Exploring multiple diversification strategies for academic citation contexts recommendation.
Purpose: Citation contexts have been found useful in many scenarios. However, existing context-based recommendations ignored the importance of diversity in reducing the redundant issues and thus cannot cover the broad range of user interests. To address this gap, the paper aims to propose a novelty...
| Publicado en: | Electronic Library Vol. 38; no. 4; pp. 821 - 843 |
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| Autores principales: | , , , |
| Formato: | computer program equations & formulas research tables/charts Journal Article |
| Publicado: |
Emerald Publishing Limited
2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=146976695&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 146976695 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02640473 2OJ jtl: Electronic Library issn: 02640473 maglogo: N pubinfo: dt: 2020 vid: 38 iid: 4 pid: 465 pub: Emerald Publishing Limited artinfo: ui: 146976695 146976695 146976695 10.1108/EL-02-2020-0046 146976695 ppf: 821 ppct: 22 formats: tig: atl: Exploring multiple diversification strategies for academic citation contexts recommendation. aug: au: Chen, Haihua Yang, Yunhan Lu, Wei Chen, Jiangping affil: Department of Information Science, College of Information University of North Texas, Denton, Texas, USA sug: subj: Information Retrieval Semantics Algorithms Citation Analysis Human Software Literature Review Data Collection Experimental Studies ab: Purpose: Citation contexts have been found useful in many scenarios. However, existing context-based recommendations ignored the importance of diversity in reducing the redundant issues and thus cannot cover the broad range of user interests. To address this gap, the paper aims to propose a novelty task that can recommend a set of diverse citation contexts extracted from a list of citing articles. This will assist users in understanding how other scholars have cited an article and deciding which articles they should cite in their own writing. Design/methodology/approach: This research combines three semantic distance algorithms and three diversification re-ranking algorithms for the diversifying recommendation based on the CiteSeerX data set and then evaluates the generated citation context lists by applying a user case study on 30 articles. Findings: Results show that a diversification strategy that combined "word2vec" and "Integer Linear Programming" leads to better reading experience for participants than other diversification strategies, such as CiteSeerX using a list sorted by citation counts. Practical implications: This diversifying recommendation task is valuable for developing better systems in information retrieval, automatic academic recommendations and summarization. Originality/value: The originality of the research lies in the proposal of a novelty task that can recommend a diversification context list describing how other scholars cited an article, thereby making citing decisions easier. A novel mixed approach is explored to generate the most efficient diversifying strategy. Besides, rather than traditional information retrieval evaluation, a user evaluation framework is introduced to reflect user information needs more objectively. pubtype: Academic Journal doctype: computer program equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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