本文選題：信息檢索 + 科學數據��； 參考：《數字圖書館論壇》2017年11期

【摘要】：通過對科學數據用戶相關性判斷行為的研究,探索科學數據相關性判斷過程中所使用的指標及模式,加深對科學數據相關性判定機制的理解,為設計開發(fā)智能化數據搜索引擎提供算法和理論支撐。使用出聲思考和事后訪談兩種方法對用戶相關性判斷行為進行研究。數據在真實的環(huán)境中收集,使用攝像機記錄實驗過程,采用扎根理論對訪談數據進行編碼分析。在定性研究的基礎上設計問卷,開展大樣本問卷調查�？茖W數據用戶相關性判斷過程使用的標準可以分為數據本體性和數據可用性兩類,共9個指標。與其他信息類型相比,科學數據檢索有更強的目的性,相關性判斷過程不能缺少對數據主題性、質量和權威性的評估,其他指標在具體情境中,只有受到相關信息需求刺激才會調用。
[Abstract]:Through the research on the behavior of scientific data user correlation judgment, this paper explores the indicators and models used in the process of scientific data correlation judgment, and deepens the understanding of the scientific data correlation judgment mechanism. It provides algorithm and theory support for design and development of intelligent data search engine. This paper studies the behavior of user correlation judgment by means of sound thinking and post-interview. The data is collected in real environment, the experimental process is recorded by video camera, and the interview data is coded and analyzed by root theory. On the basis of qualitative research, a large sample questionnaire was designed. The criteria used in the process of determining the relevance of scientific data users can be divided into two categories: data ontology and data availability. Compared with other types of information, scientific data retrieval has a stronger purpose, correlation judgment process can not be lack of data thematic, quality and authoritative evaluation, other indicators in specific situations, It is called only if stimulated by the need for relevant information.
【作者單位】： 中國農業(yè)科學院農業(yè)信息研究所;國家科技基礎條件平臺中心;
【基金】：中國農業(yè)科學院科技創(chuàng)新工程項目(編號:CAAS-ASTIP-2016-AII)資助
【分類號】：G353.1
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本文編號：1964425