@misc{10481/99480,
year = {2024},
month = {12},
url = {https://hdl.handle.net/10481/99480},
abstract = {The explosive growth of Internet of Things (IoT) and Web of Things (WoT) technologies, characterized by a vast diversity of devices and data formats, producing vast volumes of information at a high pace in real time necessitates a paradigm shift in Information Retrieval (IR) systems. Traditional IR struggles to navigate the dynamic landscapes of these interconnected environments. This work proposes a multi-dimensional taxonomy framework to bridge this critical gap. Our framework not only unifies existing classification approaches but also delves into the analysis of traditional IR sub-tasks, thereby establishing a cohesive foundation for future advancements in IR tailored to the evolving IoT/WoT landscape. We further contribute by identifying key challenges and posing open research questions, thus propelling the development of next-generation IR techniques specifically tailored to the intricate search demands of the evolving IoT and WoT cyber-world.},
publisher = {IEEE},
keywords = {Systematic Literature Review},
keywords = {Internet of Things},
keywords = {Information Retrieval},
keywords = {Taxonomy},
keywords = {Search Engines},
keywords = {Protocols},
keywords = {Surveys},
keywords = {Web of Things},
title = {Information Retrieval for IoT and WoT: State-of-the-Art, Taxonomy Framework, and Evolutionary Directions},
doi = {10.1109/JIOT.2024.3522219},
author = {Manta Caro, Héctor Cristyan and Fernández Luna, Juan Manuel},
}