23
Andrei Tabarcea , Matti Mononen 6.03.2013 World-wide location- based search using OpenStreetMap
| Date post: | 31-Mar-2015 |
| Category: |
Documents |
| Upload: | karley-truett |
| View: | 214 times |
| Download: | 0 times |
Andrei Tabarcea, Matti Mononen
6.03.2013
World-wide location-based search using
OpenStreetMap
Joint PhD degree candidate for University of Eastern Finland and Technical University of Iasi, Romania
ECSE grant 2012 & 2013Proposed graduation 2014, supervisor prof.
Pasi FräntiThesis “Location-based applications”Research part of Mopsi project
http://cs.uef.fi/mopsi
Andrei Tabarcea
A. Tabarcea, K. Waga, Z. Wan and P. Fränti, "O-Mopsi: Mobile Orienteering Game Using Geotagged Photos", Int. Conf. on Web Information Systems & Technologies (WEBIST'13), Aachen, Germany, 8-10 May 2013.
K. Waga, A. Tabarcea, R. Mariescu-Istodor and P. Fränti, "Real Time Access to Multiple GPS Tracks", Int. Conf. on Web Information Systems & Technologies (WEBIST'13), Aachen, Germany, 8-10 May 2013.
K. Waga, A. Tabarcea, R. Mariescu-Istodor and P. Fränti, "System for real time storage, retrieval and visualization of GPS tracks", Int. Conf. System Theory, Control and Computing (ICSTCC 2012), Sinaia, Romania, Vol. 2, October 2012.
K. Waga, A. Tabarcea, M. Chen and P. Fränti, "Detecting movement type by route segmentation and classification", IEEE Int. Conf. on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom'12), Pittsburgh, USA, 2012
K. Waga, A. Tabarcea and P. Fränti, "Recommendation of points of interest from user generated data collection", IEEE Int. Conf. on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom'12), Pittsburgh, USA, 2012.
Publications 2012-2013
How to find location-information in web-pages?
Location-based search
Site hosting informationdomain: uef.fidescr: ITÄ-SUOMEN YLIOPISTO (UNIV OF EASTERN FINLAND)descr: 22857339address: TIETOTEKNIIKKAKESKUS (IT-CENTRE)/Jarno Huuskonenaddress: PL 1627address: 70211address: KUOPIO FINLANDphone: +358 44 7162810status: Grantedcreated: 26.5.2010modified: 19.8.2011expires: 26.5.2015nserver: ns-secondary.funet.fi [Ok]nserver: ns1.uef.fi [Ok]nserver: ns2.uef.fi [Ok]dnssec: no
geo-tags, address-tags, vcards for Google Maps etc.
HTML tags
<HTML><HEAD profile"="http://geotags.com/geo>
<META name="geo.position" content="62.35;29.44"> <META name="geo.region" content="FI"><META name="geo.placename" content="Joensuu"> <META http-equiv="Content-Type" content="text/html; charset=iso-8859-1"><link rel="stylesheet" href="http://www.joensuu.fi/tkt/sivutyyli.css" type="text/css"><TITLE>Pages of Pasi Fränti</TITLE></HEAD>
Natural language descriptions
Scouts' Youth Hostel (8.3 km from Joensuu Airport) Show map
Good, 7.4 Latest booking: January 23 Scouts’ Youth Hostel is located at the outfall of River Pielisjoki, 1.5 km from Joensuu city centre. It offers free Wi-Fi and rooms with shared bathroom and kitchen facilities. OlgaSaint-Petersburg, Russia "Great price for the nice room. Friendly stuff, cozy atmosphere. But a bit loud."
from € 46
Postal addresses
Input:
• user location (lat, lon)
• keywords
Output: list of services containing:
• name/title
• website
• address (street, number. city)
• location (lat, lon)
• image
• other info (opening hours, telephone etc.)
Main idea:
• preprocess the search results of an external search engine (Google, Yahoo, Bing etc.) by detecting postal address in order to find the location
Mopsi search
1. Convert user location (lat, lon) into user address = Geocoding step
2. Search with the query "keyword+city" using an external search engine API and download the first k results (web pages) = Web page retrieval step
3. Detect addresses and additional informatio from the downloaded web pages = Data mining step
4. Ranking the results (distance, relevance etc.) = Ranking step
5. Display the search results to the user
Proposed steps
1. Geocode
r 2.
Web page
retrieval
3. Data minin
g
4. Result rankin
gUser
lat, lon
keywords
web page
s
result list
5. ranked result
list
Geocoding
Geocoder Web
page retrieva
l
Data minin
g
Result rankin
gUser
lat, lon
keywords
web page
s
result list
ranked result
list
Convert user location (lat, lon) into user address using:
Web page retrieval
Geocoder Web
page retrieva
l
Data minin
g
Result rankin
gUser
lat, lon
keywords
web page
s
result list
ranked result
list
Download k webpages from the query <keyword, city> using API of:
Ranking
Geocoder Web
page retrieva
l
Data minin
g
Result rankin
gUser
lat, lon
keywords
web page
s
result list
ranked result
list
Main criterion: distance from the user’s location
Future idea: relevance to user’s profile and history
Data mining
Geocoder Web
page retrieva
l
Data minin
g
Result rankin
gUser
lat, lon
keywords
web page
s
result list
ranked result
list
Main idea:
Find location information in HTML pages by detecting postal addresses
Steps:
1. Parse and segment the HTML page
2. Identify addresses and locations
3. Identify the services the addresses are pointing to (name/title)
4. Retrieve extra information (photos, opening hours, telephone etc.)
Extract text from HTML pages
Segmentation of web pages using DOM tree
Parsing HTML pagesONLINE TILAUS RAVINTOLAT Ravintola Deli Istanbul Kotiinkuljetus Nouto11.00-21.00 Pilkkitie 1, Joensuu, Rantakylä Avoinna - Kotiinkuljetus - Nouto La Dolce Vita Kotiinkuljetus Nouto10.00-21.00 Wahlforssinkatu 6, Joensuu, Ke.. Avoinna - Kotiinkuljetus - Nouto
• Rule-based pattern matching algorithm• Starting point: the detection of street-names• An address-block candidate is constructed by detecting:
• street names and number• postal codes• municipal names
• We will use OpenStreetMap database for global detection
Postal address detection
Street namesStreetnumbers
City namesTelephonenumbers
Web page example - Homepage
DOM tree
blue: links (the A tag)red: tables (TABLE, TR and TD tags)green: dividers (DIV tag)violet: images (the IMG tag)yellow: forms (FORM, INPUT, TEXTAREA, SELECT and OPTION tags)orange: linebreaks and blockquotes (BR, P, and BLOCKQUOTE tags)black: HTML tag, the root nodegray: all other tags
DOM subtree
<html>
<body>
<table> <td>
<tr> <div>
<table>
<tr><td>PizzaPojat Niinivaara
Niinivaarantie 19
80200 Joensuu
013 - 137 017
<br/>
<div>
<table align="center“> <tr> <td> <div id="footerleft"> <h3>PizzaPojat Niinivaara</h3> <p>Niinivaarantie 19</p> <p>80200 Joensuu</p> <br /> <p>013 - 137 017</p> </div> <td> </tr> </table>
Web page example - Catalog
Web page example - Catalog
Bosbor kebab
Fiesta
Miami
<html>
<body>
<table> <td>
<tr> <div>
<table>
<tr><td>PizzaPojat Niinivaara
Niinivaarantie 19
80200 Joensuu
013 - 137 017
<br/>
1. Convert HTML pages to xHTML for using xQuery
2. Detect addresses and postal codes
3. Break the DOM tree into subtrees
4. Use heuristics and regular expressions to detect extra information from the subtree (service name, telephone, opening hours etc.)
Implementation
Thank you
Questions?
