2017/01/10 by Anasua Mitra, Mitra, Anasua, Amit Awekar +1
Computer Science · #Advanced Text Analysis Techniques #Digital Libraries (cs.DL) #FOS: Computer and information sciences #H.3.3 #Information Retrieval (cs.IR) #Information Retrieval and Search Behavior #Web Data Mining and Analysis
paper · pdf · doi:10.48550/arxiv.1701.02617
openalex publication_date 2017/01/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Number of published scholarly articles is growing exponentially. To tackle this information overload, researchers are increasingly depending on niche academic search engines. Recent works have shown that two major general web search engines: Google and Bing, have high level of agreement in their top search results. In contrast, we show that various academic search engines have low degree of agreement among themselves. We performed experiments using 2500 queries over four academic search engines. We observe that overlap in search result sets of any pair of academic search engines is significantly low and in most of the cases the search result sets are mutually exclusive. We also discuss implications of this low overlap.