我个人的理解重点其实是人为定义的，对同一份内容，不同需求的阅读者就会有不同的重点倾向，如果在summary后面加上想关注的主题我觉得效果还是不错的，下面是我测试的一个例子：
Question: Summarize the papers, focus on their advances
The papers discussed in Sakpere2017 and Kunhoth2020 focus on advances in indoor positioning and wayfinding systems. Sakpere2017 provides a state-of-the-art survey of indoor positioning and navigation systems, discussing the strengths and limitations of various positioning techniques and technologies and proposing possible research directions for further improvement. The studies discussed in Sakpere2017 pages 21-22 focus on improving indoor positioning and tracking systems using magnetic fields, with advances in excitation of magnetic sources, sensor output, and sensor positions. Kunhoth2020 discusses three different indoor positioning and wayfinding systems, including advances in keyframe extraction, topological map creation, localization, routing, barcode-based navigation, and wearable virtual ushers. Other papers discussed in Kunhoth2020 pages 19-20 and Kunhoth2020 pages 37-37 propose advances in building distinct models for different indoor environments, efficient signal processing, and improved accuracy in challenging environments.
Question: Summarize the papers, focus on related works
There are several papers related to indoor positioning and wayfinding systems. WLAN fingerprinting methods for indoor positioning have been proposed by Kaemarungsi (2005), Jiang (2012), and Niu et al. (2013) with varying degrees of accuracy and energy efficiency (Sakpere2017 pages 30-31). Computer vision-based line segment matching and trifocal tensor have been proposed for indoor navigation, as well as detecting doors in indoor areas using a miniature camera and a computer with a door detection algorithm (Kunhoth2020 pages 10-11). Other related works include foot-mounted inertial systems, substitute vision systems, and GPS-enabled mobile phones, as well as feature detection and matching, deep learning, and wearable RGBD indoor navigation systems (Kunhoth2020 pages 35-36). Additionally, there are papers on object recognition, scene labeling, and navigation systems for the visually impaired (Kunhoth2020 pages 37-37). The papers are summarized briefly and include direct links to their respective sources (Kunhoth2020 pages 37-37).
References
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(Sakpere2017): Sakpere, Wilson, Michael Adeyeye-Oshin, and Nhlanhla B.W. Mlitwa. "A state-of-the-art survey of indoor positioning and navigation systems and technologies." South African Computer Journal 29.3 (2017): 145-197. https://doi.org/10.18489/sacj.v29i3.452.
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(Kunhoth2020): Kunhoth, Jayakanth, et al. "Indoor positioning and wayfinding systems: a survey." Journal of Ambient Intelligence and Humanized Computing, vol. 11, no. 5, 2020, pp. 2145-2167.
我个人的理解重点其实是人为定义的，对同一份内容，不同需求的阅读者就会有不同的重点倾向，如果在summary后面加上想关注的主题我觉得效果还是不错的，下面是我测试的一个例子：
Question: Summarize the papers, focus on their advances
The papers discussed in Sakpere2017 and Kunhoth2020 focus on advances in indoor positioning and wayfinding systems. Sakpere2017 provides a state-of-the-art survey of indoor positioning and navigation systems, discussing the strengths and limitations of various positioning techniques and technologies and proposing possible research directions for further improvement. The studies discussed in Sakpere2017 pages 21-22 focus on improving indoor positioning and tracking systems using magnetic fields, with advances in excitation of magnetic sources, sensor output, and sensor positions. Kunhoth2020 discusses three different indoor positioning and wayfinding systems, including advances in keyframe extraction, topological map creation, localization, routing, barcode-based navigation, and wearable virtual ushers. Other papers discussed in Kunhoth2020 pages 19-20 and Kunhoth2020 pages 37-37 propose advances in building distinct models for different indoor environments, efficient signal processing, and improved accuracy in challenging environments.
Question: Summarize the papers, focus on related works
There are several papers related to indoor positioning and wayfinding systems. WLAN fingerprinting methods for indoor positioning have been proposed by Kaemarungsi (2005), Jiang (2012), and Niu et al. (2013) with varying degrees of accuracy and energy efficiency (Sakpere2017 pages 30-31). Computer vision-based line segment matching and trifocal tensor have been proposed for indoor navigation, as well as detecting doors in indoor areas using a miniature camera and a computer with a door detection algorithm (Kunhoth2020 pages 10-11). Other related works include foot-mounted inertial systems, substitute vision systems, and GPS-enabled mobile phones, as well as feature detection and matching, deep learning, and wearable RGBD indoor navigation systems (Kunhoth2020 pages 35-36). Additionally, there are papers on object recognition, scene labeling, and navigation systems for the visually impaired (Kunhoth2020 pages 37-37). The papers are summarized briefly and include direct links to their respective sources (Kunhoth2020 pages 37-37).
References
(Sakpere2017): Sakpere, Wilson, Michael Adeyeye-Oshin, and Nhlanhla B.W. Mlitwa. "A state-of-the-art survey of indoor positioning and navigation systems and technologies." South African Computer Journal 29.3 (2017): 145-197. https://doi.org/10.18489/sacj.v29i3.452.
(Kunhoth2020): Kunhoth, Jayakanth, et al. "Indoor positioning and wayfinding systems: a survey." Journal of Ambient Intelligence and Humanized Computing, vol. 11, no. 5, 2020, pp. 2145-2167.