A new subject-based retrieval and search result visualization approach for scientific digital libraries.
Purpose: Many search engines in digital libraries are restricted to the terms presented in users' queries. When users cannot represent their information needs in terms of keywords in a query, the search engine fails to provide appropriate results. In addition, most search engines do not have the abi...
| Publicado en: | Electronic Library Vol. 39; no. 4; pp. 572 - 596 |
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| Autores principales: | , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Emerald Publishing Limited
2021
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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=153418828&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 153418828 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02640473 2OJ jtl: Electronic Library issn: 02640473 maglogo: N pubinfo: dt: 2021 vid: 39 iid: 4 pid: 465 pub: Emerald Publishing Limited artinfo: ui: 153418828 153418828 153418828 10.1108/EL-08-2020-0243 153418828 ppf: 572 ppct: 24 formats: tig: atl: A new subject-based retrieval and search result visualization approach for scientific digital libraries. aug: au: Bakhshayesh, Sayed Mahmood Ahmadi, Abbas Mohebi, Azadeh affil: Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran sug: subj: Information Retrieval Methods Libraries, Electronic Human Web Search Engines Science Computerized Literature Searching ab: Purpose: Many search engines in digital libraries are restricted to the terms presented in users' queries. When users cannot represent their information needs in terms of keywords in a query, the search engine fails to provide appropriate results. In addition, most search engines do not have the ability to visualize search results for users to help them in their information journey. The purpose of this paper is to develop a new approach for search result visualization in digital libraries. The visualization approach enables subject-based visualization of search results and search queries. Design/methodology/approach: To enable subject-based visualization of search results in digital libraries, new subject-based document retrieval is proposed in which each document is represented as a vector of subjects as well. Then, using a vector space model for information retrieval, along with the subject-based vector, related documents to the user's query are retrieved, whilst each document is visualized through a ring chart, showing the inherent subjects within each document and the query. Findings: The proposed subject-based retrieval and visualization approach is evaluated from various perspectives to amplify the impact of the visualization approach from users' opinions. Users have evaluated the performance of the proposed subject-based retrieval and search result visualization, whilst 67% of users prefer subject-based document retrieval and 80% of them believe that the proposed visualization approach is practical. Research limitations/implications: This research has provided a subject-based representation scheme for search result visualization in a digital library. The implication of this research can be viewed from two perspectives. First, the subject-based retrieval approach provides an opportunity for the users to understand their information needs, beyond the explicit terms in the query, leading to results, which are semantically relevant to the query. Second, the simple subject-based visualization scheme, helps users to explore the results easily, whilst allowing them to build their knowledge experience. Originality/value: A new vectorized subject-based representation of documents and queries is proposed. This representation determines the semantic and subject-based relationship between a given query and documents within a digital scientific library. In addition, it also provides a subject-based representation of the retrieved documents through which users can track the semantic relationship between the query and retrieve documents, visually. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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