标题: 探勘社交媒体之轨迹模式于旅程规划
Mining Trajectory Patterns from Social Media for Trip Planning
作者: 彭文志
Peng Wen-Chih
国立交通大学资讯工程学系(所)
关键字: 轨迹资料探勘;社交媒体;旅程规划;trajectory pattern mining;social media mining and trip planning
公开日期: 2015
摘要: 近年智慧型手持装志科技的进步与社交媒体成为使用者分享资讯的平台,使得
地理资讯相关的服务也逐渐普及,像是许多行动社群网路 (Location-based Social
Networks) 相关的服务如Facebook、Foursquare 等都提供使用者在社群上分享个人所在
位置。许多人会在旅游或日常生活时将自己所在的地理位置或是照片分享于社群之上
(如分享照片和打卡 (check-in)),增加与社群上成员的互动。目前已经有许多网站提供
使用者上传个人的轨迹供其他人参考并增加更多互动,使用者得以分享其旅游的轨迹资
讯供其他使用者参考。在本计划中,我们预计提出一系列的资料探勘演算法于社交媒体
资料,找寻使用者的轨迹模式。透过这个轨迹模式,我们拟提出旅程规划的平台,在此
平台上透过所探勘的轨迹模式,用以协助使用者更为方便地规划旅程。
本计画是为期三年之计画 ‘探勘社交媒体之轨迹模式于旅程规划’。在此计画中,
将专注于从社交媒体中探勘使用者的移动模式,使用于旅程规划推荐服务。其中社群媒
体探勘包含了含有地理资讯(经纬度座标)和拜访该地点的时间的资料,如轨迹资讯、
打卡资讯、相片等资料中,探勘使用者移动模式,并根据探勘出的使用者移动模式和使
用者所输入的旅游路径偏好,计算并推荐合适的旅游路径。其中使用者移动模式将考量
三个部分,顺序因素 (Ordering factor)、时间因素 (Time factor) 和社群因素 (Social
factor)。具体而言,在第一年,我们将透过社交媒体所包含之 GPS 轨迹资料、照片资料
以及打卡资料,探勘热门的景点资讯。透过这些景点资讯与轨迹资料,提出以轨迹模式
为基础之旅程规划搜寻平台。在第二年,我们进一步透过社交媒体资料,探勘每个景点
地拜访时间分布模式。在旅程规划搜寻平台中,研发(1). 具有适合拜访时间之旅程规划
演算法 (2). 具有使用者查询景点 (query points) 与适合拜访时间之旅程规划演算法。
有鉴于社交媒体上,我们将可探勘使用者社交活动行为模式,在第三年中,我们拟提出
具有社交行为模式的旅程规划演算法。
随着社交媒体与地理资讯服务近年的蓬勃发展,我们相信此计画之执行,将可研
发出适用于轨迹模式为基础之旅程规划规划搜寻平台,提供使用者更为便利的旅程规划
服务。
The increasing availability of location-acquisition technology (e.g., GPS), has led to a
huge volume of spatial trajectories that represent the movement routes of humans. Without
loss of generality, a trajectory is a sequence of data points where each data point records
location information and a time-stamp. For example, users could perform check-in services
(e.g., Foursquare) to note their locations via a mobile phone and share their photos and
activities. The time-ordered check-in records of a user are able to be expressed by trajectories.
Moreover, on a photo sharing website (e.g., Flickr), people share geotagged photos whose
time-stamps and geolocations can be represented as trajectories as well. In our project, we
intend to mine trajectory patterns from social media and develop pattern-aware trajectory
search platform for trip planning.
This project is a three-year project ‘Mining trajectory patterns from social media for trip
planning’, and aims at designing a trip planning platform that consists of mining social media
and trip planning algorithms. Our primary goals include (1) developing Pattern-Aware
Trajectory Search (abbreviated as PATS); (2) proposing pattern-aware trajectory search with
time constraint and user query points; (3) exploring social relationship for trip planning. More
specifically, in the first year, given a spatial range and a user preference of depth/breadth
specified by a user, we develop a Pattern-Aware Trajectory Search (PATS) framework to
retrieve the top K trajectories passing through popular Regions Of Interests (abbreviated as
ROIs). PATS is novel because the returned travel trajectories, discovered from travel patterns
hidden in trip trajectories, may represent the most valuable travel experiences of other
travelers fitting the user’s trip preference in terms of depth or breadth. In the second year, we
aim at mining visiting time distribution of ROIs. Based on the mining results, we propose
PATS with time constraint and PATS with both time constraint and user query points. Due to
the social relationships among users, in the third year, we propose a social-aware trip planning
framework.
In view of the increasing attention on social media and location-based services, we strongly
believe that this project is very timely and will deliver results of both theoretical and practical
importance.
官方说明文件#: NSC102-2221-E009-171-MY3
URI: http://hdl.handle.net/11536/129963
https://www.grb.gov.tw/search/planDetail?id=11260880&docId=452468
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