Web Query Behaviour Concerning HEV (Blue) Light in Ophthalmology

Background: High-energy visible (HEV) possesses high-frequency in the violet-blue band of the visible light spectrum. Blue light has relevance to ophthalmology via photochemically-induced retinal injury. Objectives: To explore the spatial-temporal mapping of online search behavior concerning HEV light. Materials and Methods: We retrieved raw data of web search volume, via Microsoft Google Trends, using five search topics; "Biological effects of HEV light", "Vision impairment", "Macular degeneration", "Retinal tear", and "Retinal detachment", for the period 2004-2020. Results: Web users, mainly from Far-East Asia and Australasia, were most interested in seeking online information concerning "Macular degeneration" and "Vision impairment" search topics, moderately interested in "Biological effects of HEV light" and "Retinal detachment", and least interested in "Retinal tear". Internet users from the Middle East and Arab world contributed minimally to the holistic map. Web queries increased at both chronological ends, 2004-2006 and 2018-2020; however, these trends were respondent to specific search topics. For instance, the search volume for the "Biological effects of HEV light" increased significantly in 2018-2020. Predictive modeling was most accurate for "Biological effects of HEV light". The strongest correlation was for "Vision impairment" versus "Macular degeneration". ANOVA, linear modeling, and machine learning unanimously agreed on predictors' significant effect (search topics and time) on the web search volume. Conclusion: Web queries' mapping provided indirect evidence on the causality between HEV light and retinal damage. Future research mandates rigor observational and experimental studies.

Horizontal Web Searching and Navigational Resource Identification

Generally speaking, horizontal search engines are meant to deal with general web queries. In the context of this chapter, the authors investigated the act of navigational resource identification in the light of horizontal web searching. State-of-the-art navigational resource identification is reluctant to the distinct characteristics of the navigational queries and specific users' treatments toward different searching tasks. Consequently, in this chapter, the authors discussed a new mechanism for navigational resource identification according to previous findings.

A Survey on Automatically Mining Facets for Web Queries

In this paper, a detailed survey on different facet mining techniques, their advantages and disadvantages is carried out. Facets are any word or phrase which summarize an important aspect about the web query. Researchers proposed different efficient techniques which improves the user’s web query search experiences magnificently. Users are happy when they find the relevant information to their query in the top results. The objectives of their research are: (1) To present automated solution to derive the query facets by analyzing the text query; (2) To create taxonomy of query refinement strategies for efficient results; and (3) To personalize search according to user interest.