mining interesting locations and travel sequences from gps trajectories pdf

Mining Interesting Locations And Travel Sequences From Gps Trajectories Pdf

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Traveling to unfamiliar regions require a significant effort from novice travelers to plan where to go within a limited duration. In this paper, we propose a smart recommendation for highly efficient and balanced itineraries based on multiple user-generated GPS trajectories.

Mining interesting locations and travel sequences from GPS trajectories

With the increasing use of GPS-enabled mobile phones, geo-tagging, which refers to adding GPS information to media such as micro-blogging messages or photos, has seen a surge in popularity recently. This enables us to not only browse information based on locations, but also discover patterns in the location-based behaviors of users. Many techniques have been developed to find the patterns of people's movements using GPS data, but latent topics in text messages posted with local contexts have not been utilized effectively. In this paper, we present a latent topic-based clustering algorithm to discover patterns in the trajectories of geo-tagged text messages. We propose a novel probabilistic model to capture the semantic regions where people post messages with a coherent topic as well as the patterns of movement between the semantic regions. Based on the model, we develop an efficient inference algorithm to calculate model parameters.

Here, interesting locations mean the culturally important places, such as Tiananmen Square in Beijing, and frequented public areas, like shopping malls and restaurants, etc. Such information can help users understand surrounding locations, and would enable travel recommendation. This model infers the interest of a location by taking into account the following three factors. We evaluated our system using a large GPS dataset collected by users over a period of one year in the real world. As a result, our HITS-based inference model outperformed baseline approaches like rank-by-count and rank-by-frequency. Abstract Related Info.

Abstract :. Code :. Data :. Mining interesting locations and travel sequences from GPS trajectories. Lizhu Zhang. Cited by : Bibtex Views Links.

Mining Interesting Locations and Travel Sequences From GPS Trajectories

Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: Zheng and L. Zhang and X. Xie and W. Zheng , L.

Background GPS-enabled devices have become prevalent These devices enable us to record our location history with GPS trajectories Human location history is a big cake given the large number of GPS phones. Motivation When people come to an unfamiliar city Whats the top interesting locations in this city How should I travel among these places travel sequences A map does not make much sense to a freshman. Difficulty What is a location? How to determine a users travel experience? The location interest and user travel are region-related are relative value Ranking problem. Stands for a geo-region where a user has stayed for a while Carry a semantic meaning beyond a raw GPS point. Solution 2.

Mining interesting locations and travel sequences from GPS trajectories

Background GPS-enabled devices have become prevalent These devices enable us to record our location history with GPS trajectories Human location history is a big cake given the large number of GPS phones. Motivation When people come to an unfamiliar city Whats the top interesting locations in this city How should I travel among these places travel sequences A map does not make much sense to a freshman. Difficulty What is a location?

ГЛАВА 97 Фонтейн стремительно вбежал в комнату для заседаний. Бринкерхофф и Мидж последовали за. - Смотрите! - сдавленным голосом сказала Мидж, махнув рукой в сторону окна. Фонтейн посмотрел на вспышки огней в куполе шифровалки. Глаза его расширились.

Нам обоим грозит опасность. Сьюзан не верила ни единому его слову. Хейл подтянул ноги и немного приподнялся на корточках, желая переменить позу.

1. Introduction

Я же сказал тебе… - Но это была не Мидж. Джабба удивленно заморгал.  - Соши. Соши Кута, тонкая как проволока, весила не больше сорока килограммов. Она была его помощницей, прекрасным техником лаборатории систем безопасности, выпускницей Массачусетс кого технологического института. Она часто работала с ним допоздна и, единственная из всех сотрудников, нисколько его не боялась.

Часы показывали два часа с минутами по местному времени. Возле главного здания аэровокзала Беккер въехал на тротуар и соскочил с мотоцикла, когда тот еще двигался. Машина упала на бок и замерла. На затекших ногах Беккер прошел через вращающуюся дверь. Больше никаких мотоциклов, пообещал он. Ярко освещенное помещение аэровокзала сияло стерильной чистотой. Здесь не было ни души, если не считать уборщицы, драившей пол.

 - С ним все будет в порядке.

Коммандер поднес его к уху. - В чем дело? - рявкнул он и замолчал, внимательно слушая собеседника. Сьюзан на какое-то время забыла про Хейла. Она молила Бога, чтобы Стратмору звонил Дэвид. Скажи мне скорей, что с ним все в порядке, - думала .

 Читайте! - Джабба обливался.  - В чем разница. Должна же она. - Да! - Соши ткнула пальцем в свой монитор.  - Смотрите.

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4 Comments

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  2. Dawn R.

    In this paper, based on multiple users' GPS trajectories, we aim to mine interesting locations and classical travel sequences in a given geospatial region. Here.

    26.05.2021 at 20:35 Reply
  3. AndrГ© G.

    based on multiple users' GPS trajectories, we aim to mine interesting locations and classical travel sequences in a given geospatial region.

    29.05.2021 at 14:53 Reply
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