Using Machine Learning and Natural Language Processing to Analyze Library Chat Reference Transcripts.
The use of artificial intelligence and machine learning has rapidly become a standard technology across all industries and businesses for gaining insight and predicting the future. In recent years, the library community has begun looking at ways to improve library services by applying AI and machine...
| Publicado en: | Information Technology & Libraries Vol. 41; no. 3; pp. 1 - 11 |
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| Autor principal: | |
| Formato: | research tables/charts Journal Article |
| Publicado: |
American Library Association
Sep2022
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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=159462251&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159462251 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 07309295 ITL jtl: Information Technology & Libraries issn: 07309295 maglogo: N pubinfo: dt: Sep2022 vid: 41 iid: 3 pid: 55 pub: American Library Association place: Chicago, Illinois artinfo: ui: 159462251 159462251 159462251 10.6017/ital.v41i3.14967 159462251 ppf: 1 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Using Machine Learning and Natural Language Processing to Analyze Library Chat Reference Transcripts. aug: au: Yongming Wang affil: Systems Librarian, The College of New Jersey sug: subj: Machine Learning Natural Language Processing Library Reference Services Libraries, Academic Human Library Automation Qualitative Studies Quantitative Studies Information Needs Information Seeking Behavior Pilot Studies ab: The use of artificial intelligence and machine learning has rapidly become a standard technology across all industries and businesses for gaining insight and predicting the future. In recent years, the library community has begun looking at ways to improve library services by applying AI and machine learning techniques to library data. Chat reference in libraries generates a large amount of data in the form of transcripts. This study uses machine learning and natural language processing methods to analyze one academic library's chat transcripts over a period of eight years. The built machine learning model tries to classify chat questions into a category of reference or nonreference questions. The purpose is to predict the category of future questions by the model with the hope that incoming questions can be channeled to appropriate library departments or staff. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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