2021/10/14 by Xuesong Chen, Chen, Xuesong, Ziyi Ye +13 · 2 citations
Computer Science · Engineering · Neuroscience · #Advanced Memory and Neural Computing #Computer science #Context (archaeology) #Decoding methods #EEG and Brain-Computer Interfaces #FOS: Computer and information sciences #Human–computer interaction #Information Retrieval (cs.IR) #Information retrieval #Interface (matter) #Machine learning #Neural dynamics and brain function #Operating system #Process (computing) #Rank (graph theory) #Search engine #User interface #cs.IR
paper · pdf · doi:10.48550/arxiv.2110.07225
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2021/10/14 · arxiv created 2021/10/15 · arxiv updated 2021/10/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
While search technologies have evolved to be robust and ubiquitous, the fundamental interaction paradigm has remained relatively stable for decades. With the maturity of the Brain-Machine Interface, we build an efficient and effective communication system between human beings and search engines based on electroencephalogram(EEG) signals, called Brain-Machine Search Interface(BMSI) system. The BMSI system provides functions including query reformulation and search result interaction. In our system, users can perform search tasks without having to use the mouse and keyboard. Therefore, it is useful for application scenarios in which hand-based interactions are infeasible, e.g, for users with severe neuromuscular disorders. Besides, based on brain signals decoding, our system can provide abundant and valuable user-side context information(e.g., real-time satisfaction feedback, extensive context information, and a clearer description of information needs) to the search engine, which is hard to capture in the previous paradigm. In our implementation, the system can decode user satisfaction from brain signals in real-time during the interaction process and re-rank the search results list based on user satisfaction feedback. The demo video is available at http://www.thuir.cn/group/YQLiu/datasets/BMSISystem.mp4.