This paper presents a system for visualization of large amounts of new stories. In the first phase, the new stories are preprocessed for the purpose of name -entity extraction. Next, a graph of relationships between the extracted name entities is created, where each name entity represents one vertex in the graph and two name entities are connected if they appear in the same document. The graph ...

A large number of news articles are published on the Web every day, and demand of discovering news articles on new/important topics has been growing. In this paper, we present a method for detecting characteristic words co-occurring with a target word (characteristic co-occurrence words) to help users find important topics related to the target word. The method divides news articles published i...

In recent years, “News Curation Services” that recommend news articles on the internet to user have been popular. In this study, we propose a new “News Curation Service” that collects and recommends novel articles by using semantic relationships between events in the news articles that a user feels interest. The semantic relationships between events are represented by Linked Data. In order to r...

In this era of fake news and political polarization, it is desirable to have a system to enable users to access balanced news content. Current solutions focus on top down, server based approaches to decide whether a news article is fake or biased, and display only trusted news to the end users. In this paper, we follow a different approach to help the users make informed choices about which new...

People often write in their blogs about news articles or events in news articles. In this case, however, the details of the news articles or events are often poorly described in such blog entries. Therefore, the readers of blogs need to find the original articles, which contain more details of the news articles, when they want to know about them. In this paper, we propose a method for linking n...

We propose a novel news browsing system that can cluster photo news articles based on both textual features of articles and image features of news photos for a personal news database which is built by accumulating Web photo news articles. The system provides two types of clustering methods: normal clustering and thread-style clustering. It enables us to browse news articles over several weeks o...

Textuality is a key concept in text linguistics. It property that must have order to be regarded as good text. In this paper, an attempt made arrive at the aspects of textuality utilized online newspaper articles. More precisely, paper endeavors answer following question: what are most prevalent kind discourse? As such, aims identifying common exploited Accordingly, it hypothesized cohesion, co...