With the rapid development and wide use of Global Positioning System in technology tools, such as smart phones and touch pads, many people share their personal experience through their trajectories while visiting plac...With the rapid development and wide use of Global Positioning System in technology tools, such as smart phones and touch pads, many people share their personal experience through their trajectories while visiting places of interest. Therefore, trajectory query processing has emerged in recent years to help users find their best trajectories. However, with the huge amount of trajectory points and text descriptions, such as the activities practiced by users at these points, organizing these data in the index becomes tedious. Therefore, the parallel method becomes indispensable. In this paper, we have investigated the problem of distributed trajectory query processing based on the distance and frequent activities. The query is specified by start and final points in the trajectory, the distance threshold, and a set of frequent activities involved in the point of interest of the trajectory.As a result, the query returns the shortest trajectory including the most frequent activities with high support and high confidence. To simplify the query processing, we have implemented the Distributed Mining Trajectory R-Tree index(DMTR-Tree). For this method, we initially managed the large trajectory dataset in distributed R-Tree indexes.Then, for each index, we applied the frequent itemset Apriori algorithm for each point to select the frequent activity set. For the faster computation of the above algorithms, we utilized the cluster computing framework of Apache Spark with MapReduce as the programing model. The experimental results show that the DMTR-Tree index and the query-processing algorithm are efficient and can achieve the scalability.展开更多
Driven by the flourish of location-based services, trajectory search has received significant attentions in recent years. Different from existing studies that focus on searching trajectories with spatio-temporal infor...Driven by the flourish of location-based services, trajectory search has received significant attentions in recent years. Different from existing studies that focus on searching trajectories with spatio-temporal information and text de-scriptions, we study a novel problem of searching trajectories with spatial distance, activities, and rating scores. Given a query q with a threshold of distance, a set of activities, a start point S and a destination E, trip oriented search on activity trajectory （TOSAT） returns k trajectories that can cover the activities with the highest rating scores within the threshold of distance. In addition, we extend the query with an order, i.e., order-sensitive trip oriented search on activity trajectory （OTOSAT）, which takes both the order of activities in a query q and the order of trajectories into consideration. It is very challenging to answer TOSAT and OTOSAT e？ciently due to the structural complexity of trajectory data with rating infor-mation. In order to tackle the problem e？ciently, we develop a hybrid index AC-tree to organize trajectories. Moreover, the optimized variant RAC＋-tree and novel algorithms are introduced with the goal of achieving higher performance. Extensive experiments based on real trajectory datasets demonstrate that the proposed index structures and algorithms are capable of achieving high e？ciency and scalability.展开更多
Scientists have long debated the relative importance of tropospheric photochemical production versus stratospheric influx as causes of the springtime tropospheric ozone maximum over northern mid-latitudes. This paper ...Scientists have long debated the relative importance of tropospheric photochemical production versus stratospheric influx as causes of the springtime tropospheric ozone maximum over northern mid-latitudes. This paper investigates whether or not stratospheric intrusion and photochemistry play a significant role in the springtime ozone maximum over Northeast Asia, where ozone measurements are sparse. We examine how tropospheric ozone seasonalities over Naha （26°N, 128°E）, Kagoshima （31°N, 131°E）, and Pohang （36°N, 129°E）, which are located on the same meridional line, are related to the timing and location of the jet stream. The ozone seasonality shows a gradual increase from January to the maximum ozone month, which corresponds to April at Naha, May at Kagoshima, and June at Pohang. In order to examine the occurrence of stratospheric intrusion, we analyze a correlation between jet stream activity and tropospheric ozone seasonality. From these analyses, we did not find any favorable evidence supporting the hypothesis that the springtime enhancement may result from stratospheric intrusion. According to trajectory analysis for vertical and horizontal origins of the airmass, a gradual increasing tendency in ozone amounts from January until the onset of monsoon was similar to the increasing ozone formation tendency from winter to spring over China's Mainland, which has been observed during the build-up of tropospheric ozone over Central Europe in the winter-spring transition period due to photochemistry. Overall, the analyses suggest that photochemistry is the most important contributor to observed ozone seasonality over Northeast Asia.展开更多
With the widespread use of smart phones and mobile Internet,social network users have generated massive geo-tagged tweets,photos and videos to form lots of informative trajectories which reveal not only their spatio-t...With the widespread use of smart phones and mobile Internet,social network users have generated massive geo-tagged tweets,photos and videos to form lots of informative trajectories which reveal not only their spatio-temporal dynamics,but also their activities in the physical world.Existing spatial trajectory query studies mainly focus on analyzing the spatio-temporal properties of the users'trajectories,while leaving the understanding of their activities largely untouched.In this paper,we incorporate the semantics of the activity information embedded in trajectories into query modelling and processing,with the aim of providing end users more informative and meaningful results.To this end,we propose a novel trajectory query that not only considers the spatio-temporal closeness but also,more importantly,leverages a proven technique in text mining field,probabilistic topic modelling,to capture the semantic relatedness of the activities between the data and query.To support efficient query processing,we design a hierarchical grid-based index by integrating the probabilistic topic distribution on the substructures of trajectories and their spatio-temporal extent at the corresponding level of the index hierarchy.This specialized structure enables a top-down search algorithm to traverse the index while pruning unqualified trajectories in spatial and topical dimensions simultaneously.The experimental results on real-world datasets demonstrate the good efficiency and scalability performance of the proposed indices and trajectory search methods.展开更多
基金partially supported by the National Natural Science Foundation of China (Nos. U1509216 and 61472099)the National Sci-Tech Support Plan (No. 2015BAH10F01)+1 种基金the Scientific Research Foundation for the Returned Overseas Chinese Scholars of Heilongjiang Provience (No. LC2016026)MOECMicrosoft Key Laboratory of Natural Language Processing and Speech, Harbin Institute of Technology
文摘With the rapid development and wide use of Global Positioning System in technology tools, such as smart phones and touch pads, many people share their personal experience through their trajectories while visiting places of interest. Therefore, trajectory query processing has emerged in recent years to help users find their best trajectories. However, with the huge amount of trajectory points and text descriptions, such as the activities practiced by users at these points, organizing these data in the index becomes tedious. Therefore, the parallel method becomes indispensable. In this paper, we have investigated the problem of distributed trajectory query processing based on the distance and frequent activities. The query is specified by start and final points in the trajectory, the distance threshold, and a set of frequent activities involved in the point of interest of the trajectory.As a result, the query returns the shortest trajectory including the most frequent activities with high support and high confidence. To simplify the query processing, we have implemented the Distributed Mining Trajectory R-Tree index(DMTR-Tree). For this method, we initially managed the large trajectory dataset in distributed R-Tree indexes.Then, for each index, we applied the frequent itemset Apriori algorithm for each point to select the frequent activity set. For the faster computation of the above algorithms, we utilized the cluster computing framework of Apache Spark with MapReduce as the programing model. The experimental results show that the DMTR-Tree index and the query-processing algorithm are efficient and can achieve the scalability.
基金This work was supported by the National Natural Science Foundation of China under Grant Nos. 61073061, 61303019, 61003044, 61232006, 61472263, 61402312, and 61402313, the Doctoral Fund of Ministry of Education of China under Grant No. 20133201120012, and Jiangsu Provincial Department of Education under Grant No. 12KJB520017.
文摘Driven by the flourish of location-based services, trajectory search has received significant attentions in recent years. Different from existing studies that focus on searching trajectories with spatio-temporal information and text de-scriptions, we study a novel problem of searching trajectories with spatial distance, activities, and rating scores. Given a query q with a threshold of distance, a set of activities, a start point S and a destination E, trip oriented search on activity trajectory （TOSAT） returns k trajectories that can cover the activities with the highest rating scores within the threshold of distance. In addition, we extend the query with an order, i.e., order-sensitive trip oriented search on activity trajectory （OTOSAT）, which takes both the order of activities in a query q and the order of trajectories into consideration. It is very challenging to answer TOSAT and OTOSAT e？ciently due to the structural complexity of trajectory data with rating infor-mation. In order to tackle the problem e？ciently, we develop a hybrid index AC-tree to organize trajectories. Moreover, the optimized variant RAC＋-tree and novel algorithms are introduced with the goal of achieving higher performance. Extensive experiments based on real trajectory datasets demonstrate that the proposed index structures and algorithms are capable of achieving high e？ciency and scalability.
基金supported by Research Agency for Climate Science funded by Korea Meteorological Administration(RACS 2010-1011)
文摘Scientists have long debated the relative importance of tropospheric photochemical production versus stratospheric influx as causes of the springtime tropospheric ozone maximum over northern mid-latitudes. This paper investigates whether or not stratospheric intrusion and photochemistry play a significant role in the springtime ozone maximum over Northeast Asia, where ozone measurements are sparse. We examine how tropospheric ozone seasonalities over Naha （26°N, 128°E）, Kagoshima （31°N, 131°E）, and Pohang （36°N, 129°E）, which are located on the same meridional line, are related to the timing and location of the jet stream. The ozone seasonality shows a gradual increase from January to the maximum ozone month, which corresponds to April at Naha, May at Kagoshima, and June at Pohang. In order to examine the occurrence of stratospheric intrusion, we analyze a correlation between jet stream activity and tropospheric ozone seasonality. From these analyses, we did not find any favorable evidence supporting the hypothesis that the springtime enhancement may result from stratospheric intrusion. According to trajectory analysis for vertical and horizontal origins of the airmass, a gradual increasing tendency in ozone amounts from January until the onset of monsoon was similar to the increasing ozone formation tendency from winter to spring over China's Mainland, which has been observed during the build-up of tropospheric ozone over Central Europe in the winter-spring transition period due to photochemistry. Overall, the analyses suggest that photochemistry is the most important contributor to observed ozone seasonality over Northeast Asia.
基金the National Natural Science Foundation of China under Grant No.61872100.
文摘With the widespread use of smart phones and mobile Internet,social network users have generated massive geo-tagged tweets,photos and videos to form lots of informative trajectories which reveal not only their spatio-temporal dynamics,but also their activities in the physical world.Existing spatial trajectory query studies mainly focus on analyzing the spatio-temporal properties of the users'trajectories,while leaving the understanding of their activities largely untouched.In this paper,we incorporate the semantics of the activity information embedded in trajectories into query modelling and processing,with the aim of providing end users more informative and meaningful results.To this end,we propose a novel trajectory query that not only considers the spatio-temporal closeness but also,more importantly,leverages a proven technique in text mining field,probabilistic topic modelling,to capture the semantic relatedness of the activities between the data and query.To support efficient query processing,we design a hierarchical grid-based index by integrating the probabilistic topic distribution on the substructures of trajectories and their spatio-temporal extent at the corresponding level of the index hierarchy.This specialized structure enables a top-down search algorithm to traverse the index while pruning unqualified trajectories in spatial and topical dimensions simultaneously.The experimental results on real-world datasets demonstrate the good efficiency and scalability performance of the proposed indices and trajectory search methods.
