关于微软研究院(谢幸、郑宇研究员主导的)“智能城市”“智能生活”研究的一个归纳...

2019独角兽企业重金招聘Python工程师标准>>> hot3.png

微软亚洲研究院基于GPS数据展开的研究工作,取得了另学术界瞩目的成就。从2008年开始每年都在顶级的计算机类会议上有文章发出,掀起了研究GPS数据智能化处理的热潮。

       他们的工作由谢幸研究员和郑宇研究员主导。实验数据采集主要有两个工程:

1、Geolife工程使用的,170多个志愿者4年左右的GPS轨迹;

2、北京市2万多出租车约3个月的行驶轨迹。

参见:http://research.microsoft.com/en-us/projects/geolife/

    个人将近年来该小组发表的论文做了下整理,归纳其研究脉络如下(个人愚见,仅供拍砖,前面序号按照文章发表时间倒序排列,时间排列文献全表见最后的“参考文献”部分):

阶段一:   GPS+webGIS:(GPS数据在GIS地图上的灵活展示和使用)

41、(生成用户日志,帮助用户回忆),Searching Your Life on Web Maps,SIGIR2008

42、(GeoLife1.0,在地图上管理自己的GPS日志)GeoLife:Managing and Understanding Your Past Life over Maps,MDM08

阶段二:GPS数据的简单挖掘(出行方式,用户轨迹的相似性,关联规则,异常行为,群组发现)

40、(理解用户行为),Understanding User Behavior Geospatially,计算机通信2008

36、(出行模式:步行,公交,驾驶)Learning Transportation Mode from Raw GPS Data for GeographicApplication on the Web,www2008

37、(理解移动特性),Understanding mobility based on GPS data,ubicom2008

38、(基于轨迹挖掘用户相似性)Mining user similarity based on location history,GIS2008

33、(挖掘有趣位置及旅行顺序)Mining Interesting Locations and Travel Sequences From GPSTrajectories,WWW 2009

34、(挖掘个人生活模式)Mining Individual Life Pattern Based on Location History,MDM 2009

35、(GeoLife生活模式),GeoLife2.0: A Location-Based Social Networking Service,MDM2009

30、(挖掘位置间的关联),Mining Correlation Between Locations Using Human Location History,GIS 2009

29、(基于GPS轨迹发现用户交通模式:行走、驾车、公交、地铁),Understanding transportation modes based on GPS data for Webapplications,ACMTransaction on the Web,2010

23、(学习位置间的关联)Learning Location Correlation from GPS trajectories,MDM2010

9、(交通异常,前一个版本)Discovering Spatio-Temporal Causal Interactions in Traffic DataStreams,sigkdd2011

1、群组发现(提出了一个群组发现加速的数据结构):A Framework of Traveling Companion Discovery on Trajectory DataStreams,ICDE2012

阶段三:结合外部信息,提供基于云的LBS服务

27、(计算机学会刊文)Enabling smart location-based services by mining GPS traces,Communication of China ComputerFederation2010

28、(基于云的位置服务)Location-Based Services on the Cloud,Journal on Digital Mobile Era 2010

10、(基于云的,融合多种信息,探寻用户习惯的发现)Driving with Knowledge from the Physical World,SIGKDD 2011

阶段四:同协同过滤等算法结合实现位置、活动的推荐

24、(位置和活动推荐)Collaborative Location and Activity Recommendations With GPS HistoryData,WWW 2010

22、(基于用户的推荐,旅游景点和行程)Collaborative Filtering Meets Mobile Recommendation: A User-centeredApproach, AAAI2010

20、(前期版本,智能的行程推荐)Smart Itinerary Recommendation based on User-Generated GPSTrajectories,UIC2010

21、(GeoLife,智能生活,双层网络),GeoLife: A Collaborative Social Networking Service among User,location and trajectory,IEEE Data(base) Engineering Bulletin

14、(旅游推荐,较全面的工作),Learning travel recommendations from user-generated GPS traces, ACM Transaction onIntelligent Systems and Technology,2011

15、(根据单个轨迹推荐位置和朋友),Recommending friends and locations based on individual locationhistory,2011

12、(个人行程推荐,最初版本),Social Itinerary Recommendation from User-generated Digital Trails,Personal and Ubiquitous Computing

2、热点旅游位置推荐、周边活动发现(第二次发表:协同过滤):Towards Mobile Intelligence: Learning from GPS History Data forCollaborative Recommendation, Artificial Intelligence Journal,2012-04-29

阶段五:引入语义轨迹,泛华推荐和相似性算法

19、(利用语义轨迹,发现相似用户),Finding Similar Users Using Category-Based Location History,GIS2010

3、(语义轨迹历史)基于GPS推到用户的社会关系:InferringSocial Ties between Users with Human Location History,Journal of Ambient Intelligence andHumanized Computing

阶段六:根据出租车数据,实现智能化驾驶

16、(根据出租车历史,指导行驶方向)T-Drive: Driving Directions Based on Taxi Trajectories,GIS,2010

17、(出租司机,灵活驾驶)Drive smartly as a taxi driver,UIC2010

13、(推到出租车行驶状况),Inferring Taxi Status Using GPS Trajectories,2011

6、出租车数据探测城市的异常交通:On Mining Anomalous Patterns in Road Traffic Streams:2011International Conference on Advanced Data Mining and Applications

7、(基于出租数据的城市规划,计算)Urban Computing with Taxicabs,

8、(寻找下一个旅客)Where to Find My Next Passenger?Ubicom2011

4、基于时间关系图发现出租车行驶路线:T-Drive: Enhancing Driving Directions with Taxi Drivers'Intelligence,IEEETransactions on Knowledge and Data Engineering (TKDE)

(贯穿)轨迹的预处理类工作:

39、(灵活的时空索引),A Flexible Spatio-temporal Indexing Scheme for Large-scale GPS TrackRetrieval,2008

32、(基于客观需求的,轨迹简化策略,方向变化的位置信息量越大)Trajectory Simplification Method for Location-Based SocialNetworking Services,SIGSPATIAL GIS workshop on location-based social networks,2009

31、(稀疏采样轨迹的地图匹配)Map-Matching for Low-Sampling-Rate GPS Trajectories,GIS2009

26、(Top-k区域查询)AnsweringTop-k Similar Region Queries,DASFAA 2010

25、(基于位置点,搜索轨迹)Searching Trajectories by Locations: An Efficiency Study,SIGMOD

18、(发现数据库中的相似记录),Detecting Nearly Duplicated Records in Location Datasets,GIS2010

11、(给定一组点,检索k个最近邻的点)Retrievingk-Nearest Neighboring Trajectories by a Set of Point Locations,SSTD2011

5、低采样轨迹的不确定性处理(比地图匹配性能更好):Reducing Uncertainty of Low-Sampling-Rate Trajectories, ICDE 2012

参考文献:(按照时间降序,从新到旧排列)

2012

1、群组发现(提出了一个群组发现加速的数据结构):A Framework of Traveling Companion Discovery on Trajectory DataStreams,ICDE2012

2、热点旅游位置推荐、周边活动发现(第二次发表:协同过滤):Towards Mobile Intelligence: Learning from GPS History Data forCollaborative Recommendation, Artificial Intelligence Journal,2012-04-29

3、(语义轨迹历史)基于GPS推到用户的社会关系:InferringSocial Ties between Users with Human Location History,Journal of Ambient Intelligence andHumanized Computing

4、基于时间关系图发现出租车行驶路线:T-Drive: Enhancing Driving Directions with Taxi Drivers'Intelligence,IEEETransactions on Knowledge and Data Engineering (TKDE)

5、低采样轨迹的不确定性处理(比地图匹配性能更好):Reducing Uncertainty of Low-Sampling-Rate Trajectories, ICDE 2012

2011:

6、出租车数据探测城市的异常交通:On Mining Anomalous Patterns in Road Traffic Streams:2011International Conference on Advanced Data Mining and Applications

7、(基于出租数据的城市规划,计算)Urban Computing with Taxicabs,

8、(寻找下一个旅客)Where to Find My Next Passenger?Ubicom2011

9、(交通异常,前一个版本)Discovering Spatio-Temporal Causal Interactions in Traffic DataStreams,sigkdd2011

10、(基于云的,融合多种信息,探寻用户习惯的发现)Driving with Knowledge from the Physical World,SIGKDD 2011

11、(给定一组点,检索k个最近邻的点)Retrievingk-Nearest Neighboring Trajectories by a Set of Point Locations,SSTD2011

12、(个人行程推荐,最初版本),Social Itinerary Recommendation from User-generated Digital Trails,Personal and Ubiquitous Computing

13、(推到出租车行驶状况),Inferring Taxi Status Using GPS Trajectories,2011

14、(旅游推荐,较全面的工作),Learning travel recommendations from user-generated GPS traces, ACM Transaction onIntelligent Systems and Technology,2011

15、(根据单个轨迹推荐位置和朋友),Recommending friends and locations based on individual locationhistory,2011

2010

16、(根据出租车历史,指导行驶方向)T-Drive: Driving Directions Based on Taxi Trajectories,GIS,2010

17、(出租司机,灵活驾驶)Drive smartly as a taxi driver,UIC2010

18、(发现数据库中的相似记录),Detecting Nearly Duplicated Records in Location Datasets,GIS2010

19、(利用语义轨迹,发现相似用户),Finding Similar Users Using Category-Based Location History,GIS2010

20、(前期版本,智能的形成推荐)Smart Itinerary Recommendation based on User-Generated GPSTrajectories,UIC2010

21、(GeoLife,智能生活,双层网络),GeoLife: A Collaborative Social Networking Service among User,location and trajectory,IEEE Data(base) Engineering Bulletin

22、(基于用户的推荐,旅游景点和形成)Collaborative Filtering Meets Mobile Recommendation: A User-centeredApproach, AAAI2010

23、(学习位置间的关联)Learning Location Correlation from GPS trajectories,MDM2010

24、(位置和活动推荐)Collaborative Location and Activity Recommendations With GPS HistoryData,WWW 2010

25、(基于位置点,搜索轨迹)Searching Trajectories by Locations: An Efficiency Study,SIGMOD 2010

26、(Top-k区域查询)AnsweringTop-k Similar Region Queries,DASFAA 2010

27、(计算机学会刊文)Enabling smart location-based services by mining GPS traces,Communication of China ComputerFederation2010

28、(基于云的位置服务)Location-Based Services on the Cloud,Journal on Digital Mobile Era 2010

29、(基于GPS轨迹发现用户交通模式:行走、驾车、公交、地铁),Understanding transportation modes based on GPS data for Webapplications,ACMTransaction on the Web,2010

2009

30、(挖掘位置间的关联),Mining Correlation Between Locations Using Human Location History,GIS 2009

31、(稀疏采样轨迹的地图匹配)Map-Matching for Low-Sampling-Rate GPS Trajectories,GIS2009

32、(基于客观需求的,轨迹简化策略,方向变化的位置信息量越大)Trajectory Simplification Method for Location-Based SocialNetworking Services,SIGSPATIAL GIS workshop on location-based social networks,2009

33、(挖掘有趣位置及旅行顺序)Mining Interesting Locations and Travel Sequences From GPSTrajectories,WWW 2009

34、(挖掘个人生活模式)Mining Individual Life Pattern Based on Location History,MDM 2009

35、(GeoLife生活模式),GeoLife2.0: A Location-Based Social Networking Service,MDM2009

2008

36、(出行模式:步行,公交,驾驶)Learning Transportation Mode from Raw GPS Data for GeographicApplication on the Web,www2008

37、(理解移动特性),Understanding mobility based on GPS data,ubicom2008

38、(基于轨迹挖掘用户相似性)Mining user similarity based on location history,GIS2008

39、(灵活的时空索引),A Flexible Spatio-temporal Indexing Scheme for Large-scale GPS TrackRetrieval,2008

40、(理解用户行为),Understanding User Behavior Geospatially,计算机通信2008

41、(生成用户日志,帮助用户回忆),Searching Your Life on Web Maps,SIGIR2008

42、(GeoLife1.0,在地图上管理自己的GPS日志)GeoLife:Managing and Understanding Your Past Life over Maps,MDM08

转载于:https://my.oschina.net/u/999578/blog/159383

你可能感兴趣的:(关于微软研究院(谢幸、郑宇研究员主导的)“智能城市”“智能生活”研究的一个归纳...)