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ExtraLytics

ExtraLytics: Big Data Analytics for Real Estate

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 ExtraLytics project word cloud

Explore the words cloud of the ExtraLytics project. It provides you a very rough idea of what is the project "ExtraLytics" about.

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Project "ExtraLytics" data sheet

The following table provides information about the project.

Coordinator
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD 

Organization address
address: WELLINGTON SQUARE UNIVERSITY OFFICES
city: OXFORD
postcode: OX1 2JD
website: www.ox.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 148˙377 €
 EC max contribution 148˙377 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2014-PoC
 Funding Scheme ERC-POC
 Starting year 2014
 Duration (year-month-day) from 2014-11-01   to  2016-04-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD UK (OXFORD) coordinator 148˙377.00

Map

 Project objective

Data is becoming the key to effective decision making in more and more aspects of modern society. Big data analytics provide insight into complex processes considering a breadth of factors. This promises to increase the efficiency of decision making in areas such as policy making, research, product development, or financial and retail markets. Currently, big data analytics is employed only by technologically savvy organisations with control over the relevant data. This further exacerbates the information asymmetry that has been plaguing many of these areas: real estate where buyers have long suffered from limited information, often controlled by the seller; or retail markets where sellers are now employing sophisticated competitive price intelligence solutions unaffordable to buyers. Who can tell you if it is better to buy a house with a garden or with a garage; or where renovations will yield more rent over time? ExtraLytics answers these questions through a combination of big data extraction and analytics. ExtraLytics introduces analytics and prediction models into DIADEM’s platform for accurate big data extraction from the web, which is able to extract required data at massive scale from the web. For the proof-of-concept, ExtraLytics initially focuses on residential real estate in the UK, a £4,135bn market (UBS), where buyers and renters are required to make fast decision with limited information—time on market is often below a week or even below a day as for desirable rentals in Oxford. “In an age when ‘big data’ is shaping our every move, how come an industry that takes so much profit can’t keep pace with technology and use it to actually deliver a service worth the money they take in commission?” (The Telegraph). ExtraLytics addresses this lack of data-driven analytics by giving consumers and investors alike a tool for better understanding properties, their location, their neighborhood, and their investment potential compared to other properties.

 Publications

year authors and title journal last update
List of publications.
2015 Stefano Ortona, Giorgio Orsi, Marcello Buoncristiano, Tim Furche
WADaR
published pages: 1996-1999, ISSN: 2150-8097, DOI: 10.14778/2824032.2824120
Proceedings of the VLDB Endowment 8/12 2019-07-23
2016 Tim Furche, Giovanni Grasso, Michael Huemer, Christian Schallhart, Michael Schrefl
P ea CE-Ful Web Event Extraction and Processing as Bitemporal Mutable Events
published pages: 1-47, ISSN: 1559-1131, DOI: 10.1145/2911989
ACM Transactions on the Web 10/3 2019-07-23
2015 Marco Calautti, Georg Gottlob, Andreas Pieris
Chase Termination for Guarded Existential Rules
published pages: , ISSN: , DOI:
Proceedings of the 9th Alberto Mendelzon International Workshop on Foundations of Data Management, Lima, Peru, May 6 - 8, 2015 1378 2019-07-23

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The information about "EXTRALYTICS" are provided by the European Opendata Portal: CORDIS opendata.

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