Document Type : Original Article
Authors
1 PhD student, Department of Information Science and Epistemology, Babol Branch, Islamic Azad University, Babol, Iran
2 Associate Professor, Department of Information Science and Epistemology, Babol Branch, Islamic Azad University, Babol, Iran
3 Associate Professor, Department of Information Science and Epistemology, Babol Branch, Islamic Azad University, Babol, Iran.
Abstract
Purpose: Ambiguity is one of the challenges that its creation and resolution has a great impact on the efficiency and accuracy of information storage and retrieval systems.
Methodology: The current research is applied in terms of purpose and qualitative in terms of method and with a grounded theory approach (Foundation base). The research participant,18 subject experts were selected to the subject, were selected as a snowball. A semi-structured interview technique was used to collect data. Software MAXQDA 20 was used to analyze and code the participants' data.
Findings:The most important category in ambiguity is "inherent ambiguity"(6 sub-categories, 25%) and the least is "intentional ambiguity and sentence structural ambiguity"(2 sub-categories,8.4%). Also, the most interfering category in creating ambiguity was "intentional and unintentional ambiguity"(7sub-categories, 41%) and the least category was "inauthentic sources"(1sub-category, 7%).
Conclusion:The results show that from the point of view of subject matter experts, ambiguous factors in information storage and retrieval systems include: written ambiguity, intentional ambiguity, spoken ambiguity, inherent ambiguity, semantic ambiguity of words, structural ambiguity of sentences, Structural ambiguity in data and ambiguous intervening factors include: intentional ambiguity, unintentional ambiguity, information retrieval algorithms, invalid sources.
value: The researches that have been carried out so far in the field of ambiguity factors by Iranian and non-Iranian researchers are mostly of quantitative type and have mostly investigated the technical aspect of this issue. In the current research, the foundation data approach has provided the possibility of summarizing opinions and discovering causal and intervening factors, which have not been studied before.
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