Eiji Aramaki

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Eiji Aramaki 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
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
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
Relation extraction between related concepts by combining Wikipedia and web information for Japanese language Natural Language Processing
Ontology
Thesaurus
Lecture Notes in Computer Science English 2010 Construction of a huge scale ontology covering many named entities, domain-specific terms and relations among these concepts is one of the essential technologies in the next generation Web based on semantics. Recently, a number of studies have proposed automated ontology construction methods using the wide coverage of concepts in Wikipedia. However, since they tried to extract formal relations such as is-a and a-part-of relations, generated ontologies have only a narrow coverage of the relations among concepts. In this work, we aim at automated ontology construction with a wide coverage of both concepts and these relations by combining information on the Web with Wikipedia. We propose a relation extraction method which receives pairs of co-related concepts from an association thesaurus extracted from Wikipedia and extracts their relations from the Web. 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