A quantitative study of urban vitality brings new insights for evaluating the external construction environment and internal development power cities. However, it still has limited knowledge relations between people’s diverse life vitality, although activities are often used as proxy vitality. This paper aims to deeply mine content social reveal driving mechanism after inspecting human activities. We propose a general framework exploring spatial pattern using multi-source big data. It builds...

Urban vitality provides an important basis for evaluating urban development and spatial balance. In the era of big data, quantitative analysis has become a research hotspot in field sustainability planning research. However, time variation characteristics are often neglected, which leads to one-sidedness pattern vitality. this paper, method extracting areas integrating spatiotemporal features clustering is proposed. The used divide space into multiple scientifically. temporal distribution...

As urbanization intensifies, congestion and safety concerns in various public venues have garnered significant societal attention, presenting substantial challenges for management emergency response. To address this issue, developing a technological framework capable of automatic perception, analysis, early warning crowd dynamics is urgently needed. Current technologies face hindrances such as low data precision, limited generalization across diverse scenarios, incomplete coverage, sluggish...

Understanding sentiment changes in tourist flow is critical designing exciting experiences for tourists and promoting sustainable tourism development. This paper proposes a novel analytical framework to investigate the between different attractions based on geotagged social media data. Our mainly focuses visualizing detailed of exploring valuable spatiotemporal pattern flow. The were first identified from users. Then, we accurately evaluated by constructing Chinese dictionary, grammatical...

The weighted K-nearest neighbor algorithm (WKNN) is easily implemented, and it has been widely applied. In the large-scale positioning regions, using all fingerprint data in matching calculations would lead to high computation expenses, which not conducive real-time positioning. Due signal instability, irrelevant fingerprints reduce accuracy when performing calculation process. Therefore, selecting appropriate from database more quickly accurately an urgent problem for improving WKNN. This...

The automatic classification of pathological images breast cancer has important clinical value. In order to improve the accuracy and efficiency detection, we implement two classifications in this paper. (1) Train deep convolutional neural network (CNN) models based on AlexNet GoogLeNet structures. (2) Take idea transfer learning complete training models. We use CNN extract image features, then select distinguished features simplify feature set, combine them with texture images. At last, a...

Coverless information hiding has become a hot topic because it can hide secret (SI) into carriers without any modification. Aiming at the problems of low capacity (HC) and mismatch in text big data, novel method coverless by retrieving massive amount web on Internet. First, proposed uses spider technology to capture texts associated with SI construct web-text library. Second, some containing are searched optimal is selected from them. Then, location described using 2-D coordinate system....

As a fundamental component of trajectory processing and analysis, map-matching can be used for urban traffic management tourism route planning, among other applications. While there are many methods, high-sampling-frequency GPS data still depend on simple geometric matching which lead to mismatches when multiple points near one intersection. Therefore, this study proposed novel segmented method in were separated into intersection non-intersection points. Matching rules methods dedicated...

Abstract With the development of mobile positioning technology, a large amount trajectory data has been generated. Therefore, to store, process and mine in better way, simplification is imperative. Current methods are either based on spatiotemporal features or semantic features, such as road network structure, but they do not consider stop. To overcome this limitation, study presents segmentation method stop features. The proposed first extracts feature trajectory, then divides into move...

Microscale research on tourism flows is crucial for controlling such flows, analyzing resource-carrying capacity, and promoting sustainable development in the industry. Current fine-grained monitoring of using location-based big data faces challenges, as inadequate user representation, acquisition difficulties spatiotemporal uncertainty. This study presents a method modeling estimation regional based collaborative perception discrete surveillance videos. The employed bridges gap between...

Urban space vitality is a critical indicator for supporting rational urban spatial planning and updating formulating sustainable development strategies. However, in many areas (e.g., aging areas), there often mismatch between the conditions of physical built environment its attractiveness. Traditional methods based on design theory fail to accurately measure these areas. Street view images directly reflect actual construction situation effectively compensate lack visual, subjective,...

Data-driven urban human activity mining has become a hot topic of dynamic modeling and analysis. Semantic chain with purpose provides scientific methodological support for the analysis decision-making behavior, planning, traffic management, green sustainable development, etc. However, spatial temporal uncertainty ubiquitous mobile sensing data brings huge challenge analyzing activities. Existing approaches identifying activities based on massive social rely large number valid supervised...

Online texts and images have become an important data source for investigating tourism emotion. However, emotion extracted from online cannot reflect the emotions in real world. Few scholarly attempts focused on complex biases based data. By comparing offline emotion, this study quantified explored patterns among biases. Facial expressions within Disney Resort were collected. Based facial expression recognition text mining, several indices proposed to measure Our results reveal that tourists...

Urban functions often diverge from initial planning due to changes driven by residents’ behaviors. Effective urban and renewal require accurately identifying functional regions based on behavior data (including activity travel data). However, previous methods have primarily relied either point of interest (POI) or a single source traffic data, ignore the combined influence activities In this study, we introduce novel framework that integrates multiple sources (such as metro smart card...

While the influence maximization problem (IMP) which studies how to trigger a large cascade in Online Social Networks (OSNs) by properly selecting seed nodes has been extensively studied past decade, one important and practical issue on these or celebrities will get paid for promoting cascades is seldom addressed. In order selected advertising platform maximize his/her own utility, it natural each celebrity determine price of based other celebrities' decisions power influence. this paper, we...

Emotional experience is an important topic in the field of tourism research. Current studies have paid less attention to emotion differences tourist attractions. This paper analyzes type and theme eleven categories Nanjing, was selected as study area. Ten main travel types five themes applied Chinese texts were proposed, expanding dimension existing emotions. The framework extraction constructed by natural language processing deep learning method. results verified that different attractions...

Fieldwork is an important aspect of geography learning in higher educational institutions. Under the support mobile technologies, process and method fieldwork education have significantly been changed. However, in-depth combination Location-Based Services (LBSs) still initial exploration stage. This paper designed implemented a professional platform based on Lushan, famous station Jiangxi, China. The includes student-side application, teacher-side web back-end management system. Three...

Abstract Geographic information system navigation services are now incorporating psychological well‐being as a factor when devising routes. However, challenges such limited data, method generalizability, and subjective human perception remain unresolved. Therefore, general humanized path‐navigation that effectively quantifies emotional demands is required. In this study, we designed deep learning model using large, crowdsourced dataset to predict responses street‐view images. Our enhances...

Vehicle trajectory modelling is an essential foundation for urban intelligent services. In this paper, a novel method, Distant Neighbouring Dependencies (DND) model, has been proposed to transform vehicle trajectories into fixed-length vectors which are then applied predict the final destination. This paper defines problem of neighbouring and distant dependencies first time, puts forward way learn memorize these two kinds dependencies. Next, destination prediction model given based on DND...

In recent years, mobile phone location (MPL) data have been widely used to determine the spatial trajectories of users. Although this massive amount MPL can provide insight into human movement, definite conclusions cannot be drawn because positioning bias: locations are usually not users' actual locations. accuracy has increasingly evaluated. Such efforts led many insights regarding quality and applicability data. Despite these achievements, best our knowledge, no studies quantitatively...