Hiroaki Kaminaga

Methods for extracting the polish contexts in research document creation

Intellectual document creation and its polish represent an important phase in research activities. This kind of documenting consists of multiple tasks. Such combined documenting involves the contexts in their processes of polish. Polish contexts are often valuable hints that can be utilized for later work. However, it is difficult for most users, especially research beginners, to manage the polish contexts and satisfactorily utilize them. This research was aimed at developing methods for extracting the contexts and organizing them so that users could easily reflect on the contexts. A method for extracting important portions of the generated context information network is also proposed. The effectiveness and features of the proposed methods are discussed based on the results obtained from experiments.

Graph Grammar for the Research Information Collection Method According to Research Activities

To share information more effectively in a laboratory, this study develops a method to collect and visualize research documents as well as research activities efficiently without exception. First, this paper introduces a research information relation graph that reflects research activities that obtain information. Furthermore, this paper makes research activities modeled as productions that help to generate the graph and defines the graph grammar, which generates a research information relation graph, by using the production. It is expected that conducting research in accordance with this grammar can reduce the burden of laboratory members in making research information graphs and make information sharing easy by visualizing both research documents and the context information. Customizing the graph grammar in accordance with a particular scenario and applying this method to various scenarios can make it easy to realize a system for collecting and sharing research information in different research fields.

Development of a Topic-Centered Adaptive Document Management System

Skillful management of the various types of documents used in intelligent activities and their efficient utilization are important. However, most available systems target only a single type of document (e-mails, Web pages, etc.) or are not adaptive enough. A more promising approach is topic-centered document management. A topic-centered document management system is described that changes its own functions and interfaces adaptively.

Hybrid Analysis of Audience Gaze and Slide Construction to Obtain the Clues for Improving Presentations

Abstract The aim of this research is to develop a novel mechanism for finding clues to improve presentations and providing them to its author. Promising approach is extracting the defect portions of slides by analyzing the multiple familiar sources that have been overlooked. This paper describes an overview of the hybrid analysis of audience gaze and characteristics of slide construction.

Methods for strategic accumulation of context information in research activities

Research activities normally consist of numerous works such as paper composition, discussions and surveys of literature. It is important for smooth accomplishment of research to strategically accumulate the context information (i.e. processes of the work, methods and results) and to skillfully utilize them. However, it is difficult to accumulate relevant context information since most automatic methods target only the specific work and/or researchers tend to selectively use different applications suitable for each purpose. This research aims to develop methods of organizing context information across the different styles of information and applications. This paper outlines methods to strategically accumulate context information and to organize it. Moreover, it describes an experiment using test-case data and discusses the effectiveness of the methods in light of the results.

Extraction methods of e-mail discussion processes considering diversity of description granularity and their complicated relationships

Discussion using e-mail is frequently conducted in intelligent works such as research activity. It is important but generally difficult to successfully grasp the processes of the discussions and their results. There exist descriptions of diverse particle sizes in actual discussion using e-mail. This feature brings about the difficulty in grasping the discussion processes in addition to basic features such as increase of number of e-mails. Although there have been some research projects which aim at extraction of discussion processes, these existing methods have not consider the diversity of description granularity. This research has aimed to develop a support system for extracting discussion processes and their visualization. This paper mainly describes methods for extracting the discussion processes considering the diversity of description granularity and complicated connections between them. This paper also describes the overview of target service and the outline of support system.

Algorithms for Extracting Topic across Different Types of Documents

Clever management of the various types of documents used in intelligent activities and their efficient utilization are important. However, most available methods target only a single type of document (e-mails, Web pages, etc.). A more promising approach is topic-centered document management. Algorithms are described for extracting topics across various of types of documents. Moreover, a topic-centered document management system is described that is based on grouping by topics.

Analyzation of Relationships among Search Queries for Extracting the Complicated Contexts in Web Exploration

Complicated Web exploration involving trial and error is quite important in intellectual creative activities. To successfully conduct such exploration, each user needs to satisfactorily understand the results and circumstances (i.e., contexts) of his/her own exploration. However, the contexts are difficult for a user to understand since queries and the pages obtained with them increase rapidly as exploration progresses. In this research, we were aiming at developing methods for visualizing the contexts so that a user can easily understand them. This paper mainly describes methods for clustering queries and extracting the transitions of search queries by analyzing the relationships between the clusters of queries. Moreover, this paper also describes a prototype of context map with some screenshots.

Learning History Transition Graphs for understanding the programming learning situations

This research project aims at enabling easier understanding of a learning situation on the basis of a students learning process (compile error history) in programming exercise currently conducted at universities. We express transition of learning history of a student in graph form of time series (we call it Learning History Transition Graph (LHTG)). Facilitators or a learner can refer to an LHTG along with additional information regarding the learner. Moreover, this paper describes a prototype of the support system for grasping the learning situation introducing LHTG along with the flow of our support. Application of this system enables a novel learning support with an emphasis on context.

Dynamically visualizing the relationships between Web pages depending on user's search viewpoints

Opportunities of continuous Web exploration with trial and error have been increased in intellectual creative activities such as research work and PBL. However, it is often difficult to pick up useful pages. In such exploration, information that a user particularly needs and his/her viewpoints changes in accordance with progress of the work and trial and error in it. Therefore, it is important but difficult to understand the relationships between obtained pages and to examine the promising information based on the latest perspectives. We aimed to develop the mechanism for dynamic visualization of the relationships between the pages. This paper mainly describes the outline of our dynamic visualization and methods for extracting the relationships between the pages using focused page of a user as a base point.