Akiyo Nadamoto

WebCarousel: Restructuring web search results for passive viewing in mobile environments

In the present paper, we propose a new way of organizing Web search results and of viewing those results passively in the mobile environment which has limited display and limited interaction. Specifically, the system makes Carousel Components, that are composed of image and voice, from Web search result. Each time of users interaction, the system automatically computes sets of similar, different, more-detailed, and more-abstracted pages, respectively and reorganizes them as carousels. We call this system WebCarousel.

Complementing your TV-viewing by web content automatically-transformed into TV-program-type content

Despite much talk about the fusion of broadcasting and the Internet, no technology has been established for fusing web and TV program content. In this paper, we propose ways to transform web content into TV-program-type content as a first step towards the fusion of these media. Our transformation method is based on two criteria - the transmitted information and the dialogue among character agents. The method deals with both an audio component and a visual component. By combining these techniques, we can transform web content into various forms of TV-program-type content depending on the users aims. We present three different prototype systems, u-Pav which reads out the entire text of web content and presents image animation, Web2TV which reads out the entire text of web content and presents character agent animation, and Web2Talkshow which presents keyword-based dialogue and character agent animation. These prototype systems enable users to watch web content in the same way, they watch a TV program.

Back to the TV: information visualization interfaces based on TV-program metaphors

The authors describe the idea and usage of the TV program metaphors and personalization techniques to visualize WWW documents, database querying results, and broadcast based information delivery systems. Our TV program metaphors based interfaces combined with personalization facilities provide users with a couch-potato-like, passive-type user interface to browse information from the users viewpoint. Intuitively, by our TV program metaphors and personalization techniques, users can browse information from WWW, databases, and push-type information delivery systems as if they were watching a TV program.

A TV program generation system using digest video scenes and a scripting markup language

This paper describes a TV program generation system using digest video scenes that are retrieved from video streams with the program indexes. The key features of the system are: (1) TV programs can be dynamically generated from digest video scenes selected by user preference. (2) Directions can be added using a happiness or sadness level based on the user preferences. (3) Personalized TV programs for an individual viewer can be made. The procedures taken by the system are as follows: (1) Conjunctive expressions between scenes are automatically generated; (2) Emotional expressions are automatically generated by user preference; (3) TV program metaphors are defined; (4) Direction templates corresponding to the metaphors are defined; (5) These expressions and definitions are coded using a markup language, and (6) Contents such as virtual characters and movies are synchronized. The resultant program can be shown on a TV set.

B-CWB: Bilingual Comparative Web Browser Based on Content-Synchronization and Viewpoint Retrieval

We propose a new way of browsing bilingual web sites through concurrent browsing with automatic similar-content synchronization and viewpoint retrieval facilities. Our prototype browser system is called the Bilingual Comparative Web Browser (B-CWB) and it concurrently presents bilingual web pages in a way that enables their contents to be automatically synchronized. The B-CWB allows users to browse multiple web news sites concurrently and compare their viewpoint of news articles written in different languages (English and Japanese). Our viewpoint retrieval is based on similar and different detection. We described categorizing pages in terms of viewpoint: the entire similarity, the content difference, and subject difference. Content synchronization means that user operation (scrolling or clicking) on one web page does not necessarily invoke the same operations on the other web page to preserve similarity of content between the multiple web pages. For example, scrolling a web page may invoke passage-level viewpoint retrieval on the other web page. Clicking a web page (and obtaining a new web page) invokes page-level viewpoint retrieval within the other sites pages through the use of an English-Japanese dictionary.

Clustering for closely similar recipes to extract spam recipes in user-generated recipe sites

Nowadays, many user-generated recipe sites are accessible on the internet. On user-generated recipe sites, however, are various spam recipe pages that describe closely similar recipes requiring special cooking equipment, with no preparation explanations. These spam recipes are not useful for users. In fact, they impede users recipe searches. In this paper, we target closely similar recipes as a first step in extracting spam recipes. If user search results could be classified to identify closely similar recipes, users recipe searches would be easier and more productive. Clustering tools of many kinds are proposed, but it is difficult to cluster closely similar recipes using only existing clustering tools because recipe sites have a unique page structure comprising a title, ingredients, directions (preparation instructions), and comments. The importance of words from each part differs. We propose a clustering method for user-generated recipe sites based on page structure and important words. Next, we conducted an experiment to measure the benefits of our proposed method. The result of experiment presents the benefits of our proposed method which classify the closely similar recipes.

Multidimensional sentiment calculation method for Twitter based on emoticons

Purpose – The purpose of this paper is to propose a method of calculating the sentiment value of a tweet based on the emoticon role. Design/methodology/approach – Classification of emoticon roles as four types showing “emphasis”, “assuagement”, “conversion” and “addition”, with roles determined based on the respective relations to sentiment of sentences and emoticons. Findings – Clustering of users of four types based on emoticon sentiment. Originality/value – Formalization, using regression analysis, of the relation of sentiment between sentences and emoticons in all roles.

Tip information from social media based on topic detection

Purpose – The information of social media is not often written in ordinary web pages. Nevertheless, it is difficult to extract such information from social media because such services include so much information. Furthermore, various topics are mixed in social media communities. The authors designate such important and unique information related to social media as tip information. In this paper, they aim to propose a method to extract tip information that has been classified by topic from social networking services as a first step in extracting tip information from social media.Design/methodology/approach – Themes of many kinds exist in a social media community because users write contents freely. Then the authors first detect the topics from the community and cluster the comment based on the topics. Subsequently, they extract tip information from each cluster. In this time, the tip information is include a users experience and it has common important words.Findings – The authors used an experiment to co...

Words-of-wisdom search based on multi-dimensional sentiment vector

With the rapid advance of the Internet, everybody has become able to obtain information from it easily. However. there are no systems which are available to extract and present information suitable to a users sentiment. We propose a system that searches for information based on a users sentiment. As described in this this paper, we propose a words-of-wisdom search system as a first step of the research. Specifically, we first propose a multi-dimensional sentiment vector based on Nakamuras proposed 10 categories of sentiments. Next, based on our experiment, we calculate the value of sentiment words included in words-of-wisdom. Subsequently we calculate the sentiment value of words-of-wisdom using a value of sentiment words. We developed a prototype system and conducted experiments.

Extracting content holes by comparing community‐type content with Wikipedia

Purpose – Community‐type content that are social network services and blogs are maintained by communities of people. Occasionally, community members do not understand the nature of the content from multiple perspectives, and so the volume of information is often inadequate. The authors thus consider it necessary to present users with missing information. The purpose of this paper is to search for the content “hole” where users of community‐type content missed information.Design/methodology/approach – The proposed content hole is defined as different information that is obtained by comparing community‐type content with other content, such as other community‐type content, other conventional web content, and real‐world content. The paper suggests multiple types of content holes and proposes a system that compares community‐type content with Wikipedia articles and identifies the content hole. The paper first identifies structured keywords from the community‐type content, and extracts target articles from Wiki...