Paper Info
Title
Open Data for Local Search: Challenges and Perspectives.
Abstract
Local search engines are specialized information retrieval systems enabling users to discover amenities and services in their neighbourhood. Developing a local search system still raises scientific questions, as well as very specific technical issues. Those issues come for example from the lack of information about local events and actors, or the specific form taken by the indexable data. Available open data can be exploited to dramatically improve the design of local search engines and their content. The purpose of this workshop is to explore new fields of investigation both in terms of algorithmic approaches as well as originality of usable data. The workshop focuses on how open data can be used to enhance the capabilities of local search engines.
Year
DOI
Venue
2016
10.1145/2872518.2890487
WWW '16: 25th International World Wide Web Conference Montréal Québec Canada April, 2016
Field
DocType
ISBN
USable,Data science,Open data,Data mining,World Wide Web,Search engine,Semantic search,Computer science,Semantic Web,Originality,Neighbourhood (mathematics),Local search (optimization)
Conference
978-1-4503-4144-8
Citations 
PageRank 
References 
0
0.34
11
Authors
3
Name
Order
Citations
PageRank
Eric Charton1458.94
Nizar Ghoula2163.60
Marie-Jean Meurs39415.32