Image search and retrieval problems in web search engines

Abstract

Purpose The purpose of this paper is to investigate image search and retrieval problems in selected search engines in relation to Persian writing style challenges. Design/methodology/approach This study is an applied one, and to answer the questions the authors used an evaluative research method. The aim of the research is to explore the morphological and semantic problems of Persian language in connection with image search and retrieval among the three major and widespread search engines: Google, Yahoo and Bing. In order to collect the data, a checklist designed by the researcher was used and then the data were analyzed by descriptive and inferential statistics. Findings The results indicate that Google, Yahoo and Bing search engines do not pay enough attention to morphological and semantic features of Persian language in image search and retrieval. This research reveals that six groups of Persian language features include derived words, derived/compound words, Persian and Arabic Plural words, use of dotted T and the use of spoken language and polysemy, which are the major problems in this area. In addition, the results suggest that Google is the best search engine of all in terms of compatibility with Persian language features. Originality/value This study investigated some new aspects of the above-mentioned subject through combining morphological and semantic aspects of Persian language with image search and retrieval. Therefore, this study is an interdisciplinary research, the results of which would help both to offer some solutions and to carry out similar research on this subject area. This study will also fill a gap in research studies conducted so far in this area in Farsi language, especially in image search and retrieval. Moreover, findings of this study can help to bridge the gap between the user’s questions and search engines (systems) retrievals. In addition, the methodology of this paper provides a framework for further research on image search and retrieval in databases and search engines.