be improved by adapting aspects of the to each user. To this end, paper presents aimed at supporting design novel user-adaptive systems. In particular, we discuss results on using information user eye gaze patterns while interacting with given predict...

There is increasing evidence that users' characteristics such as cognitive abilities and personality have an impact on the effectiveness of information visualization techniques. This paper investigates relationship between fine-grained user attention patterns. In particular, we present results from eye tracking study involving bar graphs radar graphs, showing a user's perceptual speed verbal working memory significant gaze behavior, both in general relation to task difficulty type. These are...

In this paper, we present an automatic abstractive summarization system of meeting conversations.Our extends a novel multi-sentence fusion algorithm in order to generate abstract templates.It also leverages the relationship between summaries and their source transcripts select best templates for generating meetings.Our manual evaluation results demonstrate success our achieving higher scores both readability informativeness.

Accessing an ever increasing number of emails, possibly on small mobile devices, has become a major problem for many users. Email summarization is promising way to solve this problem. In paper, we propose new framework email summarization. One novelty use fragment quotation graph try capture conversation. The second clue words measure the importance sentences in conversation Based and their scores, method called CWS, which capable producing summary any length as requested by user. We provide...

In many decision‐making scenarios, people can benefit from knowing what other people's opinions are. As more and evaluative documents are posted on the Web, summarizing these useful resources becomes a critical task for organizations individuals. This paper presents framework corpus of about single entity by natural language summary. We propose two summarizers: an extractive summarizer abstractive one. additional contribution, we show how our be modified to generate summaries tailored model...

Information visualization systems have traditionally followed a one-size-fits-all model, typically ignoring an individual user's needs, abilities, and preferences. However, recent research has indicated that performance could be improved by adapting aspects of the to user. To this end, article presents aimed at supporting design novel user-adaptive systems. In particular, we discuss results on using information user eye gaze patterns while interacting with given predict properties task; (in...

Abstract Today it is quite common for people to exchange hundreds of comments in online conversations (e.g., blogs). Often, can be very difficult analyze and gain insights from such long conversations. To address this problem, we present a visual text analytic system that tightly integrates interactive visualization with novel mining summarization techniques fulfill information needs users exploring At first, perform user requirement analysis the domain blog derive set design principles....

There is increasing evidence that the effectiveness of information visualization techniques can be impacted by particular needs and abilities each user. This suggests it important to investigate systems dynamically adapt In this paper, we address question how adapt. particular, present a study evaluate variety visual prompts, called "interventions", performed on help users process it. Our results show some tested interventions perform better than condition in which no intervention provided,...

In the last decade, there has been an exponential growth of asynchronous online conversations thanks to rise social media. Analyzing and gaining insights from such can be quite challenging for a user, especially when discussion becomes very long. A promising solution this problem is topic modeling, since it may help user quickly understand what was discussed in long conversation explore comments interest. However, results modeling noisy not match user's current information needs. To address...

We consider the problem of Visual Question Answering (VQA). Given an image and a free-form, open-ended, question, expressed in natural language, goal VQA system is to provide accurate answer this question with respect image. The task challenging because it requires simultaneous intricate understanding both visual textual information. Attention, which captures intra- inter-modal dependencies, has emerged as perhaps most widely used mechanism for addressing these challenges. In paper, we...

In this paper we describe research on summarizing conversations in the meetings and emails domains. We introduce a conversation summarization system that works multiple domains utilizing general conversational features, compare our results with domain-dependent systems for meeting email data. find by treating as features common, can achieve competitive state-of-the-art rely more domain-specific features.

Abstract There is increasing evidence that user characteristics can have a significant impact on visualization effectiveness, suggesting visualizations could be designed to better fit each user's specific needs. Most studies date, however, looked at static visualizations. Studies considering interactive only limited number of characteristics, and consider either low‐level tasks (e.g., value retrieval), or high‐level (in particular: discovery), but not both. This paper contributes this line...