# Comprehensive Review and Future Research Directions on Dynamic Faceted Search
## 4 Materials and Methods  
As mentioned in the Introduction, in this research, we followed the SLR method to collect the related research articles based on two concepts: \"faceted search\" and \"refining information\". The research article collection was carried out via three reputed digital libraries; (1) Web of Science, as it provides multidisciplinary research articles in the fields of science; (2) IEEE explore, which provides articles specialized in the field of electrical and electronics engineering; (3) the ACM digital library, which has a comprehensive database for computing and information technology. Many searches on the three mentioned databases were performed in July 2021 using several keywords (or phrases) such as \"faceted search\", \"faceted-search\", \"faceted model\", \"faceted taxonomy\", \"faceted\", \"faceted applications\", \"faceted browsing\", and \"faceted classification\". The keywords were only slightly different. Subsequently, these keywords were joined using the conjunctions \"OR\" and \"AND\" followed by \"Refining Information\". Figure 3 shows the search queries that were used in this work. We excluded some results corresponding to letters, magazine articles, and book chapters. The main goal of this exclusion was to obtain the most recent scientific articles and enhance the FS application's capability to refine information. Then, the results were divided into two classes: (1) general and (2) coarse-gained. The latter is discussed in five subsequent sections obtained from the study results in which the Google Scholar SE was utilized to define the study's direction. The significance of the collected articles was evaluated to retain the most related articles among a large number of collected literature articles. Moreover, the included articles were categorized based on two criteria: (1) performing the initial screening to identify the relevant results; (2) applying three iterations in the filtering process to remove the redundant and duplicated articles. As highlighted earlier, an article was excluded if it did not satisfy the selection criteria listed as follows: (1) the English language is not the language used to write the paper; (2) faceted search and/or information refining were the main focus of the paper; (3) the research interest in the paper was only concentrated on FS without information refinement. Moreover, after the second exclusion cycle, the articles could be eliminated if ES was not included or: (1) the contribution of the paper did not consider any aspects of refining information based on FS; (2) the discussion in the paper was only focused on refining information based on FS and did not consider any other topic. In this work, articles underwent extensive filtration, whereby the remaining articles were later categorized into five categories based on the proposed methods to enhance FS in refining information. The categories were: (1) review and surveys, (2) faceted models, (3) graphical models, (4) evaluation measures, and (5) faceted technologies. Subsequently, further subcategorization was performed according to the authors' writing and presentation of the articles to readers. Figure 3 illustrates our results where there were 2343 research articles gathered based on the user queries, of which 554 were obtained from WOS, 1331 from IEEE, and 458 from ACM digital libraries. All selected articles were published between 2005 and 2021. These articles were later divided into three groups: (1) 561 redundant articles, (2) 1255 irrelevant based on the titles and abstracts, and (3) the 170 articles that fell within the FS search criteria. Figure 4 presents the statistics of the different categories above for the articles related to FS. In the figure, it can be seen that the 170 articles from the three databases were divided into review and surveys (25), faceted models (35), graphical models (30), evaluation measures (36), and faceted technologies--those that describe enhancement to FS (44).