In order to prevent the formation of a gap between the quality and quantity in Iranian scientific publications, this study makes an effort to analyze Iranian scientific publications indexed on the ISI Web of Science database using quantitative and qualitative scientometrics criteria over a ten year period. As a first step, all Iranian institutes were divided into three categories; universities, research institutes and other organizations. Then they were compared according to quantitative and qualitative criteria. Second, the correlation between the quality and quantity of the publications was measured. The research findings indicated that, according to qualitative criteria (citation, citation impact and percentage of cited documents) there are no meaningful differences among the three groups, while regarding quantitative criterion(number of papers), universities rank higher than the other two groups. The results also indicated that there is a positive and meaningful correlation among qualitative and quantitative criteria in the scholarly scientific publications conducted by Iranian organizations. In other words, in Iranian organizations the quality of publications increases as their quantity increases. The comparison of magnitude of correlation between these two criteria in the three categories reveals the fact that the correlation between number of papers and citations criterion in research institutes is stronger than the other two groups.

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This study aims at introducing a new source for translation and expansion of user queries in Persian language in order to develop a bilingual dictionary. For the purpose of this study, required data were extracted and processed from English and Persian bibliographic information of journal articles to develop a dictionary for query translation and expansion, denoted as Query Expansion Assistant Database (QEAD). In this study, psychology and educational sciences journals have been selected as the sample with the potential of extension to other domains. Persian–English authors’ keywords were used for translation part and titles of English references were used to extract phrases using natural language processing techniques for the expansion part. The proposed algorithm is demonstrated. Then we evaluated this approach using human evaluation by using Google translate (GT) and Google scholar. Although the evaluation of translation part indicated 60% match between GT and QEAD, in 40% of unmatched translations, QEAD showed a better performance according to expert evaluators. Expansion part of QEAD was compared with Google scholar suggestions, which indicated that the expanded words of QEAD can equalize with Google scholar suggestions. Persian as a low resource language needs more qualified lexicon translation. In addition, using the English–Persian bibliographic information of scientific journals to mine lexicon translation is conducted for the first time. Since these journals are peer-reviewed, they can be a valuable source for translation of user’s query. Users can be informed of the most prevalent and up-to-date words or phrases among scientists, because journals are published frequently.