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    政大機構典藏 > 資訊學院 > 資訊科學系 > 會議論文 >  Item 140.119/74403


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/74403


    Title: Context-based people search in labeled social networks
    Authors: Li, C.-T.;Shan, Man-Kwan.;Lin, S.-D.
    沈錳坤
    Contributors: 資科系
    Keywords: Communication cost;Context-based;Context-based search;Graph topology;Greedy search algorithms;High school;people search;Query context;Search spaces;Social Networks;Subgraphs;Time efficiencies;Tree algorithms;Algorithms;Knowledge management;Social networking (online);Topology;Trees (mathematics)
    Date: 2011
    Issue Date: 2015-04-08 17:33:34 (UTC+8)
    Abstract: In online social networking services, there are a range of scenarios in which users want to search a particular person given the targeted person one`s name. The challenge of such people search is namesake, which means that there are many people possess the same names in the social network. In this paper, we propose to leverage the query contexts to tackle such problems. For example, given the information of one`s graduation year and city, the last names of some individuals, one may wish to find classmates from his/her high school. We formulate such problem as the context-based people search. Given a social network in which each node is associated with a set of labels and given a query set of labels consisting of a targeted name label and other context labels, our goal is to return a ranking list of persons who possess the targeted name label and connects to other context labels with minimum communication costs through an effective subgraph in the social network. We consider the interactions among query labels to propose a grouping-based method to solve the context-based people search. Our method consists of three major parts. First, we model those nodes with query labels into a group graph which is able to reduce the search space to enhance the time efficiency. Second, we identify three different kinds of connectors which connecting different groups, and exploit connectors to find the corresponding detailed graph topology from the group graph. Third, we propose a Connector-Steiner Tree algorithm to retrieve a resulting ranked list of individuals who possess the targeted label. Experimental results on the DBLP bibliography data show that our grouping-based method can reach the good quality of returned persons as a greedy search algorithm at a considerable outperformance on the time efficiency. © 2011 ACM.
    Relation: Proceedings of the 20th ACM international conference on Information and knowledge management,1607-1612
    Data Type: conference
    DOI 連結: http://dx.doi.org/10.1145/2063576.2063809
    DOI: 10.1145/2063576.2063809
    Appears in Collections:[資訊科學系] 會議論文

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