Akiyo Nadamoto

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Akiyo Nadamoto is an author.

Publications

Only those publications related to wikis are shown here.
Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Complementary information for Wikipedia by comparing multilingual articles Lecture Notes in Computer Science English 2013 Information of many articles is lacking in Wikipedia because users can create and edit the information freely. We specifically examined the multilinguality of Wikipedia and proposed a method to complement information of articles which lack information based on comparing different language articles that have similar contents. However, much non-complementary information is unrelated to a user's browsing article in the results. Herein, we propose improvement of the comparison area based on the classified complementary target. 0 0
Extracting complementary information from Wikipedia articles of different languages Comparison
Complementary information
Wikipedia
International Journal of Business Intelligence and Data Mining English 2013 In Wikipedia, users can create and edit information freely. Few editors take responsibility for editing the articles. Therefore, information of many Wikipedia articles is lacking. Furthermore, Wikipedia has different levels of value of its information depending on the language version of the site. In this paper, we propose the extraction of complementary information from different language Wikipedia and its automatic presentation. The important points of our method are: 1) extraction of comparison articles from different language Wikipedia; 2) extraction of complementary information; 3) presentation of complementary information. 0 0
Extracting difference information from multilingual wikipedia Lecture Notes in Computer Science English 2012 Wikipedia articles for a particular topic are written in many languages. When we select two articles which are about a single topic but which are written in different languages, the contents of these two articles are expected to be identical because of the Wikipedia policy. However, these contents are actually different, especially topics related to culture. In this paper, we propose a system to extract different Wikipedia information between that shown for Japan and that of other countries. An important technical problem is how to extract comparison target articles of Wikipedia. A Wikipedia article is written in different languages, with their respective linguistic structures. For example, "Cricket" is an important part of English culture, but the Japanese Wikipedia article related to cricket is too simple. Actually, it is only a single page. In contrast, the English version is substantial. It includes multiple pages. For that reason, we must consider which articles can be reasonably compared. Subsequently, we extract comparison target articles of Wikipedia based on a link graph and article structure. We implement our proposed method, and confirm the accuracy of difference extraction methods. 0 0
Extracting lack of information on Wikipedia by comparing multilingual articles ACM International Conference Proceeding Series English 2012 Wikipedia has multilingual articles, the information of which differs, even for articles on the same topic. As described in this paper, we propose a system to extract and present lack of information of one language on Wikipedia by comparing two languages on the Wikipedia. When we compare Wikipedia articles of two languages, the granularity of information between them differs. Therefore, we propose a method of extracting multiple comparison articles using a Wikipedia link graph. The system extracts lack of information that is included in articles in Wikipedia by comparing one base article with other articles that are found using the link graph. 0 0
Good quality complementary information for multilingual Wikipedia Lecture Notes in Computer Science English 2012 Many Wikipedia articles lack information, because not all users submit truly complete information to Wikipedia. However, Wikipedia has many language versions that have been developed independently. Therefore, if we supply these complementary information from many language versions, the users must satisfy the amount of information of Wikipedia articles with the complementary information, instead of only one language version of Wikipedia articles. In this study, we specifically examine multilingual Wikipedia and propose a method of extracting good quality complementary information from Wikipedia of other languages. Specifically, we compare Wikipedia articles with less information to those with more information. From Wikipedia articles, which can have the same theme and different languages, we extract different information as complementary information. As described herein, we extract comparison target articles of Wikipedia based on a link graph, because cases exist in which information included in an articles is written in multiple pages of different languages. Furthermore, some low-quality information is extracted as complementary information because Wikipedia articles are written by not only good editors but also bad editors such as vandals. We propose a method to calculate the quality of information based on the editors, and we extract good quality complementary information. 0 0
Search for minority information from wikipedia based on similarity of majority information Lecture Notes in Computer Science English 2012 In this research, we propose a method of searching for minority information, which is less acknowledged and less popular, on the internet. We propose two methods to extract minority information. One is that of calculating relevance of content. The other is based on analogy expression. In this paper, we propose such a minority search system. At this time, we consider it necessary to search for minority information in which a user is interested. Using our proposed system, the user inputs a query which represents their interest in majority information. Then the system searches for minority information that is similar to the majority information provided. Consequently, users can obtain the new information that users do not know and can discover new knowledge and new interests. 0 0
Acquiring the gist of Social Network Service Threads via comparison with wikipedia Coverage Degree
Link Graph
SNS Thread
Social Network Services (SNSs)
Wikipedia
International Journal of Business Data Communications and Networking English 2011 Internet-based social network services (SNSs) have grown increasingly popular and are producing a great amount of content. Multiple users freely post their comments in SNS threads, and extracting the gist of these comments can be difficult due to their complicated dialog. In this paper, the authors propose a system that explores this concept of the gist of an SNS thread by comparing it with Wikipedia. The granularity of information in an SNS thread differs from that in Wikipedia articles, which implies that the information in a thread may be related to different articles on Wikipedia. The authors extract target articles on Wikipedia based on its link graph. When an SNS thread is compared with Wikipedia, the focus is on the table of contents (TOC) of the relevant Wikipedia articles. The system uses a proposed coverage degree to compare the comments in a thread with the information in the TOC. If the coverage degree is higher, the Wikipedia paragraph becomes the gist of the thread. 0 0
Credibility Assessment Using Wikipedia for Messages on Social Network Services Credibility
Social Network Service
Wikipedia
DASC English 2011 0 0
Gist of a Thread in Social Network Services Based on Credibility of Wikipedia HICSS English 2011 0 0
Gist of a thread in social network services based on credibility of Wikipedia Proceedings of the Annual Hawaii International Conference on System Sciences English 2011 Users of Social Network Services(SNS) can sometimes enter into heated discussions, which prompt those users to concentrate on a single issue and lose track of the actual theme. We believe that it would be beneficial for users and visitors to present information to help understand the gist of the discussion at a glance. As described in this paper, we propose a system that presents a gist of a thread on an SNS and basic information about it by comparing the comments in the thread with Wikipedia article. Wikipedia articles, however, are not always credible. When we compare a thread on an SNS with Wikipedia, the Wikipeida article must have credible content. We measure the credibility of the article based on the credibility of Editors. We first extract the target passage which is candidate of the gist of a thread in an SNS based on the Wikipedia Table of Contents(TOC). Then we measure the credibility of editors of Wikipedia using the edit history and measure the credibility of the article using results of the credibility of editors. The target passage, which has a high similarity degree with comment in an SNS and has a high credibility rate becomes the gist of the thread in SNS. Consequently, users and viewers can ascertain the gist of an SNS thread by viewing a Wikipedia TOC with credibility. 0 0
Extracting content holes by comparing community-type content with Wikipedia International Journal of Web Information Systems 2010 0 0
Extracting the gist of Social Network Services using Wikipedia Social Network Services
Summarize
Wikipedia
IiWAS2010 - 12th International Conference on Information Integration and Web-Based Applications and Services English 2010 Social Network Services(SNSs), which are maintained by a community of people, are among the popular Web 2.0 tools. Multiple users freely post their comments to an SNS thread. It is difficult to understand the gist of the comments because the dialog in an SNS thread is complicated. In this paper, we propose a system that presents the gist of information at a glance and basic information about an SNS thread by using Wikipedia. We focus on the table of contents (TOC) of the relevant articles on Wikipedia. Our system compares the comments in a thread with the information in the TOC and identifies contents that are similar. We consider the similar contents in the TOC as the gist of the thread and paragraphs in Wikipedia similar to the comments in the thread as comprising basic information about the thread. Thus, a user can obtain the gist of an SNS thread by viewing a table with similar contents. Copyright 2010 ACM. 0 0
Outline of community-type content based on Wikipedia Lecture Notes in Computer Science English 2010 It is difficult to understand the outline of community-type content such as Blog, Social Network Services(SNS), and Bulletin Board System(BBS) because multiple users post content freely. In this paper, we have developed a system that presents the outline of community-type content by using Wikipedia. We focus on the table of contents (TOC) collected from Wikipedia. Our system compares the comments in a thread with the information in the TOC obtained from Wikipedia and identifies contents that are similar. Thus, the user can understand the outline of community-type content when he/she views a table with similar contents. 0 0
Outline of community-type content based on wikipedia DASFAA English 2010 0 0
Content hole search in community-type content Blogs
Community
Content hole search
SNS
WWW'09 - Proceedings of the 18th International World Wide Web Conference English 2009 In community-type content such as blogs and SNSs, we call the user's unawareness of information as a "content hole"and the search for this information as a "content hole search." A content hole search differs from similarity searching and has a variety of types. In this paper, we propose different types of content holes and define each type. We also propose an analysis of dialogue related to community-type content and introduce content hole search by using Wikipedia as an example. Copyright is held by the author/owner(s). 0 0
Content hole search in community-type content using Wikipedia SNS
Blogs
Community
Content hole search
IiWAS English 2009 0 0