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Title:Diversifying citation recommendation by combining semantics and time of academic papers
Author(s):Zhang, Xiaojuan
Subject(s):Citation recommendation
Diversification
Publication time
Semantics
Abstract:In this paper, we present a study of a novel problem, i.e., diversifying citation recommendation by combining the semantics and publication time of academic papers, and we seek to generate a list of rec- ommended citations that consist of relevant ones covering diverse semantics, and at the same time, being related to different time periods. Two major tasks are involved in our work. In the first task, a unified graph model is used to generate candidate citations for each query manuscript. In the second task, candidate citation diversification is carried out by combining semantics and time of academic papers in an implicit diversification way. Preliminary experiment on ANN dataset demonstrates that our proposed method beats the baselines in terms of metrics used in citation recommendation ranking and diversification.
Issue Date:2020-03-23
Publisher:iSchools
Series/Report:iConference 2020 Proceedings
Genre:Conference Poster
Type:Text
image
Language:English
URI:http://hdl.handle.net/2142/106578
Rights Information:Copyright 2020 Xiaojuan Zhang
Date Available in IDEALS:2020-03-17


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