Workshop on Location-based Social Networks最新文献_第6页

Proximate sensing using georeferenced community contributed photo collections 利用地理参考社区提供的图片集进行近似值传感

Workshop on Location-based Social Networks Pub Date : 2009-11-03 DOI: 10.1145/1629890.1629903

Daniel Leung, S. Newsam

引用次数: 9

An efficient pre-computation technique for approximation KNN search in road networks 道路网络中近似KNN搜索的一种高效预计算技术

Workshop on Location-based Social Networks Pub Date : 2009-11-03 DOI: 10.1145/1629890.1629899

Guangzhong Sun, Zhong Zhang, Jing Yuan

引用次数: 4

Less-conscious information retrieval techniques for location based services 基于位置服务的低意识信息检索技术

Workshop on Location-based Social Networks Pub Date : 2009-11-03 DOI: 10.1145/1629890.1629905

K. Sumiya

引用次数: 0

Joint learning user's activities and profiles from GPS data 从GPS数据中联合学习用户的活动和概况

Workshop on Location-based Social Networks Pub Date : 2009-11-03 DOI: 10.1145/1629890.1629894

V. Zheng, Yu Zheng, Qiang Yang

{"title":"Joint learning user's activities and profiles from GPS data","authors":"V. Zheng, Yu Zheng, Qiang Yang","doi":"10.1145/1629890.1629894","DOIUrl":"https://doi.org/10.1145/1629890.1629894","url":null,"abstract":"As the GPS-enabled mobile devices become extensively available, we are now given a chance to better understand human behaviors from a large amount of the GPS trajectories representing the mobile users' location histories. In this paper, we aim to establish a framework, which can jointly learn the user activities (what is the user doing) and profiles (what is the user's background, such as occupation, gender, age, etc.) from the GPS data. We will show that, learning user activities and learning user profiles can be beneficial to each other in nature, so we try to put them together and formulate a joint learning problem under a probabilistic collaborative filtering framework. In particular, for activity recognition, we manage to extract the location semantics from the raw GPS data and use it, together with the user profile, as the input; and we will output the corresponding activities of daily living. For user profile learning, we build a mobile social network among the users by modeling their similarities with the performed activities and known user backgrounds. Compared with the other work on solely learning user activities or profiles from GPS data, our approach is advantageous by exploiting the connections between the user activities and profiles for joint learning.","PeriodicalId":107369,"journal":{"name":"Workshop on Location-based Social Networks","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122297492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 30

Overcoming challenges in delivering services to social networks in location centric scenarios 克服在以位置为中心的场景中向社交网络提供服务的挑战

Workshop on Location-based Social Networks Pub Date : 2009-11-03 DOI: 10.1145/1629890.1629910

T. Lange, M. Kowalkiewicz, T. Springer, T. Raub

引用次数: 2

A case for space: physical and virtual location requirements in the CouchSurfing social network 空间的一个案例:CouchSurfing社交网络中的物理和虚拟位置需求

Workshop on Location-based Social Networks Pub Date : 2009-11-03 DOI: 10.1145/1629890.1629909

Edward Pultar, M. Raubal

引用次数: 18

SoNavNet: a framework for social navigation networks SoNavNet:一个社会导航网络的框架

Workshop on Location-based Social Networks Pub Date : 2009-11-03 DOI: 10.1145/1629890.1629908

H. Karimi, Benjamin Zimmerman, Alper Ozcelik, Duangduen Asavasuthirakul

引用次数: 39

From trajectories to activities: a spatio-temporal join approach 从轨迹到活动:一种时空连接方法

Workshop on Location-based Social Networks Pub Date : 2009-11-03 DOI: 10.1145/1629890.1629897

Kexin Xie, K. Deng, Xiaofang Zhou

引用次数: 78

Skyline queries based on user locations and preferences for making location-based recommendations Skyline根据用户的位置和偏好进行查询，从而提供基于位置的推荐

Workshop on Location-based Social Networks Pub Date : 2009-11-03 DOI: 10.1145/1629890.1629893

K. Kodama, Yuichi Iijima, G. Xi, Y. Ishikawa

{"title":"Skyline queries based on user locations and preferences for making location-based recommendations","authors":"K. Kodama, Yuichi Iijima, G. Xi, Y. Ishikawa","doi":"10.1145/1629890.1629893","DOIUrl":"https://doi.org/10.1145/1629890.1629893","url":null,"abstract":"Due to the recent development of mobile computing and communication network technologies, information services for mobile phone users and car navigation systems have becomeof some importance. Since these mobile devices have limited display sizes, we often need to select carefully the appropriate information to be presented to the user. However, it is not easy to select the \"appropriate\" information because users have different contexts and preferences.\u0000 In this paper, we present an approach to recommending items such as restaurants to a mobile user taking into account his current location and preferences. In our framework, a user initially provides a profile, which records preferences as relative orders within predefined categories such as food types and prices. We then select items to be recommended from the database based on the user's profile as well as the current location. To select good items, we extend the notion of spatial skyline queries to incorporate not only distance information but also categorical preference information.\u0000 Based on the proposed approach, a prototype system has been implemented in a small mobile PC containing a small embedded RDBMS. The facilities of the RDBMS, such as spatial indexes, were used to process our skyline queries effectively.","PeriodicalId":107369,"journal":{"name":"Workshop on Location-based Social Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117112367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 74

Visualizing hot spot analysis result based on mashup 基于mashup的热点分析结果可视化

Workshop on Location-based Social Networks Pub Date : 2009-11-03 DOI: 10.1145/1629890.1629900

Han dong Wang, H. Zou, Y. Yue, Qingquan Li

{"title":"Visualizing hot spot analysis result based on mashup","authors":"Han dong Wang, H. Zou, Y. Yue, Qingquan Li","doi":"10.1145/1629890.1629900","DOIUrl":"https://doi.org/10.1145/1629890.1629900","url":null,"abstract":"Driven by travel demand, the distribution and density of taxi passenger pick-up and drop-off points reflect the attractiveness of an area and thus, can be used to find out hot spots and the movement of human flow, to benefit location-based services (LBS) and transport planning, etc. There exist some point pattern analysis (PPA) methods can facilitate the analysis. But most of them lack of the ability to integrate with location-based data in geo-visualization environment. We build an interactive visualization system based on mashup technique to contain diverse analysis data and applications under one framework. Two PPA methods--Kernel Density Estimation (KDE) and Agglomerative Hierarchical Clustering (AHC) are used to discover the hot spots. Microsoft Virtual Earth is used as data integration and visualization platform by combining with some other web techniques, to display analysis results in both static and dynamic effect. This study on one hand represents a novel application of vehicle trajectory data, reveals urban hot spots and traffic pattern, and addresses data integration and geo-visualization issues on the other hand. Preliminary attempt can benefit LBS and LBSN (Location-based Social Network) related web applications.","PeriodicalId":107369,"journal":{"name":"Workshop on Location-based Social Networks","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121986831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 30