In this work, we present an approach for mining user preferences and recommendation based on reviews. There have been various studies worked on recommendation problem. However, most of the studies beyond one aspect user generatedcontent such as user ratings, user feedback and so on to state user preferences. There is a problem in one aspect mining is lacking for stating user preferences. As a d...

Model choice and validation have a central role in data analysis, including predictive modeling. While standard diagnostics can help identify model inadequacies, it is natural to use predictive accuracy as the decisive criterion in the final choice of predictive model. A key point is that any assessment of predictive accuracy, theoretical or empirical, inevitably assumes a “data mechanism”, i.e...

In this paper we investigate the discovery of spatial association rules from a particular kind of images, namely document images. Document images are initially processed to extract both their layout structures and their logical structures. To take into account the inherent spatial nature of the layout structure, a spatial data mining algorithm is applied, which returns spatial association rules...

This paper defines a systematic approach to Opinion Mining (OM) on YouTube comments by (i) modeling classifiers for predicting the opinion polarity and the type of comment and (ii) proposing robust shallow syntactic structures for improving model adaptability. We rely on the tree kernel technology to automatically extract and learn features with better generalization power than bag-of-words. An...

For the competition SemEval-2017 we investigated the possibility of performing stance classification (support, deny, query or comment) for messages in Twitter conversation threads related to rumours. Stance classification is interesting since it can provide a basis for rumour veracity assessment. Our ensemble classification approach of combining convolutional neural networks with both automatic...

Over the past few years, our Data Management, Exploration and Mining (DMX) group at Microsoft Research has worked closely with the Bing team to address challenging data cleaning and approximate matching problems. In this article we describe some of the key Big Data challenges in the context of these Bing services primarily focusing on two key services: Bing Maps and Bing Shopping. We describe i...

In this paper we present the OnForumS corpus developed for the shared task of the same name on Online Forum Summarisation (OnForumS at MultiLing’15). The corpus consists of a set of news articles with associated readers’ comments from The Guardian (English) and La Repubblica (Italian). It comes with four levels of annotation: argument structure, comment-article linking, sentiment and coreferenc...

Sentiment analysis is a process of understanding, extracting, and processing textual data automatically to get sentiment information contained in comment sentence on Twitter. needs be done because the use social media society increasing so that it affects development public opinion. Therefore, can used analyze opinion by applying science, one which Natural Language Processing (NLP) Text Mining ...

Interactions in social media can be seen from comments as feedback every activity on media, starting statuses the form of text, images or videos. One area computer technology that study meaning text is mining. Sentiment analysis opinion mining a solution to solving problems automatically classify opinions into positive and negative. Comments YouTube video viewers TvOne channel about Ustadz Abdu...