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    政大機構典藏 > 資訊學院 > 資訊科學系 > 期刊論文 >  Item 140.119/61583


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    題名: Exploring Heterogeneous Information Networks and Random Walk with Restart for Academic Search
    作者: 沈錳坤
    Shan,Man-Kwan
    Peng,Wen-Chih
    Wang,Jen-Liang
    Liou,Jiun-Jiue
    Chiang,Meng-Fen
    貢獻者: 資科系
    日期: 2012.04
    上傳時間: 2013-11-11 16:28:04 (UTC+8)
    摘要: In this paper, we explore heterogenous information networks in which each vertex represents one entity and the edges reflect linkage relationships. Heterogenous information networks contain vertices of several entity types, such as papers, authors and terms, and hence can fully reflect multiple linkage relationships among different entities. Such a heterogeneous information network is similar to a mixed media graph (MMG). By representing a bibliographic dataset as an MMG, the performance obtained when searching relevant entities (e.g., papers) can be improved. Furthermore, our academic search enables multiple-entity search, where a variety of entity search results are provided, such as relevant papers, authors and conferences, via a one-time query. Explicitly, given a bibliographic dataset, we propose a Global-MMG, in which a global heterogeneous information network is built. When a user submits a query keyword, we perform a random walk with restart (RWR) to retrieve papers or other types of entity objects. To reduce the query response time, algorithm Net-MMG (standing for NetClus-based MMG) is developed. Algorithm Net-MMG first divides a heterogeneous information network into a collection of sub-networks. Afterward, the Net-MMG performs a RWR on a set of selected relevant sub-networks. We implemented our academic search and conducted extensive experiments using the ACM Digital Library. The experimental results show that by exploring heterogeneous information networks and RWR, both the Global-MMG and Net-MMG achieve better search quality compared with existing academic search services. In addition, the Net-MMG has a shorter query response time while still guaranteeing good quality in search results.
    關聯: Knowledge and Information Systems, 36(1) , 59-82
    資料類型: article
    DOI 連結: http://dx.doi.org/10.1007/s10115-012-0523-8
    DOI: 10.1007/s10115-012-0523-8
    顯示於類別:[資訊科學系] 期刊論文

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