Hiroyuki Kitagawa
University of Tsukuba
394 Papers
1.7K Citations
Hiroyuki Kitagawa is an academic researcher from University of Tsukuba. The author has contributed to research in topics: Computer science & Stream processing. The author has an hindex of 21, co-authored 380 publications. Previous affiliations of Hiroyuki Kitagawa include University of Tokyo & Toyohashi University of Technology.
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Papers
PR-MVI: Efficient Missing Value Imputation over Data Streams by Distance Likelihood
TL;DR: In this paper , Past and Recent Neighbor (PR-MVI) is proposed to predict the missing attribute value in data streams by distance likelihood, which can handle both numerical and categorical data streams that have similar and/or different distribution from that of the past training data.
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•Journal Article
LocalRank : Ranking web pages considering geographical locality by integrating web and databases
TL;DR: In this paper, the authors propose a method called LocalRank to rank web pages by integrating the web and a user database containing information on a specific geographical area, which is a rank value for a web page to assess its relevance degree to database entries considering geographical locality and its popularity on local web space.
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A Local Method for ObjectRank Estimation
Yuta Sakakura,Yuto Yamaguchi,Toshiyuki Amagasa,Hiroyuki Kitagawa +3 more
- 02 Dec 2013
TL;DR: Zhang et al. as mentioned in this paper proposed a method for estimating ObjectRank scores for specific objects by applying local computation over partial graphs, thereby allowing us to maintain low computational cost even for large graphs.
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Record extraction based on user feedback and document selection
Jianwei Zhang,Yoshiharu Ishikawa,Hiroyuki Kitagawa +2 more
- 16 Jun 2007
TL;DR: This paper proposes a method to efficiently extract those records whose topics agree with the user's interest, and makes use of user feed-back on extraction results to find topic-related documents and records.
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Facet-value extraction scheme from textual contents in XML data
TL;DR: The purpose of this paper is to extract appropriate terms to summarize the current results in terms of the contents of textual facets, a type of faceted search on XML data where a content of a facet is considered as a document.
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